what is primary research article

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base

Methodology

• Primary Research | Definition, Types, & Examples

Primary Research | Definition, Types, & Examples

Published on January 14, 2023 by Tegan George . Revised on January 12, 2024.

Primary research is a research method that relies on direct data collection , rather than relying on data that’s already been collected by someone else. In other words, primary research is any type of research that you undertake yourself, firsthand, while using data that has already been collected is called secondary research .

Primary research is often used in qualitative research , particularly in survey methodology, questionnaires, focus groups, and various types of interviews . While quantitative primary research does exist, it’s not as common.

Table of contents

When to use primary research, types of primary research, examples of primary research, advantages and disadvantages of primary research, other interesting articles, frequently asked questions.

Primary research is any research that you conduct yourself. It can be as simple as a 2-question survey, or as in-depth as a years-long longitudinal study . The only key is that data must be collected firsthand by you.

Primary research is often used to supplement or strengthen existing secondary research. It is usually exploratory in nature, concerned with examining a research question where no preexisting knowledge exists. It is also sometimes called original research for this reason.

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

• Academic style
• Vague sentences
• Style consistency

See an example

Primary research can take many forms, but the most common types are:

• Surveys and questionnaires
• Observational studies
• Interviews and focus groups

Surveys and questionnaires collect information about a group of people by asking them questions and analyzing the results. They are a solid choice if your research topic seeks to investigate something about the characteristics, preferences, opinions, or beliefs of a group of people.

Surveys and questionnaires can take place online, in person, or through the mail. It is best to have a combination of open-ended and closed-ended questions, and how the questions are phrased matters. Be sure to avoid leading questions, and ask any related questions in groups, starting with the most basic ones first.

Observational studies are an easy and popular way to answer a research question based purely on what you, the researcher, observes. If there are practical or ethical concerns that prevent you from conducting a traditional experiment , observational studies are often a good stopgap.

There are three types of observational studies: cross-sectional studies , cohort studies, and case-control studies. If you decide to conduct observational research, you can choose the one that’s best for you. All three are quite straightforward and easy to design—just beware of confounding variables and observer bias creeping into your analysis.

Similarly to surveys and questionnaires, interviews and focus groups also rely on asking questions to collect information about a group of people. However, how this is done is slightly different. Instead of sending your questions out into the world, interviews and focus groups involve two or more people—one of whom is you, the interviewer, who asks the questions.

There are 3 main types of interviews:

• Structured interviews ask predetermined questions in a predetermined order.
• Unstructured interviews are more flexible and free-flowing, proceeding based on the interviewee’s previous answers.
• Semi-structured interviews fall in between, asking a mix of predetermined questions and off-the-cuff questions.

While interviews are a rich source of information, they can also be deceptively challenging to do well. Be careful of interviewer bias creeping into your process. This is best mitigated by avoiding double-barreled questions and paying close attention to your tone and delivery while asking questions.

Alternatively, a focus group is a group interview, led by a moderator. Focus groups can provide more nuanced interactions than individual interviews, but their small sample size means that external validity is low.

Primary research can often be quite simple to pursue yourself. Here are a few examples of different research methods you can use to explore different topics.

Primary research is a great choice for many research projects, but it has distinct advantages and disadvantages.

Advantages of primary research

Advantages include:

• The ability to conduct really tailored, thorough research, down to the “nitty-gritty” of your topic . You decide what you want to study or observe and how to go about doing that.
• You maintain control over the quality of the data collected, and can ensure firsthand that it is objective, reliable , and valid .
• The ensuing results are yours, for you to disseminate as you see fit. You maintain proprietary control over what you find out, allowing you to share your findings with like-minded individuals or those conducting related research that interests you for replication or discussion purposes.

Disadvantages of primary research

Disadvantages include:

• In order to be done well, primary research can be very expensive and time consuming. If you are constrained in terms of time or funding, it can be very difficult to conduct your own high-quality primary research.
• Primary research is often insufficient as a standalone research method, requiring secondary research to bolster it.
• Primary research can be prone to various types of research bias . Bias can manifest on the part of the researcher as observer bias , Pygmalion effect , or demand characteristics . It can occur on the part of participants as a Hawthorne effect or social desirability bias .

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Chi square goodness of fit test
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Inclusion and exclusion criteria

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

The 3 main types of primary research are:

Exploratory research aims to explore the main aspects of an under-researched problem, while explanatory research aims to explain the causes and consequences of a well-defined problem.

There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control and randomization.

In restriction , you restrict your sample by only including certain subjects that have the same values of potential confounding variables.

In matching , you match each of the subjects in your treatment group with a counterpart in the comparison group. The matched subjects have the same values on any potential confounding variables, and only differ in the independent variable .

In statistical control , you include potential confounders as variables in your regression .

In randomization , you randomly assign the treatment (or independent variable) in your study to a sufficiently large number of subjects, which allows you to control for all potential confounding variables.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analyzing data from people using questionnaires.

When conducting research, collecting original data has significant advantages:

• You can tailor data collection to your specific research aims (e.g. understanding the needs of your consumers or user testing your website)
• You can control and standardize the process for high reliability and validity (e.g. choosing appropriate measurements and sampling methods )

However, there are also some drawbacks: data collection can be time-consuming, labor-intensive and expensive. In some cases, it’s more efficient to use secondary data that has already been collected by someone else, but the data might be less reliable.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

George, T. (2024, January 12). Primary Research | Definition, Types, & Examples. Scribbr. Retrieved April 3, 2024, from https://www.scribbr.com/methodology/primary-research/

Is this article helpful?

Tegan George

Other students also liked, data collection | definition, methods & examples, observer bias | definition, examples, prevention, what is qualitative research | methods & examples, unlimited academic ai-proofreading.

✔ Document error-free in 5minutes ✔ Unlimited document corrections ✔ Specialized in correcting academic texts

Purdue Online Writing Lab Purdue OWL® College of Liberal Arts

What is Primary Research and How do I get Started?

Welcome to the Purdue OWL

This page is brought to you by the OWL at Purdue University. When printing this page, you must include the entire legal notice.

Copyright ©1995-2018 by The Writing Lab & The OWL at Purdue and Purdue University. All rights reserved. This material may not be published, reproduced, broadcast, rewritten, or redistributed without permission. Use of this site constitutes acceptance of our terms and conditions of fair use.

Primary research involves collecting data about a given subject directly from the real world. This section includes information on what primary research is, how to get started, ethics involved with primary research and different types of research you can do. It includes details about interviews, surveys, observations, and analyses.

Primary research is any type of research that you collect yourself. Examples include surveys, interviews, observations, and ethnographic research. A good researcher knows how to use both primary and secondary sources in their writing and to integrate them in a cohesive fashion.

Conducting primary research is a useful skill to acquire as it can greatly supplement your research in secondary sources, such as journals, magazines, or books. You can also use it as the focus of your writing project. Primary research is an excellent skill to learn as it can be useful in a variety of settings including business, personal, and academic.

But I’m not an expert!

With some careful planning, primary research can be done by anyone, even students new to writing at the university level. The information provided on this page will help you get started.

What types of projects or activities benefit from primary research?

When you are working on a local problem that may not have been addressed before and little research is there to back it up.

When you are working on writing about a specific group of people or a specific person.

When you are working on a topic that is relatively new or original and few publications exist on the subject.

You can also use primary research to confirm or dispute national results with local trends.

What types of primary research can be done?

Many types of primary research exist. This guide is designed to provide you with an overview of primary research that is often done in writing classes.

Interviews: Interviews are one-on-one or small group question and answer sessions. Interviews will provide a lot of information from a small number of people and are useful when you want to get an expert or knowledgeable opinion on a subject.

Surveys: Surveys are a form of questioning that is more rigid than interviews and that involve larger groups of people. Surveys will provide a limited amount of information from a large group of people and are useful when you want to learn what a larger population thinks.

Observations: Observations involve taking organized notes about occurrences in the world. Observations provide you insight about specific people, events, or locales and are useful when you want to learn more about an event without the biased viewpoint of an interview.

Analysis: Analysis involves collecting data and organizing it in some fashion based on criteria you develop. They are useful when you want to find some trend or pattern. A type of analysis would be to record commercials on three major television networks and analyze gender roles.

Where do I start?

Consider the following questions when beginning to think about conducting primary research:

• What do I want to discover?
• How do I plan on discovering it? (This is called your research methods or methodology)
• Who am I going to talk to/observe/survey? (These people are called your subjects or participants)
• How am I going to be able to gain access to these groups or individuals?
• What are my biases about this topic?
• How can I make sure my biases are not reflected in my research methods?
• What do I expect to discover?

• Student Services
• Faculty Services

Peer Review and Primary Literature: An Introduction: Is it Primary Research? How Do I Know?

• Scholarly Journal vs. Magazine
• Peer Review: What is it?
• Finding Peer-Reviewed Articles
• Primary Journal Literature
• Is it Primary Research? How Do I Know?

Components of a Primary Research Study

As indicated on a previous page, Peer-Reviewed Journals also include non -primary content. Simply limiting your search results in a database to "peer-reviewed" will not retrieve a list of only primary research studies.

Learn to recognize the parts of a primary research study. Terminology will vary slightly from discipline to discipline and from journal to journal.  However, there are common components to most research studies.

When you run a search, find a promising article in your results list and then look at the record for that item (usually by clicking on the title). The full database record for an item usually includes an abstract or summary--sometimes prepared by the journal or database, but often written by the author(s) themselves. This will usually give a clear indication of whether the article is a primary study.  For example, here is a full database record from a search for family violence and support in SocINDEX with Full Text :

Although the abstract often tells the story, you will need to read the article to know for sure. Besides scanning the Abstract or Summary, look for the following components: (I am only capturing small article segments for illustration.)

Look for the words METHOD or METHODOLOGY . The authors should explain how they conducted their research.

NOTE: Different Journals and Disciplines will use different terms to mean similar things. If instead of " Method " or " Methodology " you see a heading that says " Research Design " or " Data Collection ," you have a similar indicator that the scholar-authors have done original research.

Look for the section called RESULTS . This details what the author(s) found out after conducting their research.

Charts , Tables , Graphs , Maps and other displays help to summarize and present the findings of the research.

A Discussion indicates the significance of findings, acknowledges limitations of the research study, and suggests further research.

References , a Bibliography or List of Works Cited indicates a literature review and shows other studies and works that were consulted. USE THIS PART OF THE STUDY! If you find one or two good recent studies, you can identify some important earlier studies simply by going through the bibliographies of those articles.

A FINAL NOTE:  If you are ever unclear about whether a particular article is appropriate to use in your paper, it is best to show that article to your professor and discuss it with them.  The professor is the final judge since they will be assigning your grade.

Subject Guide

• << Previous: Primary Journal Literature
• Last Updated: Nov 16, 2022 12:46 PM
• URL: https://suffolk.libguides.com/PeerandPrimary

Identifying Primary and Secondary Research Articles

• Primary and Secondary

Primary Research Articles

Primary research articles report on a single study. In the health sciences, primary research articles generally describe the following aspects of the study:

• The study's hypothesis or research question
• Some articles will include information on how participants were recruited or identified, as well as additional information about participants' sex, age, or race/ethnicity
• A "methods" or "methodology" section that describes how the study was performed and what the researchers did
• Results and conclusion section

Secondary Research Articles

Review articles are the most common type of secondary research article in the health sciences. A review article is a summary of previously published research on a topic. Authors who are writing a review article will search databases for previously completed research and summarize or synthesize those articles,  as opposed to recruiting participants and performing a new research study.

Specific types of review articles include:

• Systematic Reviews
• Meta-Analysis
• Narrative Reviews
• Integrative Reviews
• Literature Reviews

Review articles often report on the following:

• The hypothesis, research question, or review topic
• Databases searched-- authors should clearly describe where and how they searched for the research included in their reviews
• Systematic Reviews and Meta-Analysis should provide detailed information on the databases searched and the search strategy the authors used.Selection criteria-- the researchers should describe how they decided which articles to include
• A critical appraisal or evaluation of the quality of the articles included (most frequently included in systematic reviews and meta-analysis)
• Discussion, results, and conclusions

Determining Primary versus Secondary Using the Database Abstract

Information found in PubMed, CINAHL, Scopus, and other databases can help you determine whether the article you're looking at is primary or secondary.

Primary research article abstract

• Note that in the "Objectives" field, the authors describe their single, individual study.
• In the materials and methods section, they describe the number of patients included in the study and how those patients were divided into groups.
• These are all clues that help us determine this abstract is describing is a single, primary research article, as opposed to a literature review.
• Primary Article Abstract

Secondary research/review article abstract

• Note that the words "systematic review" and "meta-analysis" appear in the title of the article
• The objectives field also includes the term "meta-analysis" (a common type of literature review in the health sciences)
• The "Data Source" section includes a list of databases searched
• The "Study Selection" section describes the selection criteria
• These are all clues that help us determine that this abstract is describing a review article, as opposed to a single, primary research article.
• Secondary Research Article

• Primary vs. Secondary Worksheet

Full Text Challenge

Can you determine if the following articles are primary or secondary?

• Last Updated: Feb 17, 2024 5:25 PM
• URL: https://library.usfca.edu/primary-secondary

2130 Fulton Street San Francisco, CA 94117-1080 415-422-5555

• Facebook (link is external)
• Instagram (link is external)
• Twitter (link is external)
• YouTube (link is external)
• Consumer Information
• Privacy Statement
• Web Accessibility

Copyright © 2022 University of San Francisco

Main Navigation Menu

Peer-review and primary research.

• Getting Started With Peer-Reviewed Literature

Primary Research

Identifying a primary research article.

• Finding Peer-Reviewed Journal Articles
• Finding Randomized Controlled Trials (RCTs)
• Evaluating Scholarly Articles
• Google Scholar
• Tips for Reading Journal Articles

STEM Librarian

Primary research or a primary study refers to a research article that is an author’s original research that is almost always published in a peer-reviewed journal. A primary study reports on the details, methods and results of a research study. These articles often have a standard structure of a format called IMRAD, referring to sections of an article: Introduction, Methods, Results and Discussion. Primary research studies will start with a review of the previous literature, however, the rest of the article will focus on the authors’ original research. Literature reviews can be published in peer-reviewed journals, however, they are not primary research.

Primary studies are part of primary sources but should not be mistaken for primary documents. Primary documents are usually original sources such as a letter, a diary, a speech or an autobiography. They are a first person view of an event or a period. Typically, if you are a Humanities major, you will be asked to find primary documents for your paper however, if you are in Social Sciences or the Sciences you are most likely going to be asked to find primary research studies. If you are unsure, ask your professor or a librarian for help.

A primary research or study is an empirical research that is published in peer-reviewed journals. Some ways of recognizing whether an article is a primary research article when searching a database:

1. The abstract includes a research question or a hypothesis,  methods and results.

2. Studies can have tables and charts representing data findings.

3. The article includes a section for "methods” or “methodology” and "results".

4. Discussion section indicates findings and discusses limitations of the research study, and suggests further research.

5. Check the reference section because it will refer you to the studies and works that were consulted. You can use this section to find other studies on that particular topic.

The following are not to be confused with primary research articles:

- Literature reviews

- Meta-analyses or systematic reviews (these studies make conclusions based on research on many other studies)

• << Previous: Getting Started With Peer-Reviewed Literature
• Next: Finding Peer-Reviewed Journal Articles >>
• Last Updated: Feb 15, 2024 2:45 PM
• URL: https://guides.library.ucmo.edu/peerreview

• SUNY Oswego, Penfield Library
• Resource Guides

Biological Sciences Research Guide

Primary research vs review article.

• Research Starters
• Citing Sources
• Open Educational Resources
• Peer Review
• How to Read a Scientific Article
• Conducting a Literature Review
• Interlibrary Loan

Quick Links

• Penfield Library
• Research Guides
• A-Z List of Databases & Indexes

Characteristics of a Primary Research Article

• Goal is to present the result of original research that makes a new contribution to the body of knowledge
• Sometimes referred to as an empirical research article
• Typically organized into sections that include:  Abstract, Introduction, Methods, Results, Discussion/Conclusion, and References.

Example of a Primary Research Article:

Flockhart, D.T.T., Fitz-gerald, B., Brower, L.P., Derbyshire, R., Altizer, S., Hobson, K.A., … Norris, D.R., (2017). Migration distance as a selective episode for wing morphology in a migratory insect. Movement Ecology , 5(1), 1-9. doi: doi.org/10.1186/s40462-017-0098-9

Characteristics of a Review Article

• Goal is to summarize important research on a particular topic and to represent the current body of knowledge about that topic.
• Not intended to provide original research but to help draw connections between research studies that have previously been published.  
• Help the reader understand how current understanding of a topic has developed over time and identify gaps or inconsistencies that need further exploration.

Example of a Review Article:

https://www-sciencedirect-com.ezproxy.oswego.edu/science/article/pii/S0960982218302537

• << Previous: Plagiarism
• Next: Peer Review >>

• University of Northern Colorado Libraries

Q. How do I know if an article is a primary or secondary research article?

• 10 Archival Services
• 29 Articles
• 11 Bibliography
• 45 Borrowing
• 11 Campus Services
• 15 Campus Technology
• 16 Computing
• 5 Copy & Fax
• 3 Course Readings
• 8 Databases
• 10 Distance Learning/Extended Studies
• 1 Employment
• 1 Facilities reservations
• 8 Faculty Services
• 36 General services
• 10 Interlibrary Loan
• 8 Library Instruction
• 21 Library Policies
• 9 Media Materials
• 16 Online services
• 10 Prospector
• 26 Research
• 8 UNC History

Answered By: Jay Trask Last Updated: Oct 21, 2020     Views: 236871

A primary research article reports on an empirical research study conducted by the authors. It is almost always published in a peer-reviewed journal. This type of article:

• Asks a research question or states a hypothesis or hypotheses
• Identifies a research population
• Describes a specific research method
• Tests or measures something
• Includes a section called "method" or "methodology." This may only appear in the article, not the abstract.
• Includes a section called "results."

