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About Cancer Research

Cancer Research publishes impactful original studies, reviews, and opinion pieces of high significance to the broad cancer research community. Cancer Research seeks manuscripts that offer conceptual or technological advances leading to basic and translational insights into cancer biology. Manuscripts that focus on convergence science, the bridging of two or more distinct areas of cancer research, are of particular interest. The main scope of the journal is captured in its primary subsections:

Cancer Biology
Cancer Immunology
Cancer Metabolism and Molecular Mechanisms
Therapeutic Development and Chemical Biology
Translational Cancer Biology
Cancer Landscapes
Computational Cancer Biology and Technology
Convergence Science

General Criteria for Studies Considered by the Journal

Manuscripts containing findings that significantly move the field of cancer research forward.
A potentially generalizable, broadly impactful conclusion, or an incisive rationale that could interest a broad audience.
Results that have not been previously published in another tumor, cell line, or organoid model.
Studies that include a clearly written title and abstract that communicate the study's impact to non-experts.
Development or demonstration of a technological method that will greatly facilitate one or more areas of cancer research; such studies must demonstrate the potential of the approach by providing new biological insights to be considered.
Studies with a high level of rigor and reproducibility of the methodologic approach at the time of submission:
Multiple models
Inclusion of age/sex as a variable
Orthogonal approaches to support a hypothesis
Proper controls
Current techniques

Manuscript Submission

Cancer Research welcomes submissions of primary research, review and commentary article types as well as letters to the editor. For descriptions and length requirements of the article types available to submitting authors, see the journal’s Categories of Articles .

The AACR Journals all use a similar Editorial Process and adhere to the same overarching Editorial Policies , both of which are detailed in the Information for Authors . These instructions contain important guidelines on authorship, publishing ethics, availability of materials and data, and data analysis and reporting. Authors should be familiar with these instructions prior to submitting their work to the journal.

Manuscripts are stringently reviewed for high standards of scientific merit, and only those that report results of novel, timely, and broadly-significant research are accepted for publication.

Journal Metrics

Cancer Research is the second-most frequently cited cancer journal in the world. For detailed metrics about Cancer Research and the other AACR journals see AACR Journals Metrics .

Editors and Editorial Board

Editorial oversight of Cancer Research and decisions on manuscripts submitted to the journal are the responsibility of the Editorial Board with support from journal staff. See Editorial Board for more information.

Copyright, Permissions and Access

Material published in Cancer Research is covered and protected by copyright. An author can either formally transfer copyright to the AACR, and be granted considerable reuse rights, or can publish an article as open access under a Creative Commons license. The final typeset version of every published article is rendered freely accessible 12 months after publication. In addition, the AACR assists authors in satisfying major funder Open Access archiving mandates by depositing the accepted author version of their article in a designated public repository. For additional details about all these topics, see Copyright, Permissions and Access .

Publication Fees

To defray publication costs and to support other AACR programs, publication in Cancer Research involves the payment of a base publication fee and an additional fee for each display item. If no financial support exists, authors may apply for a waiver of the fixed publication fee at the time of submission. See Publication Fees for further details.

Journal Information

Cancer Research (CR) (Print ISSN: 0008-5472; Online ISSN: 1538-7445) is published twice a month, one volume/year, by the American Association for Cancer Research, Inc. (AACR).

Cancer Research is abstracted and/or indexed in BIOSIS Previews (R) Database, MEDLINE, Current Contents/Life Sciences, Current Contents/Clinical Medicine, Science Citation Index, Scopus, and Web of Science.

Back Issues and Single Issue Sales

Subject to availability, single or back issues of Cancer Research may be purchased for $60 per copy in the U.S. or $65 per copy outside the U.S. For more information, contact:

AACR Publications Sales & Marketing Department American Association for Cancer Research 615 Chestnut Street, 17th Floor Philadelphia, PA 19106-4404 Phone: (215) 440-9300; or Toll Free: (855) 744-4667 E-mail: [email protected]

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Home > Cancer Research Catalyst > Two Years of Cancer Research Communications: A Conversation with the Journal’s Editors-in-Chief

Two Years of Cancer Research Communications: A Conversation with the Journal’s Editors-in-Chief

In 2021, Lillian L. Siu, MD , and Elaine R. Mardis, PhD, FAACR , each received a call from AACR Chief Executive Officer Margaret Foti, PhD, MD (hc), asking if they’d be interested in serving as the inaugural co-editors-in-chief of Cancer Research Communications , the organization’s first open-access journal.

“I was, of course, flattered,” said Siu, who is an oncologist at the Princess Margaret Cancer Centre and a clinician-scientist at the University of Toronto. “I thought it made perfect sense for AACR to have an open access journal. Knowing that it would be alongside Elaine Mardis made it even more compelling, so I gladly agreed.”

Mardis also jumped at the opportunity.

“I’ve always had a strong commitment to open-access publishing, so I was really delighted to get the call asking about my interest and hearing that Lillian Siu, whom I’ve always held in very, very high regard, would also be invited to be a co-editor-in-chief,” said Mardis, who is co-executive director of the Institute for Genomic Medicine at Nationwide Children’s Hospital, a professor of pediatrics at The Ohio State University, and an AACR Past President.

Together, the pair have led Cancer Research Communications through its first two years of submissions, reviews, and publications, helping define the journal’s editorial ethos and place in the AACR portfolio of peer-reviewed journals. Under their leadership, the journal has published over 300 articles to date.

As Cancer Research Communications wrapped up its second year, Mardis and Siu offered their perspectives on the journal’s mission and top publications to date.

Photos of Dr. Elaine Mardis and Dr. Lillian Siu

How does Cancer Research Communications differ from other AACR journals and other cancer research journals in general?

Mardis: One clear area of distinction that we planned from the very beginning was the breadth of the journal. Cancer research encompasses multiple areas of expertise. It’s very interdisciplinary, so we wanted to capture that breadth in the content we publish. Beyond diverse research topics, we also have breadth in terms of the types of cancer research—everything from basic to clinical science plus correlative science coming out of clinical trials. It’s truly bench to bedside and back.

The other thing that distinguishes Cancer Research Communications from other journals of its type is that we have within our guidelines some unique aspects that I haven’t seen in other journals. For example, we’re interested in manuscripts that reproduce others’ results with different materials and experimental approaches.

Siu: I would say that in addition to the breadth of research we publish, another feature that sets us apart is that we’re interested in the kind of papers that do not necessarily go from beginning to end and address everything in a nice package. Perhaps they leave some questions for others to help fill in over time, but they have the scientific quality that is worthy of an AACR journal. We understand that it is not always possible to deliver a complete story in one manuscript.

Obviously, if a researcher thinks that additional experiments are achievable in a reasonable time and they’re ready to tackle them, then by all means, they should finish everything that they can and submit their study to a journal such as Cancer Discovery .

But if they think it would take a lot more time, resources, or infrastructure to tie up all the loose ends, and the results as they stand are interesting enough for others to be aware of and build upon, I think Cancer Research Communications would be a very good fit for it, assuming, of course, that the analyses and methods are sound.

Similarly, for negative studies or studies with small sample sizes, if the results answer a question that people have been asking repeatedly, we would consider publishing it. For these studies, the discussion section will be key for researchers to state the limitations and to put their findings into context for readers who are outside their field.

Can you highlight a few studies from the past two years that exemplify the journal’s niche?

Mardis: There are three studies that I think illustrate the breadth of inquiry that Cancer Research Communications supports, with the first uncovering basic features of tumor biology, the second having implications for clinical research, and the third using data science to understand clinical outcomes.