Words to look for as clues include: analysis, study, investigation, examination, experiment, numbers of people or objects analyzed, content analysis, or surveys.

To contrast, the following are not primary research articles (i.e., they are secondary sources):

• Literature reviews
• Meta-Analyses/Review articles (These are studies that arrive at conclusions based on research from many other studies.)
• Chapters in books
• Encyclopedia articles
• Speeches and interviews

Please note: if you are seeking information about primary and secondary sources for historical research, please find information here: https://libguides.unco.edu/history-primary-resources

• Share on Facebook

Was this helpful? Yes 333 No 137

Comments (0)

Related topics.

• Library Instruction

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Methodology
• Primary Research | Definition, Types, & Examples

Primary Research | Definition, Types, & Examples

Published on 15 January 2023 by Tegan George .

Primary research is a research method that relies on direct data collection , rather than relying on data that’s already been collected by someone else. In other words, primary research is any type of research that you undertake yourself, firsthand, while using data that has already been collected is called secondary research.

Primary research is often used in qualitative research , particularly in survey methodology, questionnaires, focus groups, and various types of interviews . While quantitative primary research does exist, it’s not as common.

Table of contents

When to use primary research, types of primary research, examples of primary research, advantages and disadvantages of primary research, frequently asked questions.

Primary research is any research that you conduct yourself. It can be as simple as a 2-question survey, or as in-depth as a years-long longitudinal study . The only key is that data must be collected firsthand by you.

Primary research is often used to supplement or strengthen existing secondary research. It is usually exploratory in nature, concerned with examining a research question where no preexisting knowledge exists. It is also sometimes called original research for this reason.

Prevent plagiarism, run a free check.

Primary research can take many forms, but the most common types are:

• Surveys and questionnaire
• Observational studies
• Interviews and focus groups
• Surveys and questionnaires

Surveys and questionnaires collect information about a group of people by asking them questions and analyzing the results. They are a solid choice if your research topic seeks to investigate something about the characteristics, preferences, opinions, or beliefs of a group of people.

Surveys and questionnaires can take place online, in person, or through the mail. It is best to have a combination of open-ended and closed-ended questions, and how the questions are phrased matters. Be sure to avoid leading questions, and ask any related questions in groups, starting with the most basic ones first.

Observational studies are an easy and popular way to answer a research question based purely on what you, the researcher, observes. If there are practical or ethical concerns that prevent you from conducting a traditional experiment , observational studies are often a good stopgap.

There are three types of observational studies: cross-sectional studies , cohort studies, and case-control studies. If you decide to conduct observational research, you can choose the one that’s best for you. All three are quite straightforward and easy to design – just beware of confounding variables and observer bias creeping into your analysis.

Similarly to surveys and questionnaires, interviews and focus groups also rely on asking questions to collect information about a group of people. However, how this is done is slightly different. Instead of sending your questions out into the world, interviews and focus groups involve two or more people – one of whom is you, the interviewer, who asks the questions.

There are 3 main types of interviews:

• Structured interviews ask predetermined questions in a predetermined order.
• Unstructured interviews are more flexible and free-flowing, proceeding based on the interviewee’s previous answers.
• Semi-structured interviews fall in between, asking a mix of predetermined questions and off-the-cuff questions.

While interviews are a rich source of information, they can also be deceptively challenging to do well. Be careful of interviewer bias creeping into your process. This is best mitigated by avoiding double-barreled questions and paying close attention to your tone and delivery while asking questions.

Alternatively, a focus group is a group interview, led by a moderator. Focus groups can provide more nuanced interactions than individual interviews, but their small sample size means that external validity is low.

Primary research can often be quite simple to pursue yourself. Here are a few examples of different research methods you can use to explore different topics.

Primary research is a great choice for many research projects, but it has distinct advantages and disadvantages.

Advantages of primary research

Advantages include:

• The ability to conduct really tailored, thorough research, down to the ‘nitty-gritty’ of your topic . You decide what you want to study or observe and how to go about doing that.
• You maintain control over the quality of the data collected, and can ensure firsthand that it is objective, reliable , and valid .
• The ensuing results are yours, for you to disseminate as you see fit. You maintain proprietary control over what you find out, allowing you to share your findings with like-minded individuals or those conducting related research that interests you for replication or discussion purposes.

Disadvantages of primary research

Disadvantages include:

• In order to be done well, primary research can be very expensive and time consuming. If you are constrained in terms of time or funding, it can be very difficult to conduct your own high-quality primary research.
• Primary research is often insufficient as a standalone research method, requiring secondary research to bolster it.
• Primary research can be prone to various types of research bias . Bias can manifest on the part of the researcher as observer bias , Pygmalion effect , or demand characteristics . It can occur on the part of participants as a Hawthorne effect or social desirability bias .

The 3 main types of primary research are:

Exploratory research explores the main aspects of a new or barely researched question.

Explanatory research explains the causes and effects of an already widely researched question.

There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control, and randomisation.

In restriction , you restrict your sample by only including certain subjects that have the same values of potential confounding variables.

In matching , you match each of the subjects in your treatment group with a counterpart in the comparison group. The matched subjects have the same values on any potential confounding variables, and only differ in the independent variable .

In statistical control , you include potential confounders as variables in your regression .

In randomisation , you randomly assign the treatment (or independent variable) in your study to a sufficiently large number of subjects, which allows you to control for all potential confounding variables.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analysing data from people using questionnaires.

When conducting research, collecting original data has significant advantages:

• You can tailor data collection to your specific research aims (e.g., understanding the needs of your consumers or user testing your website).
• You can control and standardise the process for high reliability and validity (e.g., choosing appropriate measurements and sampling methods ).

However, there are also some drawbacks: data collection can be time-consuming, labour-intensive, and expensive. In some cases, it’s more efficient to use secondary data that has already been collected by someone else, but the data might be less reliable.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

George, T. (2023, January 15). Primary Research | Definition, Types, & Examples. Scribbr. Retrieved 2 April 2024, from https://www.scribbr.co.uk/research-methods/primary-research-explained/

Is this article helpful?

Tegan George

Other students also liked, data collection methods | step-by-step guide & examples, observer bias | definition, examples, prevention, what is qualitative research | methods & examples.

Understanding research and critical appraisal

• Introduction
• Secondary research

What is primary research?

Quantitative research study designs, qualitative research study designs, mixed methods research study designs.

• Critical appraisal of research papers
• Useful terminology
• Further reading and helpful resources

Primary research articles provide a report of individual, original research studies, which constitute the majority of articles published in peer-reviewed journals. All primary research studies are conducted according to a specified methodology, which will be partly determined by the aims and objectives of the research.

The following sections offer brief summaries of some of the common quantitative, qualitative, and mixed-methods study designs you may encounter. 

Randomised Controlled Trial

A randomised controlled trial (RCT) is a study where participants are randomly allocated to two or more groups. One group receives the treatment that is being tested by the study (treatment or experimental group), and the other group(s) receive an alternative, which is often the current standard treatment or a placebo (control or comparison group). The nature of the control used should always be specified.

An RCT is a good study choice for determining the effectiveness of an intervention or treatment, or for comparing the relative effectiveness of different interventions or treatments. If well implemented, the randomisation of participants in RCTs should ensure that the groups differ only in their exposure to treatment, and that differences in outcomes between the groups are probably attributable to the treatment being studied.

In crossover randomised controlled trials, participants receive all of the treatments and controls being tested in a random order. This means that participants receive one treatment, the effect of which is measured, and then "cross over" into the other treatment group, where the effect of the second treatment (or control) is measured.

RCTs are generally considered to be the most rigorous experimental study design, as the randomisation of participants helps to minimise confounding and other sources of bias.

Cohort study

A cohort study identifies a group of people and follows them over a period of time to see who develops the outcome of interest to the study. This type of study is normally used to look at the effect of suspected risk factors that cannot be controlled experimentally – for example, the effect of smoking on lung cancer.

Also sometimes called longitudinal studies, cohort studies can be either prospective, that is, exposure factors are identified at the beginning of a study and the study population is followed into the future, or retrospective, that is, medical records for the study population are used to identify past exposure factors.

Cohort studies are useful in answering questions about disease causation or progression, or studying the effects of harmful exposures.

Cohort studies are generally considered to be the most reliable observational study design. They are not as reliable as RCTs, as the study groups may differ in ways other than the variable being studied.

Other problems with cohort studies are that they require a large sample size, are inefficient for rare outcomes, and can take long periods of time.

Case-Control Study

A case-control study compares a group of people with a disease or condition, against a control population without the disease or condition, in order to investigate the causes of particular outcomes. The study looks back at the two groups over time to see which risk factors for the disease or condition they have been exposed to.

Case-control studies can be useful in identifying which risk factors may predict a disease, or how a disease progresses over time. They can be especially useful for investigating the causes of rare outcomes.

Case-control studies can be done quickly, and do not require large groups of subjects. However, their reliance on retrospective data which may be incomplete or unreliable (owing to subject ability to accurately recall information such as the appearance of a symptom) can be a difficulty.

Cross-Sectional Study

A cross-sectional study collects data from the study population at one point in time, and considers the relationships between characteristics. Also  sometimes called surveys or prevalence studies.

Cross-sectional studies are generally used to study the prevalence of a risk factor, disease or outcome in a chosen population.

Because cross-sectional studies do not look at trends or changes over time, they cannot establish cause and effect between exposures and outcomes.

Case Series / Case Reports

A case series is a descriptive study of a group of people, who have either received the same treatment or have the same disease, in order to identify characteristics or outcomes in a particular group of people.

Case series are useful for studying rare diseases or adverse outcomes, for illustrating particular aspects of a condition, identifying treatment approaches, and for generating hypotheses for further study.

A case report provides a study of an individual, rather than a group.

Case series and case reports have no comparative control groups, and are prone to bias and chance association.

Expert opinion

Expert opinion draws upon the clinical experience and recommendations of those with established expertise on a topic.

Grounded theory

Grounded theory studies aim to generate theory in order to explain social processes, interactions or issues. This explanatory theory is grounded in, and generated from, the research participant data collected.

Research data typically takes the form of interviews, observations or documents. Data is analysed as it is collected, and is coded and organised into categories which inform the further collection of data, and the construction of theory. This cycle helps to refine the theory, which evolves as more data is gathered.

Phenomenology

A phenomenological study aims to describe the meaning(s) of the lived experience of a phenomenon. Research participants will have some common experience of the phenomenon under examination, but will differ in their precise individual experience, and in other personal or social characteristics.

Research data is typically in the form of observations, interviews or written records, and its analysis sets out to identify common themes in the participants' experience, while also highlighting variations and unique themes.

Ethnography

Ethnography is the study of a specific culture or cultural group, where the researcher seeks an insider perspective by placing themselves as a participant observer within the group under study.

Data is typically formed of observations, interviews and conversation. Ethnography aims to offer direct insight into the lives and the experiences of the group or the culture under study, examining its beliefs, values, practices and behaviours.

A case study offers a detailed description of the experience of an individual, a family, a community or an organisation, often with the aim of highlighting a particular issue. Research data may include documents, interviews and observations.

Content analysis

Content analysis is used to explore the occurrence, meanings and relationships of words, themes or concepts within a set of textual data. Research data might be drawn from any type of written document(s). Data is coded and categorised, with the aim of revealing and examining the patterns and the intentions of language use within the data set.

Narrative inquiry

A narrative inquiry offers in depth detail of a situation or experience from the perspective of an individual or small groups. Research data usually consists of interviews or recordings, which is presented as a structured, chronological narrative. Narrative inquiry studies often seek to give voice to individuals or populations whose perspective is less well established, or not commonly sought.

Action research

Action research is a form of research, commonly used with groups, where the participants take a more active, collaborative role in producing the research. Studies incorporate the lived experiences of the individuals, groups or communities under study, drawing on data which might include observation, interviews, questionnaires or workshops.

Action research is generally aimed at changing or improving a particular context, or a specific practice, alongside the generation of theory.

Explanatory sequential design

In an explanatory sequential study, emphasis is given to the collection and analysis of quantitative data, which occurs during the first phase of the study. The results of this quantitative phase inform the subsequent collection of qualitative data in the next phase.

Analysis of the resultant qualitative data is then used to 'explain' the quantitative results, usually serving to contextualise these, or to otherwise enhance or enrich the initial findings.

Exploratory sequential design

In an exploratory sequential study, the opposite sequence to that outlined above is used. In this case, qualitative data is emphasised, with this being collected and analysed during the first phase of the study. The results of this qualitative phase inform the subsequent collection of quantitative data in the next phase.

The quantitative data can then be used to define or to generalise the qualitative results, or to test these results on the basis of theory emerging from the initial findings.

Convergent design

In a convergent study, qualitative and quantitative data sets are collected and analysed simultaneously and independently of one another.

Results from analysis of both sets of data are brought together to provide one overall interpretation; this combination of data types can be handled in various ways, but the objective is always to provide a fuller understanding of the phenomena under study. Equal emphasis is given to both qualitative and quantitative data in a convergent study.

• << Previous: Secondary research
• Next: Critical appraisal of research papers >>
• Last Updated: Mar 26, 2024 4:38 PM
• URL: https://libguides.sgul.ac.uk/researchdesign

Animal Science

How to identify peer reviewed journals, how to identify primary research articles.

• Reference Sources
• Key Journals
• Writing & Citing
• Self Checkout
• Anatomy Study Resources
• Peer Reviewed Journals Quiz How do I know if a journal is peer reviewed? What is peer review, anyway? Take this short quiz to test your knowledge and perhaps learn something new!
• Primary Research Articles Quiz How do I know if an article is a primary or secondary research article? Are there search techniques that will help me find them? Take this short quiz to test your knowledge and perhaps learn something new!

You must get all answers correct to submit the quiz!

Peer review is defined as “a process of subjecting an author’s scholarly work, research or ideas to the scrutiny of others who are experts in the same field” ( 1 ). Peer review is intended to serve two purposes:

• It acts as a filter to ensure that only high quality research is published, especially in reputable journals, by determining the validity, significance and originality of the study.
• Peer review is intended to improve the quality of manuscripts that are deemed suitable for publication. Peer reviewers provide suggestions to authors on how to improve the quality of their manuscripts, and also identify any errors that need correcting before publication.

How do you determine whether an article qualifies as being a peer-reviewed journal article?

• If you're searching for articles in certain databases, you can limit your search to peer-reviewed sources simply by selecting a tab or checking a box on the search screen.
• If you have an article, an indication that it has been through the peer review process will be the publication history , usually at the beginning or end of the article.
• If you're looking at the journal itself, go to the  editorial statement or instructions to authors  (usually in the first few pages of the journal or at the end) for references to the peer-review process.
• Lookup the journal by title or ISSN in the ProQuest Source Evaluation Aid . 
• Careful! Not all information in a peer-reviewed journal is actually reviewed. Editorials, letters to the editor, book reviews, and other types of information don't count as articles, and may not be accepted by your professor.

What about preprint sites and ResearchGate?

• A preprint is a piece of research that has not yet been peer reviewed and published in a journal. In most cases, they can be considered final drafts or working papers. Preprint sites are great sources of current research - and most preprint sites will provide a link to a later, peer-reviewed version of an article. 
• ResearchGate is a commercial social networking site for scientists and researchers to share papers, ask and answer questions, and find collaborators. Members can upload research output including papers, chapters, negative results, patents, research proposals, methods, presentations, etc. Researchers can access these materials, and also contact members to ask for access to material that has not been shared, usually because of copyright restrictions. There is a filter to limit results to articles, but it can be difficult to determine the publication history of ResearchGate items and whether they have been published in peer reviewed sources.

A primary research article reports on an empirical research study conducted by the authors. The goal of a primary research article is to present the result of original research that makes a new contribution to the body of knowledge. 

Characteristics:

• Almost always published in a peer-reviewed journal
• Asks a research question or states a hypothesis or hypotheses
• Identifies a research population
• Describes a specific research method
• Tests or measures something
• Often (but not always) structured in a standard format called IMRAD: Introduction, Methods, Results, and Discussion
• Words to look for as clues include: analysis, study, investigation, examination, experiment, numbers of people or objects analyzed, content analysis, or surveys.

To contrast, the following are not primary research articles (i.e., they are secondary sources):

• Literature reviews/Review articles
• Meta-Analyses (studies that arrive at conclusions based on research from many other studies)
• Editorials & Letters
• Dissertations

Articles that are NOT primary research articles may discuss the same research, but they are not reporting on original research, they are summarizing and commenting on research conducted and published by someone else. For example, a literature review provides commentary and analysis of research done by other people, but it does not report the results of the author's own study and is not primary research.

• << Previous: Home
• Next: Reference Sources >>
• Last Updated: Aug 24, 2023 2:38 PM
• URL: https://libguides.berry.edu/ans

• Skip to main content
• Skip to primary sidebar
• Skip to footer
• QuestionPro

• Solutions Industries Gaming Automotive Sports and events Education Government Travel & Hospitality Financial Services Healthcare Cannabis Technology Use Case NPS+ Communities Audience Contactless surveys Mobile LivePolls Member Experience GDPR Positive People Science 360 Feedback Surveys
• Resources Blog eBooks Survey Templates Case Studies Training Help center

Home Market Research

Primary Research: What It Is, Purpose & Methods + Examples

As we continue exploring the exciting research world, we’ll come across two primary and secondary data approaches. This article will focus on primary research – what it is, how it’s done, and why it’s essential. 

We’ll discuss the methods used to gather first-hand data and examples of how it’s applied in various fields. Get ready to discover how this research can be used to solve research problems , answer questions, and drive innovation.

What is Primary Research: Definition

Primary research is a methodology researchers use to collect data directly rather than depending on data collected from previously done research. Technically, they “own” the data. Primary research is solely carried out to address a certain problem, which requires in-depth analysis .

There are two forms of research:

• Primary Research
• Secondary Research

Businesses or organizations can conduct primary research or employ a third party to conduct research. One major advantage of primary research is this type of research is “pinpointed.” Research only focuses on a specific issue or problem and on obtaining related solutions.

For example, a brand is about to launch a new mobile phone model and wants to research the looks and features they will soon introduce. 

Organizations can select a qualified sample of respondents closely resembling the population and conduct primary research with them to know their opinions. Based on this research, the brand can now think of probable solutions to make necessary changes in the looks and features of the mobile phone.

Primary Research Methods with Examples

In this technology-driven world, meaningful data is more valuable than gold. Organizations or businesses need highly validated data to make informed decisions. This is the very reason why many companies are proactive in gathering their own data so that the authenticity of data is maintained and they get first-hand data without any alterations.

Here are some of the primary research methods organizations or businesses use to collect data:

1. Interviews (telephonic or face-to-face)

Conducting interviews is a qualitative research method to collect data and has been a popular method for ages. These interviews can be conducted in person (face-to-face) or over the telephone. Interviews are an open-ended method that involves dialogues or interaction between the interviewer (researcher) and the interviewee (respondent).

Conducting a face-to-face interview method is said to generate a better response from respondents as it is a more personal approach. However, the success of face-to-face interviews depends heavily on the researcher’s ability to ask questions and his/her experience related to conducting such interviews in the past. The types of questions that are used in this type of research are mostly open-ended questions . These questions help to gain in-depth insights into the opinions and perceptions of respondents.

Personal interviews usually last up to 30 minutes or even longer, depending on the subject of research. If a researcher is running short of time conducting telephonic interviews can also be helpful to collect data.

2. Online surveys

Once conducted with pen and paper, surveys have come a long way since then. Today, most researchers use online surveys to send to respondents to gather information from them. Online surveys are convenient and can be sent by email or can be filled out online. These can be accessed on handheld devices like smartphones, tablets, iPads, and similar devices.

Once a survey is deployed, a certain amount of stipulated time is given to respondents to answer survey questions and send them back to the researcher. In order to get maximum information from respondents, surveys should have a good mix of open-ended questions and close-ended questions . The survey should not be lengthy. Respondents lose interest and tend to leave it half-done.

It is a good practice to reward respondents for successfully filling out surveys for their time and efforts and valuable information. Most organizations or businesses usually give away gift cards from reputed brands that respondents can redeem later.

3. Focus groups

This popular research technique is used to collect data from a small group of people, usually restricted to 6-10. Focus group brings together people who are experts in the subject matter for which research is being conducted.

Focus group has a moderator who stimulates discussions among the members to get greater insights. Organizations and businesses can make use of this method, especially to identify niche markets to learn about a specific group of consumers.

4. Observations

In this primary research method, there is no direct interaction between the researcher and the person/consumer being observed. The researcher observes the reactions of a subject and makes notes.

Trained observers or cameras are used to record reactions. Observations are noted in a predetermined situation. For example, a bakery brand wants to know how people react to its new biscuits, observes notes on consumers’ first reactions, and evaluates collective data to draw inferences .

Primary Research vs Secondary Research – The Differences

Primary and secondary research are two distinct approaches to gathering information, each with its own characteristics and advantages. 

While primary research involves conducting surveys to gather firsthand data from potential customers, secondary market research is utilized to analyze existing industry reports and competitor data, providing valuable context and benchmarks for the survey findings.

Find out more details about the differences: 

1. Definition

• Primary Research: Involves the direct collection of original data specifically for the research project at hand. Examples include surveys, interviews, observations, and experiments.
• Secondary Research: Involves analyzing and interpreting existing data, literature, or information. This can include sources like books, articles, databases, and reports.

2. Data Source

• Primary Research: Data is collected directly from individuals, experiments, or observations.
• Secondary Research: Data is gathered from already existing sources.

3. Time and Cost

• Primary Research: Often time-consuming and can be costly due to the need for designing and implementing research instruments and collecting new data.
• Secondary Research: Generally more time and cost-effective, as it relies on readily available data.

4. Customization

• Primary Research: Provides tailored and specific information, allowing researchers to address unique research questions.
• Secondary Research: Offers information that is pre-existing and may not be as customized to the specific needs of the researcher.
• Primary Research: Researchers have control over the research process, including study design, data collection methods, and participant selection.
• Secondary Research: Limited control, as researchers rely on data collected by others.

6. Originality

• Primary Research: Generates original data that hasn’t been analyzed before.
• Secondary Research: Involves the analysis of data that has been previously collected and analyzed.

7. Relevance and Timeliness

• Primary Research: Often provides more up-to-date and relevant data or information.
• Secondary Research: This may involve data that is outdated, but it can still be valuable for historical context or broad trends.

Advantages of Primary Research

Primary research has several advantages over other research methods, making it an indispensable tool for anyone seeking to understand their target market, improve their products or services, and stay ahead of the competition. So let’s dive in and explore the many benefits of primary research.

• One of the most important advantages is data collected is first-hand and accurate. In other words, there is no dilution of data. Also, this research method can be customized to suit organizations’ or businesses’ personal requirements and needs .
• I t focuses mainly on the problem at hand, which means entire attention is directed to finding probable solutions to a pinpointed subject matter. Primary research allows researchers to go in-depth about a matter and study all foreseeable options.
• Data collected can be controlled. I T gives a means to control how data is collected and used. It’s up to the discretion of businesses or organizations who are collecting data how to best make use of data to get meaningful research insights.
• I t is a time-tested method, therefore, one can rely on the results that are obtained from conducting this type of research.

Disadvantages of Primary Research

While primary research is a powerful tool for gathering unique and firsthand data, it also has its limitations. As we explore the drawbacks, we’ll gain a deeper understanding of when primary research may not be the best option and how to work around its challenges.

• One of the major disadvantages of primary research is it can be quite expensive to conduct. One may be required to spend a huge sum of money depending on the setup or primary research method used. Not all businesses or organizations may be able to spend a considerable amount of money.
• This type of research can be time-consuming. Conducting interviews and sending and receiving online surveys can be quite an exhaustive process and require investing time and patience for the process to work. Moreover, evaluating results and applying the findings to improve a product or service will need additional time.
• Sometimes, just using one primary research method may not be enough. In such cases, the use of more than one method is required, and this might increase both the time required to conduct research and the cost associated with it.

Every research is conducted with a purpose. Primary research is conducted by organizations or businesses to stay informed of the ever-changing market conditions and consumer perception. Excellent customer satisfaction (CSAT) has become a key goal and objective of many organizations.

A customer-centric organization knows the importance of providing exceptional products and services to its customers to increase customer loyalty and decrease customer churn. Organizations collect data and analyze it by conducting primary research to draw highly evaluated results and conclusions. Using this information, organizations are able to make informed decisions based on real data-oriented insights.

QuestionPro is a comprehensive survey platform that can be used to conduct primary research. Users can create custom surveys and distribute them to their target audience , whether it be through email, social media, or a website.

QuestionPro also offers advanced features such as skip logic, branching, and data analysis tools, making collecting and analyzing data easier. With QuestionPro, you can gather valuable insights and make informed decisions based on the results of your primary research. Start today for free!

LEARN MORE         FREE TRIAL

MORE LIKE THIS

AI Question Generator: Create Easy + Accurate Tests and Surveys

Apr 6, 2024

Top 17 UX Research Software for UX Design in 2024

Apr 5, 2024

Healthcare Staff Burnout: What it Is + How To Manage It

Apr 4, 2024

Top 15 Employee Retention Software in 2024

Other categories.

• Academic Research
• Artificial Intelligence
• Assessments
• Brand Awareness
• Case Studies
• Communities
• Consumer Insights
• Customer effort score
• Customer Engagement
• Customer Experience
• Customer Loyalty
• Customer Research
• Customer Satisfaction
• Employee Benefits
• Employee Engagement
• Employee Retention
• Friday Five
• General Data Protection Regulation
• Insights Hub
• Life@QuestionPro
• Market Research
• Mobile diaries
• Mobile Surveys
• New Features
• Online Communities
• Question Types
• Questionnaire
• QuestionPro Products
• Release Notes
• Research Tools and Apps
• Revenue at Risk
• Survey Templates
• Training Tips
• Uncategorized
• Video Learning Series
• What’s Coming Up
• Workforce Intelligence

Tutorial: Evaluating Information: Primary vs. Secondary Articles

• Evaluating Information
• Scholarly Literature Types
• Primary vs. Secondary Articles
• Peer Review
• Systematic Reviews & Meta-Analysis
• Gray Literature
• Evaluating Like a Boss
• Evaluating AV

Primary vs. Secondary Research Articles

In the sciences,  primary (or empirical) research articles :

• are original scientific reports of new research findings (Please note that an original scientific article does not include review articles, which summarize the research literature on a particular subject, or articles using meta-analyses, which analyze pre-published data.)
• usually include the following sections: Introduction , Methods , Results , Discussion, References
• are usually  peer-reviewed (examined by expert(s) in the field before publication). Please note that a peer-reviewed article is not the same as a review article, which summarizes the research literature on a particular subject

You may also choose to use some secondary sources (summaries or interpretations of original research) such as books (find these through the library catalog) or review articles (articles which organize and critically analyze the research of others on a topic). These secondary sources, particularly review articles, are often useful and easier-to-read summaries of research in an area. Additionally, you can use the listed references to find useful primary research articles.

Anatomy of a Scholarly Article

from NCSU Libraries' Anatomy of a Scholarly Article

Types of health studies

In the sciences, particularly the health sciences, there are a number of types of primary articles (the gold standard being randomized controlled trials ) and secondary articles (the gold standard being systematic reviews and meta-analysis ). The chart below summarizes their differences and the linked article gives more information.

Searching for Primary vs. Secondary Articles

Some scholarly databases will allow you to specific what kind of scholarly literature you're looking for.  However, be careful! Sometimes, depending on the database, the Review article type may mean book review instead of or as well as review article. You may also have to look under more or custom options to find these choices.

• << Previous: Scholarly Literature Types
• Next: Peer Review >>
• Last Updated: Oct 20, 2021 11:11 AM
• URL: https://guides.library.cornell.edu/evaluate

KPU Library

• Borrowing from the Library
• Returning Library Items
• Borrowing From Other Academic Institutions
• Equipment & Media Services
• Student Laptop Loans
• Course Reserves
• Interlibrary Loans
• Requesting KPU Material
• Academic Integrity & Plagiarism
• Citation Style Guides
• Subject Guides
• Research Help Guide
• Collections
• Scholarly Publications
• Video Tutorials
• χʷəχʷéy̓əm and Indigenization
• Data Services
• Link.Scan.Open.
• Library Instruction
• Library Services to support Teaching & Learning
• Library Tutorials & Activities
• Research, Scholarship & Publishing at KPU
• Teaching Online
• Open Publishing Suite
• Study Rooms & Bookings
• Our Facilities
• Printing, Photocopy, Scan
• Computers & Wifi
• Library Accessibility Services
• My Library Account & Passwords
• Welcome to KPU Library
• About the Library
• Contact Your Librarian
• Hours & Locations
• KPU Library News Blog
• Library Directory

CRIM 1208: Research Methods

• About this guide
• Developing a research question
• What are scholarly articles?
• What are primary research articles?
• Finding articles in databases
• Where to find government statistics? This link opens in a new window
• Literature reviews
• Citation mapping
• Citing in APA style
• Go to main CRIM library guide

Which of these is an ORIGINAL (PRIMARY) research article?

What are original (primary) research articles.

• Primary & secondary research

Structure of a primary research article

Primary and secondary research articles.

Once researchers complete a project, they will usually (try to) publish their findings in a peer-reviewed journal. These are often called PRIMARY or ORIGINAL research articles because they are the first-publication of new research findings and are written by the researchers themselves. They may also be called EMPIRICAL articles.

Secondary sources of information describe, explain, interpret or summarize primary sources. These include encyclopedias, book reviews, commentaries, literature reviews, and any books or journal articles that simply discuss the original (previously-published) work of others . Although these can be very helpful sources for identifying primary research articles, they are not primary studies themselves.

VIDEO: What is Original (Primary) Research in Criminology? (19:38)

Describes the typical structure of an original research article, with a particular focus on the Methods section. It shows examples of several types of original research articles (qualitative and quantitative, including articles using secondary data, and meta-analyses), as well as several types of secondary articles (book reviews, editorial essays, theoretical analyses and literature reviews). The emphasis is on learning to read the abstract for indications of original research, and checking for a Methods section in the article. Part 1 of the Finding Original Research Articles in Criminology video series.

• Video (Kaltura)
• Video transcript (text file)

• VIDEO: What is Empirical Research? (2:59)
• Finding Peer-Reviewed, Primary Research Articles in Criminology 4-page KPU Library guide.

A primary (original) research article will usually be divided into several labeled sections. The screenshot above is from the video " What is Original (Primary) Research in Criminology? ". You can jump to the 3:10 timestamp to watch the " Sections of an original research article " segment of the video.

• Introduction (which usually includes a literature review)
• Method (often called Methodology or Methods) -- always found in an empirical research article
• Findings or Results
• Conclusions

The names of the parts may vary, but a primary research article will always include a methodology section explaining how the research was conducted (i.e. what type of empirical method was used). Most secondary journal articles do not include a methods section.

• << Previous: What are scholarly articles?
• Next: Finding articles in databases >>
• Last Updated: Mar 20, 2024 11:32 AM
• URL: https://libguides.kpu.ca/crim/1208

• William & Mary Libraries
• Research Guides
• Using the Library

Science Writing

• Primary Research Articles
• Review Articles
• Citing in the Sciences

What is a primary research article? 

If you're writing an empirical article (also known as a primary research article) then you're doing original, typically experimental, research -- you are creating new knowledge and will have original findings. These primary research articles will always have a methodology section where you describe how you conducted your study. It will typically be structured like this: 

• Introduction

Methodology

How to Write a Primary Research Article

The introduction will include: 

• A review of the literature (background on your topic & what other research has been done)
• The question this study will be answering, and why it's important
• Your approach to answering the question, and your hypothesis

Things to avoid: 

• Excessive length
• Leaving out the justification for the study

The methods section is where you detail the materials and experimental approaches that you used in your study. It should be detailed, particularly if the method you're using is novel. A general guideline is that you want to include enough detail so that other researchers could replicate your experiment. When writing it, you should arrange everything chronologically and can use subsections where appropriate. 

• Switching tenses (it should be in past tense)
• Insufficient detail
• Omitting the purpose of the experiment

The results section will include data and your interpretation of the data (but it won't tie it in to the overall literature or bigger implications -- that's what the discussion section is for). You should include your main findings, any other important findings, and your control results. Most data should be in figures or tables, with the text being used to summarize and explain the data. The results section should be organized in a logical way -- for instance, from most important to least important findings. 

Things to Avoid: 

• Inexact language ("significance" means something very particular in science)
• Including irrelevant data 
• Excessive detail (don't include results from anything not discussed in the methods section)

The discussion section will answer your research question by stating and interpreting your findings, including their relevance, meaning, and context. You should tie in elements from your earlier literature review to explain what is new and impactful about your work. The discussion section is also where you can talk about possible limitations of your study and suggest future work that can be done. It should be organized in a way that moves from specific to broad, introducing your particular findings first and then moving to a more general perspective. 

• Restating your results section
• Making conclusions outside of the scope of your findings 
• Criticizing other studies

The conclusion may be the last paragraph of the discussion section, or it can be pulled out into its own section. Either way it should be about a paragraph in length and should recap the most important results and significance of your findings. 

• Introducing large ideas not already covered in the paper 
• Excessive length -- conclusion should be brief 

Examples of Primary Research Articles

• Experimental Exposure to Urban and Pink Noise Affects Brain Development and Song Learning in Zebra Finches
• Effect of an Enteric-Coated Fish Oil Preparation on Relapses in Crohn's Disease
• The Effect of Intrinsic Crumpling on the Mechanics of Free-Standing Graphene

Instruction & Research Librarian

• << Previous: Review Articles
• Next: Citing in the Sciences >>

Primary Sources

• Primary vs Secondary
• History Resources

Identifying Primary Research Articles

Searching for primary research, databases with primary research, how will i know it's a research study, structure of an experimental article.

• The author summarizes the article
• The author discusses the general background of the research topic; often, they will present a literature review, that is, summarize what other experts have written on this particular research topic
• The author describes the experiment they designed and conducted
• The author presents the data they gathered during the experiment
• The author offers ideas about the importance and implications of their research findings, and speculates on future directions that similar research might take
• The author gives a reference list of sources used in the paper

Also, experimental/empirical articles are written in very formal, technical language and will usually contain numerical data presented in tables. Because primary research articles are written in technical language by professional researchers for experts like themselves, the articles can be very hard to understand. However, if you carefully review the introduction, results, and discussion sections, you will usually be able to understand and use one or two main ideas that the author is trying to get across, like why their experiment is important, and what results they discovered.