In the first study , researchers employed cutting-edge technologies, such as single-cell RNA-seq, CITE-seq, and mass cytometry, to examine the immune microenvironment in multiple myeloma. The novelty of their approach is that they looked at the intersectionality between all three types of data. This approach may be especially significant in multiple myeloma where we don’t fully understand how the immune microenvironment contributes to disease progression. This paper defined some of the markers in the immune microenvironment that were associated with rapid progression in multiple myeloma patients and also highlighted key differences between these three cutting-edge technologies in terms of how they “perceive” differences in gene expression between cells in a tumor.

Another study examined genomic heterogeneity across 42 different tissue and blood samples from a single patient with a metastatic pulmonary atypical carcinoid. The main finding was that genetic variants that were shared across different metastatic sites could be detected in circulating tumor DNA, but emerging variants were not always detectable. Even though this study examined samples from just one patient, the finding has important implications. If we want to utilize circulating tumor DNA to study cancer evolution or monitor patient outcomes, we must recognize that there’s a level of sensitivity that we will have to transcend before we can detect emerging variants, which are often the ones that we most want to identify.

The last paper I want to mention examined sex-specific differences in brain tumors. This was a paper looking at these very specific differences between male and female patients with TP53-mutated brain cancer. The researchers found differential gain of function activity across groups and illustrated with a nice set of data the importance of sex as a biological variable, which I think often gets overlooked.

Siu: I’ll also highlight the study Dr. Mardis mentioned that sequenced samples from a single patient with a metastatic pulmonary atypical carcinoid. While this study only examined one patient, the authors went above and beyond a simple case report to conduct a very in-depth examination with multiregional sampling to provide valuable insights into how tumors evolve and metastasize. I think that’s something that sets this study apart.

In another paper that I would say exemplifies our niche, researchers performed a comprehensive immune profiling of localized leukoplakia (precancer changes in the oral cavity) with the goal of understanding the immune landscape of these lesions. We don’t have a lot of data in this area because patients with these precancer lesions are typically seen by dentists, rather than in cancer centers.

These types of data may help us understand how these lesions progress to cancer, uncover how to prevent this progression, or determine if the resulting tumors might be susceptible to immune checkpoint inhibition, for example. Moreover, this study sets the stage for others to perform similar types of analyses for precancer lesions at other sites, not just in the oral cavity.

Another study I would highlight examined the effect of combining an EXO1 inhibitor, which is a nuclear transport inhibitor, with a KRAS G12C inhibitor in KRAS G12C-mutated tumor models. Responses to clinically approved KRAS G12C inhibitors tend to be fairly short-lived, and there’s a lot of interest in learning how to deepen responses. Having preclinical models to interrogate different combinations will help researchers discover ways to prolong the efficacy of these drugs in the clinic. Manuscripts reporting on preclinical models that explore and inform clinical evaluations would fit the types of articles we are looking for, especially if new and improved models are used to address a research question that is not addressable with current existent models.

What is your vision for the next two years—and beyond—of Cancer Research Communications ?

Mardis: I would like to see us review and publish more research in the field of data science and how it impacts cancer research and clinical trials. Another area in which I’d love to see us grow is novel experimental models. There’s been a lot of skepticism of late around mouse models in particular and whether they’re reflective of human cancers. In response to that, there have been a number of efforts—some of which I’m aware of, many more of which I’m probably not—around patient-derived model systems.

We need to think outside the box to create model systems that don’t require years of careful breeding and genetic engineering to produce. I think organoid systems and tumoroid systems have started to fill that void, but we need to keep pushing the envelope. There has also been a lot of interest around tissue slice cultures to examine tumor growth kinetics and genetics in tandem with therapeutic responses. I would like to see us review and publish more of these studies.

Siu: Well, first and foremost, we want more people to submit their papers to us, and we want more researchers to serve as reviewers. We have published over 300 papers in two years, which I think is impressive for a new journal, but we would like to grow even more.

While we are proud to cover a range of article types, at the same time, I think it would be good for us to be remembered for something that sets us apart from other journals out there. In particular, I’d like to us be known as the journal that publishes studies that make perhaps incremental changes but changes that are important nonetheless because they lead to more questions and stimulate other areas of research.