Determine keywords for your research topic. Avoid sentences or long phrases.

• PTSD OR "post traumatic stress disorder"

Add one of these keyword phrases to your search:

• "empirical study"
• "empirical research"
• "primary research"
• (methods AND results)
• methodology

Or add more than one to create a larger search string:

• "empirical study" OR "empirical research" OR "primary research"
• "empirical study" AND (methods AND results) OR methodology

Your entire search might look like :

• (PTSD OR "post traumatic stress disorder") AND ("em pirical study" OR "empirical research" OR "primary research")
• ScienceDirect Articles and books covering the physical sciences, engineering, life sciences, health sciences, social sciences, and humanities, from 1995 - present. NOTE: The blue Sign In button is not in use by UMGC. more... less... Copyright and Terms & Conditions 'Copyright ©, Elsevier B.V., ALL RIGHTS RESERVED' See the Elsevier B.V. TERMS & CONDITIONS WEBSITE FOR MORE INFORMATION .
• APA PsycInfo Articles, book chapters, case studies, empirical studies, etc. for psychology and the behavioral/social sciences, from the 1800s - present.
• MEDLINE Articles about medicine, nursing, dentistry, veterinary medicine, the health care system, etc., from 1965 - present.
• Health Source: Nursing/Academic Edition Ebooks, journal articles, etc. about medicine and health, with an emphasis on nursing and allied health subjects, from 1987 - present. more... less... Also includes the Clinical Pharmacology database, providing access to up-to-date drug monographs.
• << Previous: History Resources
• Last Updated: Aug 8, 2023 1:53 PM
• URL: https://libguides.umgc.edu/primary

Understanding Nursing Research

What is primary research, how can i tell if my article is "primary research", limiting your search to primary research.

• Qualitative vs. Quantitative Research
• Experimental Design
• Is it a Nursing journal?
• Is it Written by a Nurse?
• Systematic Reviews and Secondary Research
• Quality Improvement Plans

Your Team! College of Education and Human Development and College of Nursing and Health Sciences

Left to Right: Trisha Hernandez, Emily Murphy, Lorin Flores, Aida Almanza-Ferro.

We are the librarians for College of Education and Human Development, and the College of Nursing. We look forward to working with you! To contact us or to make an appointment:

Submit your request and we'll get right back to you!

Or, you can reach out directly. For our email addresses and phone numbers, see the list below:

Aida Almanza-Ferro  | [email protected] | 361-825-2356 Lorin Flores | [email protected] | 361-825-2609 Trisha Hernandez | [email protected]  |361-825-2687 Emily Sartorius Murphy  | [email protected] | 361-825-2610 Librarians are available M-F, 8-5.

The phrase "Primary" can mean something different depending on what subject you're in.

In History , for example, you might hear the phrase "primary sources." This means the researcher is looking for sources that date back to when an event occurred. Primary sources can be a diary, a photograph, or a newspaper clipping.

If this is the kind of research you're looking for, check out this research guide on how to find primary sources:

• Primary Sources

If you're in Nursing or another scientific field you're more likely to hear the phrase "Primary Research."

Primary Research refers to research that was conducted by the author of the article you're reading. So if you're reading an article and in the methodology section the author refers to recruiting participants, identifying a control group, etc. you can be pretty sure the author has conducted the research themselves.

When you're asked to find primary research, you're being asked to find articles describing research that was conducted by the authors.

Check out the video below for an explanation of the differences between primary and secondary research.

To determine if the article you're looking at is considered Primary Research, look for the following:

• In the Abstract, can you find a description of research being conducted?
• Were participants recruited?
• Were surveys distributed?

The main question to ask yourself is "Did the author conduct research, or did they read and synthesize other people's research?"

If you've found an article in CINAHL and you want to know if it's primary research, look under "Publication Type" to see if it's a research article.

This is not always 100% correct, though. To be sure, you should always read the Methodology section to understand what kind of article you're looking at.

If you're using PubMed, you can check the article's Keywords and Abstract for clues to see if the article is primary research, like in the article below:

Or you can check to see if the article includes a "Publication Type" section like this article:

The following Publication Types are usually considered Primary Research:

• Adaptive Clinical Trial
• Clinical Study
• Clinical Trial
• Controlled Clinical Trial
• Equivalence Trial
• Evaluation Studies
• Observational Study
• Pragmatic Clinical Trial
• Randomized Controlled Trial

Remember, you will always need to read the Methodologies section of an article to be sure the article is an example of primary research!

In certain databases you can specify that you're only interested in resources that are considered primary research.

Two of those databases are CINAHL and PubMed, which you can access here:

To limit your results to primary research in CINAHL, check the "Research Article" box on the homepage before you hit "Search"

This check box is helpful, but it isn't 100% correct, so always read the Methodology section of your article to determine what kind of article it is!

If you're conducting a search in PubMed and want to limit your results to a certain kind of article, you can enter your search terms on the homepage and click "Search."

Then, when you're on your results page, use the limiters on the left side of the screen to specify the "Article Type" you're interested in. Under "Article Types" click the "Customize..." link to see the full list of article types available to you.

Check any of the article types you're interested in (don't forget to scroll down on this list!) and then click the blue "Show" button at the bottom of the pop up window.

Now the Article Types you just selected should appear under the Article Types heading. Click on the article types you want to show up in your results list and your results will limit themselves to just those that meet your criteria.

Remember to read the article's Methodology section yourself before deciding whether or not it's Primary Research! These limits are great, but they aren't always 100% accurate.

• Next: Qualitative vs. Quantitative Research >>
• Last Updated: Feb 6, 2024 9:34 AM
• URL: https://guides.library.tamucc.edu/nursingresearch

• Harvard Library
• Research Guides
• Faculty of Arts & Sciences Libraries
• Identifying Articles
• PubMed at Harvard
• Searching in PubMed
• My NCBI in PubMed
• Utilizing Search Results
• Scenarios in PubMed

Primary Research Article

Review article.

Identifying and creating an APA style citation for your bibliography: 

• Author initials are separated by a period
• Multiple authors are separated by commas and an ampersand (&)  
• Title format rules change depending on what is referenced
• Double check them for accuracy 

Identifying and creating an APA style in-text citation: 

• eg. (Smith, 2022) or (Smith & Stevens, 2022) 

The structure of this changes depending on whether a direct quote or parenthetical used:

Direct Quote: the citation must follow the quote directly and contain a page number after the date

eg. (Smith, 2022, p.21)

Parenthetical: the page number is not needed

For more information, take a look at Harvard Library's Citation Styles guide !

A primary research article typically contains the following section headings:

"Methods"/"Materials and Methods"/"Experimental Methods"(different journals title this section in different ways)

"Results"

"Discussion"

If you skim the article, you should find additional evidence that an experiment was conducted by the authors themselves.

Primary research articles provide a background on their subject by summarizing previously conducted research, this typically occurs only in the Introduction section of the article.

Review articles do not report new experiments. Rather, they attempt to provide a thorough review of a specific subject by assessing either all or the best available scholarly literature on that topic.

Ways to identify a review article: 

• Author(s) summarize and analyze previously published research 
• May focus on a specific research question, comparing and contrasting previously published research 
• Overview all of the research on a particular topic 
• Does not contain "methods" or "results" type sections
• << Previous: Scenarios in PubMed
• Last Updated: Oct 3, 2023 4:16 PM
• URL: https://guides.library.harvard.edu/PubMed

Harvard University Digital Accessibility Policy

BIO 191: General Biology I

• Get Ready to Search
• Find Articles
• What is a Scholarly Article?
• What is a Peer-Reviewed Article?

What is a Primary Research Article?

How do you identify primary research articles.

• Cite Your Sources

Librarian for the Sciences

In a primary research article, author(s) present a new set of findings from original research after conducting an original experiment. Think of what you do in any of your various lab activities. If you were to write a scholarly paper on any of your biology labs (like the Flowers and Pollinators lab from BIO 191), it would be a primary research article.

Primary research articles are also referred to as original research or research articles.

How to Identify Primary Research Article

• Did the author(s) of the paper conduct the experiment themselves? This is the most important thing to look for in order to identify primary research. Look for language that indicates that the author(s) devised the experiment, carried it out, and analyzed the resulting data themselves.
• "Methods"/"Materials and Methods"/"Experimental Methods"(different journals title this section in different ways)
• "Results"
• "Discussion"

Here is One Example of a Primary Research Article and How to Determine that it is a Primary Research Article

"Effects of Salinity Stress on Survival, Metabolism, Limb Regeneration, and Ecdysis in UCA PUGNAX"

Read the Abstract

If you read the abstract, you can see that the author(s) themselves conducted an experiment:

• "This study investigated physiological and metabolic changes in the molt cycle of U. pugnax..."
• "For this study, a limb was removed and its regenerative growth was photographed every two days"
• "...crabs were dissected, and the tissues collected were analyzed for their protein and carbohydrate contents."

Read the Headings

• The article has Materials and Methods, Results, and Discussion sections, all which indicate that the authors conducted an experiment and then analyzed the data they found.

Skim the Article

If you skim the article, it is clear that the authors tested a hypothesis using the scientific method. They are only really talking about research that was conducted by others in the "Introduction" section of the article, which is what you would expect for a primary research article.

Look for Textual Evidence

If you skim the article, you can easily find additional evidence that an experiment was conducted by the authors themselves.

• [They collected their sample i.e. crabs.]
• [They exposed their sample to different variables.]
• [They used statistical methods to analyze their data.]
• [They reported the results of their experiment.]
• [They drew a conclusion from their experimental results.]
• << Previous: What is a Peer-Reviewed Article?
• Next: Cite Your Sources >>
• Last Updated: Jan 18, 2024 2:01 PM
• URL: https://resources.library.lemoyne.edu/courses/bio191

"How Do I?" @JWULibrary

Sample Question

• JWU-Providence Library

Q. How can I tell if a research article is a primary or secondary source?

Primary research articles  discuss original, empirical research study conducted by the authors.

The purpose of this type of article is to provide readers with a detailed overview of how the study was conducted, what types of methods the authors used to measure their results, how the authors interpret the results, and recommendations based on those results as well ideas for further research in the area. A primary research article should include all of the following:

• A research question(s) or hypothesis.
• A "methods" or "methodology" section that describes how the study was conducted. Sometimes this section might go by a different name like "data collection" or "research design."
• A "results" section that discusses what the authors found out from their research.
• A "discussion" and/or "conclusion" section where the the authors acknowledge the limits of the study, discuss the significance of the results, and make recommendations for further research.

Features like charts, maps, and surveys are common in primary research articles. Look for word clues like sample size, investigation, experiment, control group, and model, which are commonly found in the abstracts of primary research articles. Primary research articles tend to be longer (10 or more pages) because of the amount of information included.

A  secondary   source  can still be published in a peer reviewed journal, but it does not contain any original research. Some examples of secondary sources are:

• Literature Reviews - authors summarize and evaluate previous research that has been done on a topic.
• Review articles - authors form conclusions by analyzing and discussing multiple primary research studies. (These are often peer reviewed)
• Editorials and opinion pieces.
• Encyclopedia entries.
• 35 about the library
• 29 articles & journals
• 1 Borrowing
• 9 citing sources
• 17 company & industry
• 11 computers
• 1 copyright compliance
• 5 countries & travel
• 2 course registration
• 10 culinary
• 51 databases
• 3 education
• 2 Interlibrary loan
• 5 job search
• 6 libguides
• 9 market research
• 25 my library account
• 12 requests
• 26 research basics
• 20 research topics
• 2 study rooms
• 16 technology
• 7 textbooks
• 42 university
• 3 video tutorial
• 1 writing_help

Answered By: Rebecca Gagne Last Updated: Apr 04, 2024     Views: 0

• Share on Facebook

Was this helpful? Yes 0 No 0

Comments (0)

Related topics.

• about the library
• articles & journals
• citing sources
• company & industry
• copyright compliance
• countries & travel
• course registration
• Interlibrary loan
• market research
• my library account
• research basics
• research topics
• study rooms
• video tutorial
• writing_help

Downcity Library:

111 Dorrance Street Providence, Rhode Island 02903

401-598-1121

Harborside Library:

321 Harborside Boulevard Providence, RI 02905

401-598-1466

• Location and Directions
• Off-Campus Access
• Staff Directory
• Student Employment
• Pay Bills and Fines
• Chat with a Librarian
• Course Reserves
• Interlibrary Loan (ILL)
• Study Rooms
• Research Appointment
• Culinary Museum

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• BMC Med Res Methodol

Primary versus secondary source of data in observational studies and heterogeneity in meta-analyses of drug effects: a survey of major medical journals

Guillermo prada-ramallal.

1 Department of Preventive Medicine and Public Health, University of Santiago de Compostela, c/ San Francisco s/n, 15786 Santiago de Compostela, A Coruña, Spain

2 Health Research Institute of Santiago de Compostela (Instituto de Investigación Sanitaria de Santiago de Compostela - IDIS), Clinical University Hospital of Santiago de Compostela, 15706 Santiago de Compostela, Spain

Fatima Roque

3 Research Unit for Inland Development, Polytechnic of Guarda (Unidade de Investigação para o Desenvolvimento do Interior - UDI/IPG), 6300-559 Guarda, Portugal

4 Health Sciences Research Centre, University of Beira Interior (Centro de Investigação em Ciências da Saúde - CICS/UBI), 6200-506 Covilhã, Portugal

Maria Teresa Herdeiro

5 Department of Medical Sciences & Institute for Biomedicine – iBiMED, University of Aveiro, 3810-193 Aveiro, Portugal

6 Higher Polytechnic & University Education Co-operative (Cooperativa de Ensino Superior Politécnico e Universitário - CESPU), Institute for Advanced Research & Training in Health Sciences & Technologies, 4585-116 Gandra, Portugal

Bahi Takkouche

7 Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública – CIBERESP), Santiago de Compostela, Spain

Adolfo Figueiras

Associated data.

All data generated or analysed during this study are included in this published article.

The data from individual observational studies included in meta-analyses of drug effects are collected either from ad hoc methods (i.e. “primary data”) or databases that were established for non-research purposes (i.e. “secondary data”). The use of secondary sources may be prone to measurement bias and confounding due to over-the-counter and out-of-pocket drug consumption, or non-adherence to treatment. In fact, it has been noted that failing to consider the origin of the data as a potential cause of heterogeneity may change the conclusions of a meta-analysis. We aimed to assess to what extent the origin of data is explored as a source of heterogeneity in meta-analyses of observational studies.

We searched for meta-analyses of drugs effects published between 2012 and 2018 in general and internal medicine journals with an impact factor > 15. We evaluated, when reported, the type of data source (primary vs secondary) used in the individual observational studies included in each meta-analysis, and the exposure- and outcome-related variables included in sensitivity, subgroup or meta-regression analyses.

We found 217 articles, 23 of which fulfilled our eligibility criteria. Eight meta-analyses (8/23, 34.8%) reported the source of data. Three meta-analyses (3/23, 13.0%) included the method of outcome assessment as a variable in the analysis of heterogeneity, and only one compared and discussed the results considering the different sources of data (primary vs secondary).

Conclusions

In meta-analyses of drug effects published in seven high impact general medicine journals, the origin of the data, either primary or secondary, is underexplored as a source of heterogeneity.

Electronic supplementary material

The online version of this article (10.1186/s12874-018-0561-3) contains supplementary material, which is available to authorized users.

Specific research questions are ideally answered through tailor-made studies. Although these ad hoc studies provide more accurate and updated data, designing a completely new project may not represent a feasible strategy [ 1 , 2 ]. On the other hand, clinical and administrative databases used for billing and other fiscal purposes (i.e. “secondary data”) are a valuable resource as an alternative to ad hoc methods (i.e. “primary data”) since it is easier and less costly to reuse the information than collecting it anew [ 3 ]. The potential of secondary automated databases for observational epidemiological studies is widely acknowledged; however, their use is not without challenges, and many quality requirements and methodological pitfalls must be considered [ 4 ].

Meta-analysis represents one of the most valuable tools for assessing drug effects as it may lead to the best evidence possible in epidemiology [ 5 ]. Consequently, its use for making relevant clinical and regulatory decisions on the safety and efficacy of drugs is dramatically increasing [ 6 ]. Existence of heterogeneity in a given meta-analysis is a feature that needs to be carefully described by analyzing the possible factors responsible for generating it [ 7 ]. In this regard, the results of a recent study [ 8 ] show that whether the origin of the data (primary vs secondary) is explored as a potential cause of heterogeneity may change the conclusions of a meta-analysis due to an effect modification [ 9 ]. Thus, considering the source of data as a variable in sensitivity and subgroup analyses, or meta-regression analyses, seems crucial to avoid misleading conclusions in meta-analyses of drug effects.

Given the evidence noted [ 8 , 9 ], we surveyed published meta-analyses in a selection of high-impact journals over a 6-year period, to assess to what extent the origin of the data, either primary or secondary, is explored as a source of heterogeneity in meta-analyses of observational studies.

Meta-analysis selection and data collection process

General and internal medicine journals with an impact factor > 15 according to the Web of Science were included in the survey [ 10 ]. This method has been widely used to assess quality as well as publication trends in medical journals [ 11 – 13 ]. The rationale is that meta-analyses published in high impact journals: (1) are likely to be rigorously performed and reported due to the exhaustive editorial process [ 12 , 14 ]; and, (2) in general, exert a higher influence on medical practice due to the major role played by these journals in the dissemination of the new medical evidence [ 14 , 15 ]. We searched MEDLINE on May 2018 using the search terms “meta-analysis” as publication type and “drug” in any field between January 1, 2012 and May 7, 2018 in the New England Journal of Medicine ( NEJM ), Lancet, Journal of the American Medical Association ( JAMA) , British Medical Journal ( BMJ ), JAMA Internal Medicine (JAMA Intern Med) , Annals of Internal Medicine ( Ann Intern Med ), and Nature Reviews Disease Primers (Nat Rev Dis Primers) .

Two investigators (GP-R, FR) independently assessed publications for eligibility. Abstracts were screened and if deemed potentially relevant, full text articles were retrieved. Articles were excluded if they met any of the following conditions: (1) were not a meta-analysis of published studies, (2) no drug effects were evaluated, (3) only randomized clinical trials were included in the meta-analysis (in order to consider observational studies), (4) less than two observational studies were included in the meta-analysis (since with a single study it would not have been possible to calculate a pooled measure). When a meta-analysis included both observational studies and clinical trials, only observational studies were considered.

A data extraction form was developed previously to extract information from articles. Two investigators (GP-R, FR) independently extracted and recorded the information and resolved discrepancies by referring to the original report. If necessary, a third author (AF) was asked to resolve disagreements between the investigators.

When available we extracted the following data from each eligible meta-analysis: first author, publication year, journal, drug(s) exposure and outcome(s); number of individual studies included in the meta-analysis based on each type of data source used (primary vs secondary), for both exposure and outcome assessment; and exposure- and outcome-related variables included in sensitivity, subgroup or meta-regression analyses. We extracted data directly from the tables, figures, text, and supplementary material of the meta-analyses, not from the individual studies.

Assessment of exposure and outcome

We considered “primary data” the information on drug exposure collected directly by the researchers using interviews –personal or by telephone– or self-administered questionnaires. The origin of the data was also considered primary when objective diagnostic methods were used for the determination of drug exposure (e.g. blood test). “Secondary data” are data that were formerly collected for other purposes than that of the study at hand and that were included in databases on drug prescription (e.g. prescription registers, medical records/charts) and dispensing (e.g. computerized pharmacy records, insurance claims databases). Regarding the outcome assessment, we considered primary data when an objective confirmation is available that endorses them (e.g. confirmed by individual medical ad hoc diagnosis, lab test or imaging results). These criteria are based on those commonly used in the risk assessment of bias for observational studies [ 16 – 19 ].

MEDLINE search results yielded 217 articles from the major general medical journals (3 from NEJM , 46 from Lancet , 26 from JAMA , 85 from BMJ , 19 from JAMA Intern Med, 38 from Ann Intern Med, and 0 from Nat Rev Dis Primers ) (see Fig. ​ Fig.1). 1 ). A total of 194 articles were excluded (see list of excluded articles with reasons for exclusion in Additional file 1 ) leaving 23 articles to be examined [ 20 – 42 ]. General characteristics of the 23 included meta-analyses are outlined in Table ​ Table1 1 .

Flow diagram of literature search results

Characteristics of the 23 included meta-analyses

Abbreviations : AABs antibodies against biologic agents, ACEIs , angiotensin converting enzyme inhibitors, Ann Intern Med Annals of Internal Medicine , ARBs angiotensin receptor blockers, BMJ British Medical Journal , DPP-4 Dipeptidyl Peptidase-4, GLP-1 glucagon like peptide-1, JAMA Journal of the American Medical Association , MIC minimum inhibitory concentration, NSAIDs non-steroidal anti-inflammatory drugs, SGLT-2 sodium–glucose cotransporter 2, SSRIs selective serotonin reuptake inhibitors

Source of exposure and outcome data

Table ​ Table2 2 summarizes the evidence regarding the type of data source included in each meta-analysis, according to the information presented in the data extraction tables of the article. The information was evaluated taking the study design into account. Only eight meta-analyses [ 21 , 24 , 26 , 31 , 32 , 34 , 38 , 41 ] reported the source of data, three of them [ 31 , 34 , 38 ] reporting mixed sources for both the exposure and outcome assessment. Five meta-analyses [ 21 , 24 , 26 , 32 , 41 ] reported only secondary sources for the exposure assessment, three of them [ 21 , 24 , 41 ] reporting as well only secondary sources for the outcome assessment, while in the other two [ 26 , 32 ] only primary and mixed sources for the outcome assessment were reported respectively.

Reporting of the data source in the data extraction tables of the included meta-analyses

Abbreviations : 1ry number of individual studies in each MA based on primary data sources, 2ry number of individual studies in each MA based on secondary data sources, NR number of individual studies in each MA with not reported data source

a Although the meta-analysis shows the results of methodological quality assessment based on a standardized scale, it does not indicate the type of data source used for each individual observational study included in the meta-analysis

b Cohort with nested case-control analysis

c The meta-analysis reports that most of the included observational studies assessed medication exposure through a review of medical records

d The meta-analysis reports only data from high-quality observational studies

Source of data in the analysis of heterogeneity

All but two [ 20 , 42 ] of the meta-analyses performed subgroup and/or sensitivity analyses. Although three of them [ 23 , 34 , 36 ] considered the methods of outcome assessment – type of diagnostic assay used for Clostridium difficile infection, method of venous thrombosis diagnosis confirmation, and type of scale for psychosis symptoms assessment respectively– as stratification variables, only the second referred to the origin of the data. Only five meta-analyses [ 22 , 28 , 33 , 35 , 39 ] included meta-regression analyses to describe heterogeneity, none of which considered the source of data as an explanatory variable. Other findings for the inclusion of the data source as a variable in the analysis of heterogeneity are presented in Table ​ Table3 3 .

Inclusion of the data source as a variable in the analysis of heterogeneity of the included meta-analyses

Abbreviations : APACHE acute physiology and chronic health evaluation, MIC minimum inhibitory concentration, SSRIs selective serotonin reuptake inhibitors, TNF tumor necrosis factor

We finally assessed if the influence of the data origin on the conclusions of the meta-analyses was discussed by their respective authors. We found that only four meta-analyses [ 21 , 31 , 32 , 34 ] noted limitations derived from the type of data source used.

The findings of this research suggest that the origin of the data, either primary or secondary, is underexplored as a source of heterogeneity and an effect modifier in meta-analyses of drug effects published in general medicine journals with high impact. Few meta-analyses reported the source of data and only one [ 34 ] of the articles included in our survey compared and discussed the meta-analysis results considering the different sources of data.

Although it is usual to consider the design of the individual studies (i.e. case-control, cohort or experimental studies) in the analysis of the heterogeneity of a meta-analysis [ 43 , 44 ], the type of data source (primary vs secondary) is still rarely used for this purpose [ 9 , 45 ]. In fact, the current reporting guidelines for meta-analyses, such as MOOSE (Meta-analysis Of Observational Studies in Epidemiology) [ 18 ] or PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) [ 46 , 47 ], do not recommend that authors specifically report the origin of the data. This is probably due to the close relationship that exists between the study design and the type of data source used, despite the fact that each criterion has its own basis. Performing this additional analysis is a simple task that involves no additional cost. Failure to do so may lead to diverging conclusions [ 8 ].

Conclusions about the effects of a drug that are derived from studies based exclusively on data from secondary sources may be dicey, among other reasons, because no information is collected on consumption of over-the-counter drugs (i.e. drugs that individuals can buy without a prescription) [ 48 ] and/or out-of-pocket expenses for prescription drugs (i.e. costs that individuals pay out of their own cash reserves) [ 49 ]. In the health care and insurance context, out-of-pocket expenses usually refer to deductibles, co-payments or co-insurance. Figure ​ Figure2 2 shows the model that we propose to describe the relationship between the different data records according to their origin, including the possible loss of information (susceptible to be registered only through primary research).

Conceptual model of individual data recording. * Never dispensed. † Absence of dispensing of successive prescriptions (or self-medication) among patients with primary adherence, or inadequate secondary adherence

Failure to take these situations into account may lead to exposure measurement bias [ 48 , 49 ]. Consumption of a drug may be underestimated when only prescription data is used as secondary source without additionally considering unregistered consumption, such as over-the-counter consumption (e.g. oral contraceptives [ 34 , 50 ]), that may only be available from a primary database. Alternatively, this may occur when dispensing data for billing purposes (reimbursement) are used for clinical research, if out-of-pocket expenses are not considered (see Fig. ​ Fig.2). 2 ). The portion of the medical bill that the insurance company does not cover, and that the individual must pay on his own, is unlikely to be recorded. Data on the sale of over-the-counter drugs will also not be available in this scenario.

The reverse situation may also occur and consumption may be overestimated when only prescription data is used, if the prescribed drug is not dispensed by the pharmacist; or when dispensing data is used, if the drug is not really consumed by the patient. While primary non-adherence occurs when the patient does not pick up the medication after the first prescription, secondary non-adherence refers to the absence of dispensing of successive prescriptions among patients with primary adherence, or to inadequate secondary adherence (i.e. ≥20% of time without adequate medication) [ 51 ] (see Fig. ​ Fig.2). 2 ). In some diseases the medication adherence is very low [ 52 – 55 ], with percentages of primary non-adherence (never dispensed) that exceed 30% [ 56 ]. It should be noted that the impact of non-adherence varies from medication to medication. Therefore, it must be defined and measured in the context of a particular therapy [ 57 ].

Moreover, failing to take into consideration the portion of consumption due to over-the-counter and/or out-of-pocket expenses may lead to confounding , as that variable may be related to the socio-economic level and/or to the potential of access to the health system [ 58 ], which are independent risk factors of adverse outcomes of some medications (e.g. myocardial infarction [ 21 , 28 , 30 , 41 ]). Given the presence of high-deductible health plans and the high co-insurance rate for some drugs, cost-sharing may deter clinically vulnerable patients from initiating essential medications, thus negatively affecting patient adherence [ 59 , 60 ].

Outcome misclassification may also give rise to measurement bias and heterogeneity [ 61 ]. This occurs, for example, in the meta-analysis that evaluates the relationship between combined oral contraceptives and the risk of venous thrombosis [ 34 ]. In the studies without objective confirmation of the outcome, the women were classified erroneously regardless of the use of contraceptives. This led to a non-differential misclassification that may have underestimated the drug–outcome relationship, especially when the third generation of progestogen is analysed: Risk ratio (RR) primary data = 6.2 (95% confidence interval (CI) 5.2–7.4), RR secondary data = 3.0 (95% CI 1.7–5.4) [ 34 ].

On the one hand, medical records are often considered as being the best information source for outcome variables. However, they present important limitations in the recording of medications taken by patients [ 62 ]. On the other hand, dispensing records show more detailed data on the measurement of drug exposure. However, they do not record the over-the-counter or out-of-pocket drug consumption at an individual level [ 48 , 49 ], apart from offering unreliable data on outcome variables [ 62 , 63 ].

Limitations

The first limitation of this research is that its findings may not be applicable to journals not included in our survey such as journals with low impact factor. Despite the widespread use of the impact factor metric [ 64 ], this method has inherent weaknesses [ 65 , 66 ]. However, meta-analyses published in high impact general medicine journals are likely to be most rigorously performed and reported due to their greater availability of resources and procedures [ 12 , 14 ]. It is then expected that the overall reporting quality of articles published in other lesser-known journals will be similar. Another limitation would be related to the limited search period . In this sense, and given that the general tendency is the improvement of the methodology of published meta-analyses [ 67 , 68 ], we find no reason to suspect that the adverse conclusions could be different before the period from 2012 to 2018. Although it exceeds the objective of this research, one last limitation may be the inability to reanalyse the included meta-analyses stratifying by the type of data source since our study design restricts the conclusions to the published data of the meta-analyses, which were insufficiently reported , or the number of individual studies in each stratum was insufficient to calculate a pooled measure (see Table ​ Table2 2 ).

Owing to automated capture of data on drug prescription and dispensing that are used for billing and other administration purposes, as well as to the implementation of electronic medical records, secondary databases have generated enormous possibilities. However, neither their limitations, nor the risk of bias that they pose should be overlooked [ 69 ]. Thus, researchers should consider the link between administrative databases and medical records, as well as the advisability of combining secondary and primary data in order to minimize the occurrence of biases due to the use of any of these databases.

No source of heterogeneity in a meta-analysis should ever be considered alone but always as part of an interconnected set of potential questions to be addressed. In particular, the origin of the data, either primary or secondary, is insufficiently explored as a source of heterogeneity in meta-analyses of drug effects, even in those published in high impact general medicine journals. Thus, we believe that authors should systematically include the source of data as an additional variable in subgroup and sensitivity analyses, or meta-regression analyses, and discuss its influence on the meta-analysis results. Likewise, reviewers, editors and future guidelines should also consider the origin of the data as a potential cause of heterogeneity in meta-analyses of observational studies that include both primary and secondary data. Failure to do this may lead to misleading conclusions, with negative effects on clinical and regulatory decisions.

Additional file

Excluded articles. List of articles excluded with reasons for exclusion. (PDF 247 kb)

This study received no funding from the public, commercial or not-for-profit sectors.

Availability of data and materials

Abbreviations, authors’ contributions.

AF and GP-R contributed to study conception and design. GP-R, FR and AF contributed to searching, screening, data collection and analyses. GP-R was responsible for drafting the manuscript. FR, MTH, BT and AF provided comments and made several revisions of the manuscript. All authors read and approved the final version.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Competing interests.

The authors declare that they no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Guillermo Prada-Ramallal, Email: [email protected] .

Fatima Roque, Email: tp.gpi@euqorf .

Maria Teresa Herdeiro, Email: tp.au@oriedrehaseret .

Bahi Takkouche, Email: [email protected] .

Adolfo Figueiras, Phone: (+34) 981 95 11 92, Email: [email protected] .

Explore millions of high-quality primary sources and images from around the world, including artworks, maps, photographs, and more.

Explore migration issues through a variety of media types

• Part of The Streets are Talking: Public Forms of Creative Expression from Around the World
• Part of The Journal of Economic Perspectives, Vol. 34, No. 1 (Winter 2020)
• Part of Cato Institute (Aug. 3, 2021)
• Part of University of California Press
• Part of Open: Smithsonian National Museum of African American History & Culture
• Part of Indiana Journal of Global Legal Studies, Vol. 19, No. 1 (Winter 2012)
• Part of R Street Institute (Nov. 1, 2020)
• Part of Leuven University Press
• Part of UN Secretary-General Papers: Ban Ki-moon (2007-2016)
• Part of Perspectives on Terrorism, Vol. 12, No. 4 (August 2018)
• Part of Leveraging Lives: Serbia and Illegal Tunisian Migration to Europe, Carnegie Endowment for International Peace (Mar. 1, 2023)
• Part of UCL Press

Harness the power of visual materials—explore more than 3 million images now on JSTOR.

Enhance your scholarly research with underground newspapers, magazines, and journals.

Explore collections in the arts, sciences, and literature from the world’s leading museums, archives, and scholars.

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Published: 08 April 2024

Where and how are we going? Simplifying the definitive diagnosis of primary aldosteronism

• Tetsuo Nishikawa 1 , 2 ,
• Kazuki Nakai 1 ,
• Yuya Tsurutani 1 ,
• Yoko Matsuzawa 1 , 3 ,
• Jun Saito 1 &
• Masao Omura 1 , 4  