I think that is an important goal for us to achieve—to be a catalyst for the next big discovery.

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Research studies answer key questions about how cancer works in the body. They also show what tests and treatments may work best. To help improve cancer care, scientists share the results of their studies with other scientists and doctors. The main way they do so is by publishing them in medical journals.

Scientists may publish their own cancer research, which can be done in a laboratory or with volunteers in a clinic. Studies that involve people are known as clinical trials . Or they may write a review article. A review article looks at all of the published research on a certain topic.

Most cancer research studies are written for scientists and medical doctors. But people with cancer may read them to learn about their disease and treatment options. Research studies use scientific terms that some people may not know. Talk with your health care team if you have questions about research you find.

How is cancer research published?

Different medical journals often focus on different topics, such as clinical cancer research. These journals present new scientific findings and the research methods used.

Most journals publish in print and online. This includes the American Society of Clinical Oncology journals . Journals usually publish on a specific schedule, such as weekly, biweekly, monthly, or quarterly.

For articles published in scientific journals, the phrase “peer reviewed" means that the article has undergone a process in which qualified experts have reviewed it and provided feedback to the authors to improve the scientific quality and integrity of the article. The reviewers were not part of the study. These experts decide whether the research data and results are reliable. Learn more about the importance of peer review in research quality .

How is a cancer research study formatted?

Most cancer research studies include background information, the researcher's methods, results, and the meaning of the findings. Studies published in many journals present this data in a certain format known as Introduction, Methods, Results, and Discussion (IMRAD).

The IMRAD format allows other scientists to do similar studies to see if there is the same result, a scientific principle called replication. The International Committee of Medical Journal Editors supports IMRAD. But some journals may use other names for the format's sections, which are described below.

Introduction. This section explains why a study was done. It also states the research question. For example, "Does this treatment help people with stage IV colon cancer live longer?"

Methods. This is where researchers describe how they answered the research question. To do this, they explain the study's design. This may include how, how much, and how often people in the study received treatment. The researchers also state what result they were measuring. For instance, this may be how long the participants lived without the cancer progressing ("progression-free survival") or if the tumors shrank. They also show how they studied the data.

Results. This section shares the main study findings. Tables and graphics may show the data in different ways. The results section also gives general information about study volunteers, such as the age range and sex. It explains why the volunteers were chosen and the type and stage of cancer they have.

Discussion. This section is also known as the conclusion. It describes what the results mean in relation to the study's purpose. It also looks at the importance of the results and how they may affect cancer research and care. For instance, the results may confirm or challenge earlier research.

What is a cancer research study abstract?

An abstract is a summary that is at the beginning of published cancer research studies. It shares the study's main data. This allows readers to quickly learn about the most important parts of the research. Researchers often share their abstracts at scientific meetings, sometimes even before they have been published in a journal.

How can I find cancer research studies?

There are many ways to find cancer research studies. One way is to visit a journal's website. Then you can use either the search function or the online archive to find a study. An archive stores older studies.

You can also use large, online databases that provide study abstracts. One popular database cancer researchers and doctors use is PubMed . PubMed is a service of the U.S. National Library of Medicine. Another online database you can use to search for studies in Google Scholar . These databases include millions of citations from a wide range of medical journals. A citation is a reference to a source that provides information. This includes the study title, author names, and journal title.

PubMed and Google Scholar can be hard to use because they include so many studies. You can make it easier by searching for a certain cancer topic. If you cannot find studies on that topic, try including more medical terms in your search. For example, try "renal cell carcinoma" instead of "kidney cancer." You can also include the word "review" along with the type of cancer to find review articles. Be as specific as you can about the topic you are interested in.

Abstracts can often be read online for free. However, sometimes you may not be able to read the full study if you do not subscribe to the journal that published it. Sometimes there may be a way to pay a one-time fee to read a study. For printed copies of medical journals, visit a local library or university.