Hypertension Research ( 2024 ) Cite this article

Metrics details

Primary aldosteronism (PA) is the most common cause of secondary hypertension in adults [ 1 , 2 ]. In Japan, plasma aldosterone concentration (PAC) measurements have typically relied on radioimmunoassay (RIA) methods such as the Spac-S® kit (Fujirebio Inc., Tokyo, Japan), which was discontinued in March of 2021. In a recent study, we compared and commutated blood aldosterone measurements using clinical specimens to clarify the commutability among RIA-equivalent values, liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) values, and chemiluminescent enzyme immunoassay (CLEIA) kits [ 3 ]. LC-MS/MS is emerging as a promising method for clinical examination, offering more accurate and reproducible aldosterone estimations than traditional methods [ 4 , 5 , 6 ]. However, regression analysis indicated significant discrepancies between RIA values estimated using Spac-S® compared to other methods, likely owing to the low specificity of RIA antibodies and variation in measurements [ 3 ]. We found that the median LC-MS/MS value corresponding to 120 pg/mL of RIA was 48.5 pg/mL [ 3 ]. Tezuka et al. have reported that novel CLEIA methods may serve as alternative standards for PACs, suggesting other applications for CLEIAs in clinical practices [ 7 ]. Furthermore, the Japan Endocrine Society has proposed new criteria for PA screening and confirmatory testing, although these diagnostic cutoffs currently lack sufficient validation [ 8 ]. The captopril challenge test (CCT) is a well-established method for distinguishing PA from essential hypertension [ 9 ]. According to a recent meta-analysis, CCT has been reported to exhibit high and comparable accuracy for diagnosing PA, as it is safe and much easier to perform [ 10 ]. Thus, CCT appears to be one of the main and most appropriate confirmatory tests for the definitive diagnosis of PA. The first version of The Japan Endocrine Society guidelines for the diagnosis and treatment of PA (2009) described the CCT procedure as follows: (1) administration of 50 mg captopril (four crushed 12.5 mg captopril [Captoril ® ] tablets); (2) sampling of blood after 60-min bed rest (or 90 min of rest in the sitting position); and (3) evaluation of the test results, wherein a PAC/plasma renin activity (PRA) ratio (ARR) of >200 pg/mL per ng/mL/h (or a PAC of >120 pg/mL) indicates a positive result [ 11 ]. However, Tezuka et al. reported that no studies have yet compared PACs measured using CLEIA and conventional RIA methods in the same blood samples obtained from confirmatory tests [ 7 ]. Moreover, there are often questions surrounding PAC values obtained from clinical laboratory centers—such as whether the values are abnormally high (thus suggesting PA) simply because the CLEIA values must be converted to conventional RIA values in order to evaluate PA according to the criteria outlined in the guidelines. Tezuka et al. compared CLEIA-based PACs with RIA using 297 plasma samples [ 7 ]. They reported that the distributions of CLEIA- and RIA-PACs (medians with interquartile ranges) were 9.30 [4.00, 17.70] and 19.30 [12.35, 30.50] ng/dL, respectively. They concluded that the use of the conventional cutoff value could result in missing approximately half of patients with PA tested using CLEIA. They also proposed an ARR of 8.2 ng/dL per ng/mL/h as an alternative cutoff value for CLEIA-based CCT to diagnose PA, which is consistent with the former criteria. The Japan Endocrine Society has recently published a new guideline for PA, which sets a new CCT criterion of “provisional positive” for PA (ARR: 10–20 ng/dL per ng/mL/h) in addition to a “positive” category (ARR: >20 ng/dL per ng/mL/h) [ 8 ]. Tezuka et al. emphasized that the “provisional positive” cutoff was designed based on the conversion formula from CLEIA-PAC to RIA-PAC, but not on any validation using actual blood samples. They found that 28.2% and 17.2% of patients with positive RIA-based CCTs fell into “provisional positive” and “negative” criteria, respectively, of the CCT-based novel CLEIA evaluation. Furthermore, these groups harbored 17 and 5 unilateral PA (UPA) cases, respectively, in which adrenalectomy procedures would likely lead to PA remission. Furthermore, their study revealed that CLEIA-ARR could identify surgically treatable PA cases more efficiently than RIA-ARR. This was the first study to verify these CCT cutoff values for accurately diagnosing PA in patients with hypertension. They also reported that the lowest CLEIA-based ARR at CCT was 3.32 ng/dL per ng/mL/h (33.2 pg/mL per ng/mL/h) among patients with UPA. Of their 95 UPA cases, 85 had aldosterone-producing adenomas (APAs) and 10 had aldosterone-producing nodules or multiple micronodules. The CLEIA-ARR was higher in APA cases than in others. In addition, the CLEIA-ARRs correlated with the maximum APA diameters, in the cases with APAs. Thus, CLEIA-ARRs may also be useful for diagnosing UPA and predicting the size and pathology of aldosterone-producing lesions, although further investigations of this notion are warranted. We previously reported that CCT revealed higher ARRs in patients with aldosterone-producing macroadenoma than in those with aldosterone-producing microadenoma (APmicroA) or idiopathic hyperaldosteronism (IHA), whereas the ARRs of patients with APmicroA were similar to those of patients with IHA [ 12 ]. Therefore, APmicroA may be misdiagnosed as IHA if clinicians attempt to distinguish APA from IHA based on the findings of imaging methods such as adrenal computed tomography and magnetic resonance imaging. We emphasize that it is important to accurately diagnose APmicroA, in which the aldosterone excess is only detectable by ACTH-stimulated adrenal vein sampling, and to treat these patients via unilateral adrenalectomy to avoid long-term medical treatment and prevent hypertensive vascular complications, as has been previously reported [ 12 ]. It is generally accepted that an RIA-ARR of >200 pg/mL per ng/mL/h (20 ng/dL per ng/mL/h) can be used to diagnose PA following CCT before using CLEIA kits. Alternatively, the cutoff ARR value of 82 pg/mL per ng/mL/h (8.2 ng/dL per ng/mL/h) for CLEIA-based CCT can now be used to diagnose PA, according to the well-established data reported by Tezuka et al. [ 7 ]. The new guidelines [ 8 ] recommend judging the screening test to be positive when ARR is ≥200 pg/mL per ng/mL/h and PAC is ≥60 pg/mL, although there is still no strong evidence for the CLEIA-ARR or -PAC cutoff values. We are entering a new era in terms of accurately diagnosing PA, as well as investigating its pathogenesis and related disorders clinically, using CLEIA kits that measure LC-MS/MS equivalent values of aldosterone. We therefore propose new cutoff values for both CLEIA-ARR and CLEIA-PAC in Table  1 .

Omura M, Saito J, Yamaguchi K, Kakuta Y, Nishikawa T. Prospective study on the prevalence of secondary hypertension among hypertensive patients visiting a general outpatient clinic in Japan. Hypertens Res. 2004;27:193–202.

Article   PubMed   Google Scholar  

Nishikawa T, Saito J, Omura M. Is primary aldosteronism rare or common among hypertensive patients? Hypertens Res. 2007;30:103–04.

Nishikawa T, Satoh F, Takashi Y, Yanase T, Itoh H, Kurihara I, et al. Comparison and commutability study between standardized liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) and chemiluminescent enzyme immunoassay for aldosterone measurement in blood. Endocr J. 2022;69:45–54.

Article   CAS   PubMed   Google Scholar  

Taylor PJ, Cooper DP, Gordon RD, Stowasser M. Measurement of aldosterone in human plasma by semiautomated HPLC–tandem mass spectrometry. Clin Chem. 2009;55:1155–62.

Higashi T, Akaishi M, Yokota M, Suzuki T, Ogawa S, Sugiura Y, et al. A method for determination of aldosterone in adrenal tributary venous serum by derivatization using Girard P reagent isotopologues followed by LC/ESI-MS/MS. J Chromatogr B Anal Technol Biomed Life Sci. 2018;1092:106–13.

Article   CAS   Google Scholar  

Fries CM, Bae YJ, Rayes N, Sandner B, Isermann B, Stumvoll M, et al. Prospective evaluation of aldosterone LC-MS/MS-specific cutoffs for the saline infusion test. Eur J Endocrinol. 2020;183:191–201.

Tezuka Y, Omata K, Ono Y, Kambara K, Kamada H, Oguro S, et al. Investigating the cut-off values of captopril challenge test for primary aldosteronism using the novel chemiluminescent enzyme immunoassay method: a retrospective cohort study. Hypertens Res. 2024. https://doi.org/10.1038/s41440-024-01594-x .

Naruse M, Katabami T, Shibata H, Sone M, Takahashi K, Tanabe A, et al. Japan Endocrine Society clinical practice guideline for the diagnosis and management of primary aldosteronism 2021. Endocr J. 2022;69:327–59.

Lyons DF, Kem DC, Brown RD, Hanson CS, Carollo ML. Single dose captopril as a diagnostic test for primary aldosteronism. J Clin Endocrinol Metab. 1983;57:892–96.

Wu S, Yang J, Hu J, Song Y, He W, Yang S, et al. Confirmatory tests for the diagnosis of primary aldosteronism: a systematic review and meta-analysis. Clin Endocrinol (Oxf). 2019;90:641–48.

Nishikawa T, Omura M, Satoh F, Shibata H, Takahashi K, Tamura N, et al. Guidelines for the diagnosis and treatment of primary aldosteronism—the Japan Endocrine Society 2009. Endocr J. 2011;58:711–21.

Omura M, Sasano H, Saito J, Yamaguchi K, Kakuta Y, Nishikawa T. Clinical characteristics of aldosterone-producing microadenoma, macroadenoma, and idiopathic hyperaldosteronism in 93 patients with primary aldosteronism. Hypertens Res. 2006;29:883–89.

Download references

Acknowledgements

This study was partly supported by the Grant Research on Intractable Diseases provided by the Japanese Ministry of Health, Labor, and Welfare. We would like to thank Editage ( www.editage.jp ) for English language editing.

Author information

Authors and affiliations.

Endocrinology & Diabetes Center, Yokohama Rosai Hospital, Yokohama, Japan

Tetsuo Nishikawa, Kazuki Nakai, Yuya Tsurutani, Yoko Matsuzawa, Jun Saito & Masao Omura

Nishikawa Clinic, Yokohama, Japan

Tetsuo Nishikawa

Matsuzawa Clinic, Yokohama, Japan

Yoko Matsuzawa

Minato Mirai Medical Square, Yokohama, Japan

Masao Omura

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Tetsuo Nishikawa .

Ethics declarations

Conflict of interest.

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Cite this article.

Nishikawa, T., Nakai, K., Tsurutani, Y. et al. Where and how are we going? Simplifying the definitive diagnosis of primary aldosteronism. Hypertens Res (2024). https://doi.org/10.1038/s41440-024-01666-y

Download citation

Received : 15 February 2024

Revised : 08 March 2024

Accepted : 13 March 2024

Published : 08 April 2024

DOI : https://doi.org/10.1038/s41440-024-01666-y

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Chemiluminescent enzyme immunoassay
• Liquid chromatography-mass spectrometry/mass spectrometry
• Plasma aldosterone concentration
• Primary aldosteronism
• Radioimmunoassay

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

• Open access
• Published: 29 March 2024

Development of a nomogram based on the clinicopathological and CT features to predict the survival of primary pulmonary lymphoepithelial carcinoma patients

• Kai Nie 1 ,
• Lin Zhu 1 ,
• Yuxuan Zhang 2 ,
• Yinan Chen 1 ,
• John Parrington 2 &
• Hong Yu 1  

Respiratory Research volume  25 , Article number:  144 ( 2024 ) Cite this article

111 Accesses

Metrics details

The aim of this study was to develop a nomogram by combining chest computed tomography (CT) images and clinicopathological predictors to assess the survival outcomes of patients with primary pulmonary lymphoepithelial carcinoma (PLEC).

113 patients with stage I–IV primary PLEC who underwent treatment were retrospectively reviewed. The Cox regression analysis was performed to determine the independent prognostic factors associated with patient’s disease-free survival (DFS) and cancer-specific survival (CSS). Based on results from multivariate Cox regression analysis, the nomograms were constructed with pre-treatment CT features and clinicopathological information, which were then assessed with respect to calibration, discrimination and clinical usefulness.

Multivariate Cox regression analysis revealed the independent prognostic factors for DFS were surgery resection and hilar and/or mediastinal lymphadenopathy, and that for CSS were age, smoking status, surgery resection, tumor site in lobe and necrosis. The concordance index (C‑index) of nomogram for DFS and CSS were 0.777 (95% CI: 0.703–0.851) and 0.904 (95% CI: 0.847–0.961), respectively. The results of the time‑dependent C‑index were internally validated using a bootstrap resampling method for DFS and CSS also showed that the nomograms had a better discriminative ability.

Conclusions

We developed nomograms based on clinicopathological and CT factors showing a good performance in predicting individual DFS and CSS probability among primary PLEC patients. This prognostic tool may be valuable for clinicians to more accurately drive treatment decisions and individualized survival assessment.

Primary pulmonary lymphoepithelial carcinoma (PLEC) is a unique and rare subtype of non-small-cell lung cancer (NSCLC), accounting for less than 0.7% of all NSCLCs [ 1 , 2 , 3 ]. PLEC was first reported in 1987 and histologically resembles undifferentiated nasopharyngeal carcinoma (NPC) [ 4 ]. From the epidemiological and etiological perspective, PLEC is more common in Asian ethnicities, tends to occur in relatively young and middle-aged individuals, and is generally considered to be closely related to Epstein–Barr virus (EBV) infection [ 5 ]. PLEC was previously classified as a subtype of large-cell lung cancer [ 6 ]. In 2015, the World Health Organization (WHO) classified it as one of the “other and unclassified carcinomas” [ 7 ]. In contrast, the latest 5th edition of the WHO classification of thoracic tumors in 2021 re-categorized PLEC as a subtype of squamous cell carcinomas (SCCs) [ 8 ]. The constantly changing classification of PLEC indicates the imperative need for further research.

Currently, the treatment of PLEC mainly follows the NCCN Clinical Practice Guidelines for NSCLC [ 9 , 10 ]. Due to the rarity of primary PLEC, the standard of management for this disease is not still established [ 9 ]. In particular, mutations of commonly driven genes are lacking for PLEC patients, and targeted therapy drugs have little significance [ 11 ]. Therefore, the lack of treatment methods and experience for treating PLEC patients indicates an imperative need for individualized clinical management and precise survival prediction.

In a prognostic setting, the estimation of risk probability is rarely based on individual risk factors, as reliable estimates are insufficient. Discovering more prognostic factors and estimating based on multivariate models are now considered more reliable methods. Chest computed tomography (CT) is the routine imaging method for lung cancer detection and post-treatment management, and the CT image features have significant value in the diagnosis and prognosis of lung cancer [ 12 , 13 ]. However, the relevant studies on imaging characteristics of primary PLEC are very few, and the cohort size of each published study was quite small [ 13 , 14 , 15 , 16 ]. Several reports have integrated clinical and pathological data from several PLEC patients for prognostic evaluation [ 17 , 18 ], but the CT imaging features associated with the survival outcome of primary PLEC have not yet been described.

Therefore, this study aimed to develop a model including clinicopathological and CT features to estimate the disease-free survival (DFS) and cancer-specific survival (CSS) in patients with primary PLEC and to evaluate its clinical predictive ability and net benefit rate for individual survival estimation.

This retrospective study was approved by the institutional review board (No. IS22019), and the requirement for written informed consent was waived.

This study was conducted in patients with pathologically diagnosed PLEC between October 2009 and March 2023 at Shanghai Chest Hospital Affiliated to the Shanghai Jiao Tong University School of Medicine (Shanghai, China). In total, 141 cases were initially retrospectively recruited. The inclusion criteria were as follows: (1) CT scan was performed before treatment; (2) The diagnosis of primary PLEC was confirmed by fine-needle biopsy or complete surgical resection pathology; (3) The patient’s baseline characteristics and clinical data were complete. The exclusion criteria were as follows: (1) The past history of other malignancy, and (2) Metastasis of nasopharyngeal PLEC. Finally, A total of 113 patients were included in this study (51 males and 62 females; mean age, 56.8 years ± 11.5; range, 20–81 years). Figure  1 shows the patient recruitment pathway, along with the exclusion criteria. All primary PLEC tumors were reclassified based on the 5th edition of the WHO classification of Thoracic Tumors. Tumor staging was performed based on the American Joint Committee on Cancer TNM Staging Manual, 8th edition [ 19 ]. Among the 113 patients, 85 patients who underwent surgery provided pathological stage, while the remaining 28 patients who underwent non-surgical treatment provided clinical stage alone. We reviewed clinicopathological records and pre-treatment CT imaging data of all patients.

Flowchart shows patient selection

Imaging examination protocol

Among the 113 patients, 34 patients underwent a plain chest CT, 79 cases underwent both unenhanced and enhanced CT. Somatom Definition AS (Siemens Medical Systems, Erlangen, Germany) and Brilliance 40 (Philips Medical Systems, the Netherlands Cleveland, state of Ohio, USA) scanners were used as the scanning machine. Patients were scanned at the end of inspiration during a single breath hold in the supine position. CT settings were as follows: tube voltage, 120 kVp; average tube current, 250 mA; pitch, 0.984; and section thickness, 1 mm. Scans covered the region from the top of the thoracic cage to the level of bilateral adrenal glands, and patients underwent a contrast-enhanced CT scan (non-ionic contrast medium, 60–80 mL). All imaging data were reconstructed using the standard algorithm and viewed with both lung window (window width, 1,500 HU; window level, − 500 HU) and mediastinal window (window width, 350 HU; window level, 50 HU).

Image analysis

All post-processed images were interpreted retrospectively and independently by two experienced thoracic radiologists (HY and YNC) with 10 and 30 years of experience in chest imaging. The observers were blinded to the identities and clinical data of the patients. For all disagreements between the two observers on CT findings, the decisions were then reached by consensus. The location, shape, size, margin, interface, internal features, adjacent structures and CT attenuation values of the lesion were assessed. The definitions and scoring rules of morphological features are described in Table S1 .

CT, MRI, or PET/CT imaging was performed for the post-treatment disease status evaluation, and patients were evaluated once every six months within the first two years and then annually thereafter unless a specific clinical event emerged. The primary endpoint was DFS, which was defined from the date of initial histological diagnosis to the date of the first recorded evidence of clinical recurrence or distant metastasis as confirmed by histological evidence or death by any related causes. The secondary endpoint was CSS, calculated from the initial histological diagnosis to the date of death resulting from the progression of lung cancer (local and/or distant). The patient’s medical records and a telephone consultation were used for follow-up.

Statistical analysis

Statistical analysis was performed using SPSS software, version 26.0 (SPSS Inc., Chicago, IL, USA), R software, version 3.0.1 ( http://www.R-project.org ) and X-tile software, version 3.6.1 (Yale University School of Medicine, New Haven, Conn). The nomogram, decision curve analysis curves and calibration curves were plotted by the rms package in R. Survival curve was plotted using Kaplan–Meier survival analysis and compared using the log-rank test with the survminer and survival package in R. Continuous variables are summarized as means and standard deviations if the distribution was normal or as medians and interquartile range (IQR) if the distribution was not normal. Categorical variables are reported as frequencies and percentages. Two-tailed p  < 0.05 was considered statistically significant.

In this study, CT values were transformed into categorical variables and the optimal cut-off values were obtained by X-tile [ 20 ]. The repeatability for quantitative tumor size measurement was analyzed using the intraclass correlation coefficient (ICC). Reproducibility was defined as poor (ICC intraclass correlation coefficient < 0.75), moderate (ICC intraclass correlation coefficient = 0.75–0.90), or high (ICC intraclass correlation coefficient > 0.90) [ 21 ]. Interobserver agreement for qualitative variables of CT imaging was evaluated using Cohen’s kappa analysis. The κ value was interpreted as < 0.20, poor or slight agreement; 0.21–0.40, fair agreement; 0.41–0.60, moderate agreement; 0.61–0.80, good agreement; and 0.81–1.00, very good agreement [ 22 ].

Predictors for DFS and CSS were selected by Cox proportional hazards regression analysis. As PLEC is a rare tumor and the number of cases is not many and the events is less. In addition, CT findings of PLEC is a new insight and the prognostic analysis is exploring, therefore, those with a significant level of p  ≤ 0.05 in univariate analysis and statistically insignificant but clinically significant were entered into the multivariate Cox regression method with a backward stepwise selection procedure. A nomogram with endpoints of 3- and 5-year CSS and DFS were constructed based on the multivariate Cox regression analysis results, respectively. Harrell’s concordance index (C-index) was measured to quantify the discriminative performance of nomograms. All internal validations were performed using a bootstrapping method with 500 resamples. The calibration curves of nomogram were then drawn for the 3-year and 5-year CSS and DFS of the patients, which illustrated both survival probabilities predicted by nomogram and the observed probabilities. The decision curve analysis was conducted to estimate the clinical usefulness of the nomogram by quantifying the net benefits at different threshold probabilities. Finally, subjects were divided into high- and low-risk groups according to the median on the nomogram scores obtained from the constructed model. The Kaplan–Meier method and log-rank test were applied to calculate and compare risk group differences. Data between groups were compared using the independent t-test. Furthermore, categorical variables were presented with count (%) and were compared using the χ 2 test.

Patients baseline characteristics

The clinicopathological features of all PLEC patients are shown in Table  1 . In the primary PLEC cohort, the median follow-up time was 53.1 months (range: 1–157.4 months). The DFS and CSS of all PLEC patients are shown in Fig.  2 and Fig S1 a. The median DFS and CSS was not reached. The 1-, 3-, and 5-year CSS rates were 99.0, 88.6 and 76.1%, respectively. The 1-, 3-, and 5-year DFS rates were 88.4, 68.2, and 60.4%, respectively. The optimal cut-off value for CT attenuation was 37.8 HU which was obtained by X-tile. The ICC for the quantitative measurement of tumor size was 0.997 (95% confidence interval [CI]: 0.995–0.998; P  < 0.001). The interobserver reproducibility for qualitative CT imaging features was good or excellent (κ, 0.73–1.00). Table S2 showed a detailed description of the inter–reader agreement. The detailed CT features of the 113 patients are summarized in Table  2 .

KaplanMeier curve for DFS of total patients

Developing a clinicopathological and CT imaging-based nomogram to predict DFS and CSS

The results of the univariate and multivariate Cox analysis for predictive factors are presented in Table  3 and Table S3 . According to multivariate analysis results for DFS, a total of four variables were retained through backward stepwise selection; only the surgery resection ( p  = 0.001, HR = 0.24; 95% CI 0.11–0.55) and Hilar and/or mediastinal LAP ( p  = 0.007, HR = 3.27; 95% CI 1.39–7.70) being significant independent prognostic factors. According to multivariate analysis results for CSS, a total of six variables were retained, and the following variables showed significantly independent prognostic factors: age ( p  < 0.001, HR = 1.13; 95% CI 1.06–1.20), smoking status ( p  = 0.038, HR = 4.15; 95% CI 1.09–15.88), surgery resection ( p  < 0.001, HR = 0.05; 95% CI 0.01–0.19), tumor site in lobe ( p  = 0.014, HR = 0.29; 95% CI 0.11–0.78), hilar and/or mediastinal LAP ( p  = 0.038, HR = 4.49; 95% CI 1.09–18.53) and necrosis ( p  = 0.011, HR = 3.96; 95% CI 1.37–11.50). The HRs and 95% CIs for the multivariate Cox regression analysis for remaining DFS and CSS risk factors are shown as forest plots in Fig.  3 a and Fig. S1 b. Consequently, the nomograms for predicting the probability of 3-and 5-year DFS and CSS of all primary PLECs were developed using the risk factors combined with clinical and CT Imaging features (Fig.  3 b and Fig. S1 c). To use the nomogram, a vertical line needs to be delineated to the point raw to assign point values for each factor, and the total points are calculated as the sum of the risk points of all risk factors.

The forest plot of factors obtained through multivariate COX regression analysis for DFS (a) ; The nomogram established for prediction of DFS (b)

The discrimination, net benefit and predictive capacity of the nomogram

The C-indexes of the nomograms for DFS and CSS prediction in the dataset were 0.777 (95% CI: 0.703–0.851) and 0.904 (95% CI: 0.847–0.961), respectively. The performance of nomogram for clinical prediction was evaluated using the area under the receiver-operating characteristic (ROC) curve (AUC) (Fig.  4 a and Fig. S1 d), the 3- and 5-year AUC for DFS were 0.820 and 0.901, respectively, and those for CSS were 0.941 and 0.922, respectively. Moreover, time-dependent C-index analysis also showed that the nomograms exhibited good prognostic accuracy in clinical outcome prediction for DFS or CSS. A similar result was also observed in internal validation using a bootstrap resampling method (red lines) (Fig.  4 b and Fig. S1 e). The calibration plots of the prognostic nomograms in predicting 3- and 5-year DFS and CSS demonstrated good coincidences between the estimated risk and observed risk (Fig.  5 a and Fig. S1 f). The decision curve analysis for 3-and 5-year DFS and CSS showed that the combined nomogram had a higher overall net benefit than each clinical and CT imaging factor across the majority of the range of reasonable threshold probabilities (Fig.  5 b,c and Fig. S1 g,h).

Area under the curves at 3-year and 5-year were calculated to assess the prognostic accuracy for DFS (a) ; Timedependent Cindex of nomogram of all PLEC patient (blue lines) and internally validated using a bootstrap resampling method (red lines) for DFS (b)

Calibration curves for 3, 5year DFS (a) of nomogram predictions; Decision curve analysis of nomogram for 3year DFS (b) and 5year DFS (c) of PLEC patients. The red line is the net benefit of a strategy of treating all people; the brown line is the net benefit of treating no people. The yaxis indicates the overall net benefit, which is calculated by summing the benefits (true-positive results) and subtracting the harms (false-positive results), weighting the latter by a factor related to the relative harm of undetected cancer compared with the harm of unnecessary treatment

Risk stratification for PLEC patients

To assess whether the primary PLEC patients could be effectively separated into two proposed risk groups based on the nomograms, we calculated each patient’s total point and used the median to determine the optimal cut-off value. Patients with nomogram scores less than or equal to the median were classified as low-risk groups, and those with scores greater than the median were classified as high-risk groups. According to the range of total points, the Kaplan- Meier curves highlighted the appropriateness of distinguishing the patients’ survival for DFS and CSS in all the subgroups. The groups were obtained considering the total point distribution of our cohort. Compared with the high-risk group (red lines), group low-risk (blue lines) represent patients with better prognoses (Fig.  6 and Fig. S1 i). In order to explore individual factor comparisons within the clinical, pathologic, and chest CT factors between the high-risk and low-risk groups, we conducted a statistical comparison of various risk factors for patients with different risks, and the relevant results are shown in Table S4 , 5 .

KaplanMeier curve for DFS based on the nomogram prediction

Discussions

In our cohort, it was found that female patients and non-smokers accounted for the majority. Most patients were found during physical examinations, while a few had symptoms such as cough with or without blood-tinged sputum, similar to other NSCLCs without specificity [ 23 , 24 ]. No common mutation-driving genes in lung cancer were observed in our study. The above characteristics are consistent with the results reported in previous studies [ 2 , 3 , 18 ]. In addition, we restaged 113 PLEC patients in this cohort according to the 8th edition of the TNM staging system. The results showed that nearly half of the PLEC patients have a higher TNM stage (III + IV, 45.2%) at initial diagnosis, indicating that surgical resection is no longer feasible for treatment and requires multidisciplinary collaborative treatment.

Routine initial and follow-up examinations of lung lesions mainly rely on CT scans in clinical practice. Therefore, we evaluated the morphological CT manifestations of 113 patients with primary PLEC before treatment. The results showed that the median maximum diameter on CT imaging was 3.4 cm (IQR, 2–4.7 cm), and the average CT value on plain CT scan was 37.3 ± 10.5 HU. This indicates that PLEC often presents as large, soft tissue-dense masses on CT. Tumors are mostly located in the right lobe of the lung and are more common in peripheral types. However, few studies have reported that PELC mainly manifested as the central type of lung cancer [ 14 , 15 ]; it may be related to the small number of included cases.

Further CT imaging analysis showed that most PLECs exhibit solitary, well-defined solid nodules or masses, with lobulation sign more common, spiculation sign less common, and bronchogram cut-off more common. These characteristics are consistent with previous research results [ 14 , 15 , 25 ]. Moreover, the hilar and/or mediastinal LAP was more common in this cohort (54/113, 47.8%), indicating that primary PLEC is prone to lymph node metastasis. With a summary of these CT scanning characteristics, we attempted to integrate the clinical, pathological, and CT imaging features of all PLEC patients in the cohort. We conducted long-term follow-ups to discover more potential indicators for predicting survival risk.

Based on univariate and multivariate analysis for DFS and CSS, PLEC patients who did not receive surgery had a worse CSS and DFS because patients who have not undergone surgery are often in the advanced stage of TNM staging. On the multivariate analysis, hilar and/or mediastinal LAP was an independent prognostic factor for DFS and CSS. Previous studies also reported that nodal stage in the TNM system and lymph node involvement were independent prognostic factors for post-operative recurrence-free survival (RFS) in stage I-IIIa PLEC patients [ 26 ]. Our findings suggest that as a non-invasive examination method, pre-treatment hilar and/or mediastinal LAP on CT images in stage I-IV PLEC patients can provide an independent value for predicting survival outcomes. On the multivariate analysis for CSS, we found that age, smoking history, tumor site in the lobe, and necrosis signs were independent prognostic factors. Older PLEC patients and those with a history of smoking have a higher risk of death. A previous study found that PLEC patients with lesions in the left lobe of the lung seemed to have a poorer DFS in univariate analysis ( p  = 0.051), but they only included 30 cases of PELC [ 17 ]. Our study expanded the size of the study cohort and covariates, further demonstrating that the location of tumors in PLEC patients was an independent prognostic factor for CSS, indicating that patients with tumors in the left lung lobe have a higher risk of survival. This may be due to the lack or difficulty in 4 L lymph node dissection during routine surgical resection in patients with left lung cancer, resulting in a poorer prognosis compared to right lung cancer patients [ 27 ]. It is worth noting that female lung cancer patients often have better prognosis than males [ 28 ], while in the univariate analysis of this study, the prognosis of females was worse than that of males. We consider this may be due to the small number of included cases. In particular, age and smoking history were not significant in univariate analysis in this cohort ( p  = 0.148, 0.546, respectively) but became independent prognostic factors for CSS when included in multivariate analysis. This fully indicates that age and smoking history, once combined with other prognostic factors, have an impact on the prognosis of PLEC patients.

Furthermore, patients with necrosis on CT images had poorer CSS; this might because necrosis often occurs in large tumors with insufficient blood supply, while larger tumors have higher T staging and poorer prognosis. These conclusions may help clinicians understand the relationship between CT findings and patient survival in PLEC patients. In addition, we also found that symptomatic patients with elevated CYFRA21-1, irregularity shape on CT images, CT values (<37.8 HU as ref.) and patients with pleural and/or pericardial effusion had worse prognosis for both DFS and CSS on univariate analysis ( p <0.05), but not significant on multivariate analysis. This suggests that these variables may potentially correlate with the prognosis of PLEC patients. Especially in this cohort, up to 37.2% of PLEC patients had elevated levels of CYFRA21-1, which had been proven to be highly expressed in SCCs [ 29 ], indirectly demonstrating the necessity for primary PLEC to be classified as a subtype of lung SCCs.

Based on the Cox multivariate regression analysis results, we developed nomograms model that included multiple clinical and CT imaging prognostic factors to predict DFS and CSS in PLEC patients. Our nomograms showed the C-indexes of the overall dataset were higher than 0.7 and AUCs greater than 0.8 under the 3-year and 5-year ROC curves, indicating that the nomograms have an excellent discrimination performance for predicting clinical outcomes. The results of time-dependent C-index analysis further showed that this combined nomogram still had good predictive ability after undergoing 500 resamples of internal bootstrap validation. Moreover, the 3-year and 5-year decision curves and calibration plots for CSS and DFS showed that the nomograms we developed had strong prediction accuracy and overall net benefits and could evaluate clinical relevance without additional validation data in traditional decision analysis methods [ 30 ]. In addition, this nomogram can successfully classify PLEC patients into high and low-risk subgroups. Compared to the low-risk group, the high-risk group had the worst prognosis ( p < 0.001). In summary, our nomogram, which combines pre-treatment CT imaging and clinicopathological features, has great potential in clinical application for predicting the prognosis of PLEC patients and may assist clinicians in the decision-making process, allowing patients to obtain more benefits.

However, our research still has some limitations. Firstly, our research findings are based on a retrospective design; therefore, this study cannot exclude all potential inherent biases. Secondly, our data were obtained from a single cancer center, and the sample size was relatively small, the prediction model of prognosis was sufficient for DFS but for CSS. Finally, we did not find enough samples for external validation.

In conclusion, we first studied the relationship between CT imaging features and the prognosis of primary PLEC patients, and the identified CT imaging features may serve as biomarkers for prognostic risk stratification in PLEC patients. At the same time, we have developed new nomograms that combine clinicopathological and CT imaging features for individualized survival risk assessment of primary PLEC patients. Before conducting multicenter studies with larger samples in future, these nomograms were developed for simple usage and readily available prognostic tools may have potential value in promoting treatment decision-making and individualized prognosis prediction more effectively in clinical practice.

Data availability

Any reasonable requests for access to available data underlying the results reported in this article will be considered. Such proposals should be submitted to the corresponding author.

Abbreviations

• Computed tomography

Pulmonary lymphoepithelial carcinoma

Disease-free survival

Cancer-specific survival

Concordance index

Cytokeratin fragment antigen 21 − 1

EBV-encoded small non-polyadenylated RNAs

Epidermal growth factor receptor

Anaplastic lymphoma kinase

Kirsten rat sarcoma viral oncogene

Standard deviation

Interquartile ranges

Right upper lobe

Right middle lobe

Right lower lobe

Left upper lobe

Left lower lobe

Lymphadenopathy

Hazard ratio

Confidence interval

Area under the curve

Hu Y, Ren S, Liu Y, et al. Pulmonary lymphoepithelioma-like carcinoma: a mini-review. Onco Targets Ther. 2020;13(undefined):3921–9.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Liang Y, Wang L, Zhu Y, et al. Primary pulmonary lymphoepithelioma-like carcinoma: fifty-two patients with long-term follow-up. Cancer. 2012;118(19):4748–58. 10.10 02/cncr.274.52.

Article   CAS   PubMed   Google Scholar  

Qin Y, Gao G, Xie X Clinical features and prognosis of pulmonary lymphoepithelioma-like carcinoma: summary of eighty-five cases. Clin Lung Cancer., 2019;20(3): e329?e337

Bégin LR, Eskandari J, Joncas J et al. Epstein-Barr virus related lymphoepithelioma-like carcinoma of lung. J Surg Oncol, 1987, 36(4): 280–283.

He J, Shen J, Pan H, et al. Pulmonary lymphoepithelioma-like carcinoma: a surveillance, epidemiology, and end results database analysis. J Thorac Dis. 2015;7(12):2330–8.

PubMed   PubMed Central   Google Scholar  

Travis WD, Brambilla E, Muller-Hermelink HK, et al. Pathology and Genetics of tumors of the lung, Pleura, Thymus and heart. Volume 9. Lyon: IARC; 2004. pp. 457–65. 50.

Google Scholar  

Travis WD, Brambilla E, Burke AP, Marx A, Nicholson AG. Introduction to the 2015 World Health Organization Classification of Tumors of the lung, Pleura, Thymus, and heart. J Thorac Oncol. 2015;10(9):1240–2.

Article   PubMed   Google Scholar  

Tsao MS, Nicholson AG, Maleszewski JJ, Marx A, Travis WD. Introduction to 2021 WHO classification of thoracic tumors. J Thorac Oncol. 2022;17(1):e1–4.

Yang H, Lin Y, Liang Y. Treatment of Lung Carcinosarcoma and other Rare histologic subtypes of non-small cell Lung Cancer. Curr Treat Options Oncol. 2017;18(9):54. Published 2017 Aug 10.

Ettinger DS, Wood DE, Aisner DL, et al. NCCN guidelines Insights: Non-small Cell Lung Cancer, Version 2.2021. J Natl Compr Canc Netw. 2021;19(3):254–66. Published 2021 Mar 2.

Chen B, Zhang Y, Dai S, et al. Molecular characteristics of primary pulmonary lymphoepithelioma-like carcinoma based on integrated genomic analyses. Signal Transduct Target Ther. 2021;6(1):6. Published 2021 Jan 8.

Ball L, Vercesi V, Costantino F, Chandrapatham K, Pelosi P. Lung imaging: how to get better look inside the lung. Ann Transl Med. 2017;5(14):294.

Article   PubMed   PubMed Central   Google Scholar  

van Laar M, van Amsterdam WAC, van Lindert ASR, de Jong PA, Verhoeff JJC. Prognostic factors for overall survival of stage III non-small cell lung cancer patients on computed tomography: a systematic review and meta-analysis. Radiother Oncol. 2020;151:152–75.

Ooi GC, Ho JC, Khong PL, Wong MP, Lam WK, Tsang KW. Computed tomography characteristics of advanced primary pulmonary lymphoepithelioma-like carcinoma. Eur Radiol. 2003;13(3):522–6.