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One in five people with cancer participate in medical research studies

by Fred Hutchinson Cancer Center

Researchers from Fred Hutchinson Cancer Center, the American Cancer Society Cancer Action Network and peer institutions released new findings in the Journal of Clinical Oncology showing that when all types of cancer research studies are considered, at least one in five people with cancer, or 21.9%, participate in some form of clinical research.

The study evaluated all categories of cancer studies, such as treatment trials, biorepository studies and quality of life studies—the first time an estimate of participation in all types of cancer studies has been reported. Moreover, enrollment in cancer treatment trials was 7.1%, a notably higher participation rate than previous estimates of 2%–3%.

The study also found that enrollment in treatment trials was over five-fold higher at National Cancer Institute-designated cancer centers than at community sites (21.6% versus 4.1%), reflecting the impact that NCI funding for staff and infrastructure has on an institution's ability to offer trials and recruit patients.

Using deidentified accreditation data provided by the Commission on Cancer, the study updated decades-old estimates for participation in cancer research.

This expanded analysis includes more than 70% of people diagnosed with cancer in the U.S. each year who received care at a variety of clinical settings, from community hospitals and academic medical centers to NCI-designated comprehensive cancer centers. Additionally, the study reflects the broad spectrum of cancer research including different study types and those sponsored by industry, government and other sources.

"As we work to increase participation in cancer research studies and make them more accessible to patients, we need an inclusive, accurate assessment of current participation to inform these policies," said Joseph Unger, Ph.D., MS, a health services researcher and biostatistician at Fred Hutch and lead author of the study.

"While we knew that patients play a significant role in advancing all types of cancer research, now we better understand just how commonly people are participating in all types of cancer studies today."

While previous estimates of participation in cancer research studies were derived solely from government-sponsored trials, the study authors used patient data from a diverse range of trial sponsors and care settings for this analysis. Importantly, the data included settings such as community hospitals, where a majority of U.S. cancer patients receive care.

"We know that most patients with cancer will participate in a clinical trial if given the chance, and the level of enrollment we see at NCI-designated cancer centers shows what participation can be when patients are offered trials," stated Mark Fleury, Ph.D., a policy principle at ACS CAN and senior author of the study.

"These findings emphasize the need to offer more patients in community settings the chance to participate and that will require an investment in these sites that currently isn't there."

People with cancer enrolled in many different types of clinical studies. The study found the following participation rates in each type of clinical study: biorepository (12.9%), treatment (7.1%), registry (7.3%), genetic (3.6%), quality-of-life (2.8%), diagnostic (2.5%) and economic studies (2.4%).

Expanding the types of cancer clinical studies in this analysis demonstrates that there are a variety of ways people choose to participate in cancer research beyond the previous assessments, which were based only on participation in treatment studies.

"Cancer clinical research, in all of its forms, simply cannot be conducted without the contributions of people with cancer," emphasized Dr. Unger.

"These contributions are much more extensive than was previously recognized. Cancer clinical research is a true partnership between those with cancer and those who study and treat cancer."

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Development of a nomogram to predict the prognosis of patients with secondary bone tumors in the intensive care unit: a retrospective analysis based on the MIMIC IV database

Open access
Published: 28 March 2024
Volume 150 , article number 164 , ( 2024 )

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Weikang Li 1 na1 ,
Jinliang Li 1 na1 &
Jinkui Cai 1

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The present study aimed to develop a nomogram to predict the prognosis of patients with secondary bone tumors in the intensive care unit to facilitate risk stratification and treatment planning.

We used the MIMIC IV 2.0 (the Medical Information Mart for Intensive Care IV) to retrieve patients with secondary bone tumors as a study cohort. To evaluate the predictive ability of each characteristic on patient mortality, stepwise Cox regression was used to screen variables, and the selected variables were included in the final Cox proportional hazard model. Finally, the performance of the model was tested using the decision curve, calibration curve, and receiver operating characteristic (ROC) curve.