Ma H, Wu Y, Lin Y, Cai Q, Ma G, Liang Y. Computed tomography characteristics of primary pulmonary lymphoepithelioma-like carcinoma in 41 patients. Eur J Radiol. 2013;82(8):1343–6.

Chen B, Chen X, Zhou P, et al. Primary pulmonary lymphoepithelioma-like carcinoma: a rare type of lung cancer with a favorable outcome in comparison to squamous carcinoma. Respir Res. 2019;20(1):262. Published 2019 Nov 21.

Shen Y, Hu F, Zhang B, Li C, Zhang X, Han B. Clinicopathological characteristics with EGFR, ALK, ROS1 genetic alternation and prognostic analysis of primary lymphoepithelioma-like carcinoma. Transl Cancer Res. 2019;8(6):2350–6.

Jiang RR, Feng XL, Zhu WT, et al. A rare subtype of non-small cell lung Cancer: report of 159 Resected Pathological Stage I-IIIA Pulmonary Lymphoepithelioma-Like Carcinoma cases. Front Surg. 2021;8:757085. Published 2021 Oct 27.

Detterbeck FC, Boffa DJ, Kim AW, Tanoue LT. The Eighth Edition Lung Cancer Stage classification. Chest. 2017;151(1):193–203.

Camp RL, Dolled-Filhart M, Rimm DL. X-tile: a new bio-informatics tool for biomarker assessment and outcome-based cutpoint optimization. Clin Cancer Res. 2004;10(21):7252–9.

McGraw KO, Wong SP. Forming inferences about some intraclass correlation coefficients. Psychol Meth. 1996;1(1):30–46.

Article   Google Scholar  

Yin WH, Lu B, Li N, Han L, Hou ZH, Wu RZ, Wu YJ, Niu HX, Jiang SL, Krazinski AW, Ebersberger U, Meinel FG, Schoepf UJ. Iterative reconstruction to preserve image quality and diagnostic accuracy at reduced radiation dose in coronary CT angiography: an intraindividual comparison, JACC Cardiovasc. Imag. 2013;6(12):1239–49.

Tay CK, Chua YC, Takano A, et al. Primary pulmonary lymphoepithelioma-like carcinoma in Singapore. Ann Thorac Med. 2018;13(1):30–5.

Su TP, Ho KC, Wang CW, et al. Prognostic value and clinical impact of pre-treatment FDG PET in Pulmonary Lymphoepithelioma-Like Carcinoma. Clin Nucl Med. 2019;44(2):e68–75.

Lei Y, Zhou J, Liu J, et al. The CT and PET/CT findings in primary pulmonary lymphoepithelioma-like carcinoma with pathological correlation: a study of 215 cases. Clin Radiol. 2022;77(3):e201–7.

Lin Z, Situ D, Chang X, et al. Surgical treatment for primary pulmonary lymphoepithelioma-like carcinoma. Interact Cardiovasc Thorac Surg. 2016;23(1):41–6.

Wang YN, Yao S, Wang CL, et al. Clinical significance of 4L Lymph Node Dissection in Left Lung Cancer. J Clin Oncol. 2018;36(29):2935–42.

Yu XQ, Yap ML, Cheng ES, et al. Evaluating prognostic factors for sex differences in Lung Cancer Survival: findings from a large Australian cohort. J Thorac Oncol. 2022;17(5):688–99.

Park SY, Lee JG, Kim J, Park Y, Lee SK, Bae MK, Lee CY, Kim DJ, Chung KY. Preoperative serum CYFRA 21 – 1 level as a prognostic factor in surgically treated adenocarcinoma of lung. Lung Cancer. 2013;79(2):156–60.

Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating pre-diction models. Med Decis Mak. 2006;26(6):565–74.

Download references

Acknowledgements

This work was financially supported by National Natural Science Foundation of China (Grant No. 82071873 and 81871353), Shanghai Municipal Commission of Science and Technology (Grant No. 22Y11911100), Shanghai Pujiang Program (Grant No. 22PJD069) and Shanghai Health Research Foundation for Talents (Grant No. 2022YQ060).

Author information

Authors and affiliations.

Department of Radiology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, No. 241 Huai-Hai West Road, Shanghai, 200030, P. R. China

Kai Nie, Lin Zhu, Yinan Chen & Hong Yu

Department of Pharmacology, University of Oxford, Oxford, OX1 3QT, UK

Yuxuan Zhang & John Parrington

You can also search for this author in PubMed   Google Scholar

Contributions

KN were involved in the literature search, figures, study design, data collection, data analysis, and writing. LZ, YXZ, and YNC were involved in literature search and data collection. J.P and HY were involved in study design and article review. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Hong Yu .

Ethics declarations

Ethics approval and consent to participate.

This study was approved by the Ethics Committee of Shanghai Chest Hospital. Informed consent was waived because data were deidentified.

Consent for publication

Not applicable.

Competing interests

All remaining authors have declared no conflicts of interest.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

12931_2024_2767_MOESM1_ESM.tif

Supplementary Material 1. Fig. S1 Kaplan Meier curve for CSS of total patients (a), the forest plot of factors obtained through multivariate COX regression analysis for CSS (b), the nomogram established for prediction of CSS (c), area under the curves at 3-year and 5-year were calculated to assess the prognostic accuracy for CSS (d), time dependent C index of nomogram of all PLEC patient (blue lines) and internally validated using a bootstrap resampling method (red lines) for CSS (e), calibration curves for 3 , 5 year CSS of nomogram predictions (f), decision curve analysis of nomogram for 3 year CSS (g) and 5 year CSS (h) of PLEC patients and Kaplan Meier curve for CSS based on the nomogram prediction (i).

Supplementary Material 2

Rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Nie, K., Zhu, L., Zhang, Y. et al. Development of a nomogram based on the clinicopathological and CT features to predict the survival of primary pulmonary lymphoepithelial carcinoma patients. Respir Res 25 , 144 (2024). https://doi.org/10.1186/s12931-024-02767-5

Download citation

Received : 23 August 2023

Accepted : 12 March 2024

Published : 29 March 2024

DOI : https://doi.org/10.1186/s12931-024-02767-5

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Lung cancer
• Prognostic factors

Respiratory Research

ISSN: 1465-993X

• General enquiries: [email protected]

New Advanced Quantum Science Institute Will Bridge Basic Research and Applied Science

AUSTIN, Texas — The University of Texas at Austin is boosting its commitment to research and education in quantum science and engineering by establishing the Texas Quantum Institute . This expanded investment reflects the University’s recognition of the vast potential that quantum science and engineering hold to benefit society through new approaches to computing, energy-efficient electronics, secure communications, ultrasensitive sensors for medical diagnostics, semiconductor quality control and observing climate processes from space.

“Some of the most exciting technological advances of the next few decades will come from quantum research,” said Dan Jaffe, vice president for research. “Thanks to our already-thriving quantum ecosystem on campus and Austin’s status as a vibrant incubator of innovative technologies, UT is the ideal place for world-changing quantum-related discoveries to be made that lead to much-needed applications for energy, medicine, the environment and computing.”

Quantum research delves into an area of science and engineering where peculiar phenomena still mysterious to many physicists meet vast potential for new advances. These unusual phenomena occur at vanishingly tiny and mindbogglingly rapid scales, made possible with new materials and highly advanced equipment.

The new institute will bring together more than 30 researchers and provide postdoctoral fellowships, an interdisciplinary seed grant program, workshops, and construction of a new lab for advanced quantum and semiconductor measurements. The institute will be co-directed by Elaine Li , the Jack S. Josey Welch Foundation Science Chair and professor in the Department of Physics, and Xiuling Li , a Temple Foundation Endowed Professor in the Chandra Family Department of Electrical and Computer Engineering and a fellow of the Dow Professorship in the Department of Chemistry.

“Here at UT, we have a strong track record in designing algorithms for quantum computers, developing materials with unprecedented properties, inventing advanced measurement tools and building quantum systems,” Elaine Li said. “The new institute will enable us to further develop these areas and cultivate collaborations with other academic institutes, as well as industry and national labs.”

With dozens of core research faculty members who study related topics, UT has already earned an international reputation for groundbreaking quantum advances. These include launching the subfield of “Twistronics ,” developing tests for quantum supremacy in computing, and inventing a new imaging technique called microwave impedance microscopy .

“By uniting researchers under a campuswide umbrella organization, the institute will enhance the visibility and impact of quantum research both within the academic community and beyond,” Xiuling Li said. “I am excited that with the increased visibility, we can attract top talent, foster collaborations with industry partners, and ultimately accelerate the translation of quantum discoveries into real-world applications.”

World-class infrastructure — such as the Texas Advanced Computing Center , home of the fastest academic supercomputer in the U.S.; the Microelectronics Research Center , the flagship semiconductor materials and devices research center; the Texas Materials Institute , a premier hub for materials research; and the Texas Institute for Electronics , which develops innovative semiconductor solutions through advanced packaging — will enable UT to hit the ground running in its expanded quantum research initiative.

“The University of Texas at Austin’s launch of the Texas Quantum Institute is a landmark moment for the University, the quantum industry and the state of Texas,” said Scott Faris, CEO of Infleqtion , a global quantum technologies company already partnering with UT on quantum manufacturing . “This bold initiative will position Texas as a leader in the development of quantum technology and the quantum economy. We are incredibly excited to partner with UT Austin on groundbreaking research and moving quantum to the forefront of the technology industry.”

Unveiled during what the University has declared the Year of AI, the new institute’s faculty members are not only physicists, chemists and chemical engineers but also leading computer scientists and electrical and computer engineers, positioned to forge partnerships with industry and national labs, drive quantum innovations through interdisciplinary collaborations, and unlock the potential of future quantum AI systems for the betterment of society.

Explore Latest Articles

Apr 05, 2024

A UTotal Solar Eclipse

Visualization of Flood, Disease and Climate Modeling through the Eclipse Path of Texas and Beyond

This UT scientist made his own line of solar eclipse glasses

Poverty and Child Neglect: How Did We Get It Wrong?

Poverty and child neglect are highly correlated and often impact families simultaneously; but poverty does not cause neglect.

Prevention is a hot topic in child welfare policy conversations, and for good reason. Preventing child maltreatment helps families thrive and reduces the frequency of tragic outcomes. The Family First Prevention Services Act of 2018 propelled prevention efforts forward and launched a national conversation about keeping children out of foster care except when absolutely necessary.

The State of Child Welfare

Child maltreatment rates have declined dramatically over the past 30 years. Between 1992 and 2019 , physical abuse declined by 56% and sexual abuse declined by 62%. Public policy, awareness programs and decreased stigma associated with seeking help contributed to these changes.

By contrast, rates of child neglect remain high. Neglect is the most common type of child maltreatment in the U.S. Until recently, federal child welfare policies primarily responded to maltreatment without much attention to addressing risk factors. The outcome was to inadvertently punish struggling families more than help them.

More than 480,000 children were impacted by neglect in 2020 , and it was a primary or contributing factor for 64% of children entering foster care the same year. By comparison, 13% of children entering foster care in 2020 were victims of physical abuse and 4% were victims of sexual abuse.

What Is Neglect?

Most experts agree child neglect occurs when the needs of a child are unmet by their primary caregivers. Inadequate clothing, food, shelter, medical and emotional care, along with unsafe environments, exposure to substance abuse and lack of supervision, are often included in definitions of neglect. Even with these definitions, pinpointing cases of neglect can be challenging. Policymakers and researchers are rethinking historical definitions, which often are intertwined with poverty . States have authority to define exactly what neglect means through legislation, and there is considerable variation .

Research shows the presence of one or more child maltreatment risk factors , such as poverty, can make a child more vulnerable to experiencing neglect. While risk factors do not cause maltreatment, buffering or reducing them is a promising prevention pathway .

Poverty Is a Risk Factor for Neglect

Poverty, much like neglect, is a complex problem. Census data show that rates of child poverty vary widely among the states, ranging from 8% to nearly 28% in 2021 . Childhood poverty is associated with a range of negative outcomes across the lifespan, such as poor health, lower educational attainment and more risk-taking behaviors.

Poverty and child neglect are highly correlated and often impact families simultaneously; but poverty does not cause neglect. Experts say it’s more complicated than that. Poverty produces material hardships for families. Such hardships often result in families experiencing toxic stress , which can impede children’s cognitive development and parents’ capacity to meet the needs of their children. Incapacity to provide is not the same as an unwillingness to provide. This distinction is at the crux of the challenge policymakers face to disentangle poverty from neglect.

Want to Go Deeper? The report Policy Levers for Preventing Child Maltreatment outlines strategies to reduce child abuse and neglect. NCSL offers a child welfare fellows program focused on preventing child maltreatment and reforming child welfare systems.

Poverty is experienced at higher rates by people of color and people living in rural areas , which can contribute to racial disparities within the child welfare system. Policies like redlining and the discriminatory use of home lending provisions in the GI Bill, for example, have had lasting generational effects, shaping the landscape of poverty across the country. While all children encounter  teachers, doctors and others required to report maltreatment, higher rates of poverty in a community are often associated with more reports of abuse . This doesn’t necessarily lead to more confirmed cases of child maltreatment, raising questions about whether over-surveillance of poor families contributes to disproportionate child welfare system involvement.

Some states have reworked their definition of neglect to recognize parents’ capacity or clarify that conditions of poverty alone do not constitute neglect. Iowa ( H 2507; 2022 ) defined neglect as “the failure on the part of a person responsible for the care of a child to provide for adequate food, shelter, clothing, medical or mental health treatment, supervision, or other care necessary for the child’s health and welfare when financially able to do so or when offered financial or other reasonable means to do so.”

Updating mandatory reporting and training policies to better respond to complex situations and relationships, such as those involving poverty and neglect, is another option. Colorado (H 1240; 2022 ) attempted to make mandatory reporting systems fairer, given evidence of disproportionate impacts of reporting systems on under-resourced communities. At least eight states enacted legislation in 2022 addressing mandatory reporting.

Evidence-Based Policy Options

Some policies appear to be particularly effective at reducing risk factors associated with neglect; examples include child care subsidies , affordable housing , home visiting and enhanced primary care . Preventing child maltreatment almost certainly requires diverse and integrated strategies. Nebraska ( L 1173; 2022 ) established a work group and called for an integrated, evidence-informed approach to transform its child welfare system to “support the well-being, permanency, and safety of children and families in Nebraska’s communities.”

Former Colorado Rep. Tonya Van Beber (R) and Rep. Jason Hughes (D) of Louisiana toured the Warren Village program in Denver as part of NCSL fellows programs last year. Warren Village provides resources, tools and a supportive environment for single parents with children to build skills and create the lives they want for their families. “When we see a public-private partnership of this quality that has actual outcomes and evidence-based processes that literally show us this does work, it was a wonderful thing to see,” Van Beber said at an NCSL Town Hall after the tour.

Hughes said the Warren Village tour reminded him that “poverty has to be addressed in a holistic way.” As states incorporate more comprehensive strategies to prevent child maltreatment, addressing neglect is especially pertinent.

Jill Yordy is a senior policy specialist in NCSL’s Children and Families Program.

This publication was made possible in collaboration with Casey Family Programs, whose mission is to provide, improve and ultimately prevent the need for foster care. The findings and conclusions presented in this report are those of the author alone, and do not necessarily reflect the opinions of Casey Family Programs.

Contact NCSL

For more information on this topic, use this form to reach NCSL staff.

• What is your role? Legislator Legislative Staff Other
• Admin Email

China Opposes US Trade Barriers Report Listing It as 'Primary Concern'

China Opposes US Trade Barriers Report Listing It as 'Primary Concern'

BEIJING (Reuters) - China's commerce ministry said on Tuesday it firmly opposes a United States' report on foreign trade barriers, which it said "listed China as a country of primary concern".

The U.S. National Trade Estimate Report on Foreign Trade Barriers released on March 29 "did not provide any evidence to prove that China's relevant policies and practices violated WTO rules, but arbitrarily accused China of having so-called 'non-market' policies and practices and barriers in agricultural products and data policies", a ministry spokesperson said in a statement.

The U.S. should stop making "false accusations" against other countries, abide by WTO rules and maintain a fair and just international trade order, the spokesperson added.

(Reporting by Ethan Wang, Ella Cao and Ryan Woo; Editing by Andrew Heavens)

Copyright 2024 Thomson Reuters .

Photos You Should See

Join the Conversation

Tags: World Trade Organization , tariffs , United States , Asia , international trade , intellectual property

America 2024

Health News Bulletin

Stay informed on the latest news on health and COVID-19 from the editors at U.S. News & World Report.

Sign in to manage your newsletters »

Sign up to receive the latest updates from U.S News & World Report and our trusted partners and sponsors. By clicking submit, you are agreeing to our Terms and Conditions & Privacy Policy .

You May Also Like

The 10 worst presidents.

U.S. News Staff Feb. 23, 2024

Cartoons on President Donald Trump

Feb. 1, 2017, at 1:24 p.m.

Photos: Obama Behind the Scenes

April 8, 2022

Photos: Who Supports Joe Biden?

March 11, 2020

RFK Jr.’s Mixed-Up Messaging on Jan. 6

Susan Milligan April 5, 2024

EXPLAINER: Rare Human Case of Bird Flu

Cecelia Smith-Schoenwalder April 5, 2024

Friday’s Northeast Earthquake, Explained

Steven Ross Johnson April 5, 2024

The Dark Clouds Looming Over the Eclipse

Blowout: Jobs Gains Defy Expectations

Tim Smart April 5, 2024

‘Unity Ticket’ a No-Go for No Labels

Cecelia Smith-Schoenwalder April 4, 2024