A total of 1028 patients were enrolled after excluding cases with missing information. In the training cohort, albumin, APSIII (Acute Physiology Score III), chemotherapy, lactate, chloride, hepatic metastases, respiratory failure, SAPSII (Simplified Acute Physiology Score II), and total protein were identified as independent risk factors for patient death and then incorporated into the final model. The model showed good and robust prediction performance.

We developed a nomogram prognostic model for patients with secondary bone tumors in the intensive care unit, which provides effective survival prediction information.

Development and validation of risk prediction nomograms for acute respiratory failure in elderly patients with hip fracture

Yue Li & Bo Dong

A clinically applicable prediction model for the risk of in-hospital mortality in solid cancer patients admitted to intensive care units with sepsis

ChengYong Ma, GuoRui Sun, … Shuo Yang

Performance of three prognostic models in critically ill patients with cancer: a prospective study

Frank D. Martos-Benítez, Hilev Larrondo-Muguercia, … Jorge L. Martínez-Alfonso

Avoid common mistakes on your manuscript.

Introduction

Bone is one of the most common sites of metastasis for malignant tumors, affecting many patients with advanced cancer (Coleman et al. 2020a ). Bone metastases often lead to skeletal morbidity called skeletal-related events (SREs) (Moos et al. 2019 ). In general, SREs reduce overall survival and are associated with loss of mobility and social function, decreased quality of life, and substantial increase in medical costs (Coleman et al. 2020b ). In most cases, the treatment of bone metastases focuses on preventing disease progression and alleviating symptoms. And within the context of multidisciplinary supportive care, years of disease control and reduction of the impact of metastatic bone disease on physical function can be achieved (Coleman 2006 ). Cancer patients require ICU (intensive care unit) admission after cancer progression, surgery, radiotherapy-related complications, or complications from severe acute illness (Soares et al. 2010 ). Patients with bone metastases are more severely ill and more likely to have complications than cancer patients without bone metastases, and an increased need for medical care (Fornetti et al. 2018 ; Jimenez-Andrade et al. 2010 ). Therefore, it is important to identify high-risk patients with poor prognosis in the intensive care unit. It helps clinicians to improve treatment strategies in time to improve the prognosis of patients.

Currently, multiple studies have explored the prognostic factors and established models to predict the prognosis of patients with various types of malignant tumors (Baba et al. 2018 ; Vichapat et al. 2011 ; Fang et al. 2020 ; Gurney et al. 2013 ; Liu et al. 2016 ; Mao et al. 2018 ). Other studies have developed models to predict bone metastasis in patients with malignant tumors (Teng et al. 2020 ; Ellmann et al. 2019 ; Hou et al. 2021 ). Bone metastases are common in patients with malignant tumors, whereas few studies have been conducted with bone metastases as research subjects to explore the prognosis of patients (Guo et al. 2008 ; Abdelazeem et al. 2022 ).

The nomogram has been widely used as a predictive method for the prognosis of patients with various diseases (Park 2018 ; Lv et al. 2021 ; Hess 2021 ; Yuan and Wu 2021 ), and its visual interface allows accurate quantification of the risk of independent risk factors by score. Clinicians can calculate scores from the characteristics on the column line graphs to predict the probability of death or illness of a patient. In this study, a nomogram prognostic model based on Cox proportional hazard model was established by employing a large multicenter database MIMIC IV 2.0 as the data source, and patients with secondary bone tumors in the intensive care unit as the research subjects. The aim was to explore the independent risk factors affecting the prognosis of patients and to facilitate clinicians to identify high-risk patients for more accurate clinical decision-making.

Study cohort and data

Data were extracted from the MIMIC IV 2.0 database on patients diagnosed with secondary bone tumors according to the International Classification of Diseases codes, Ninth Revision (198.5) and Tenth Revision (C7B.03, C79.5). To improve usability, we have collected routine, readily accessible clinical indicators. The collected data included patient demographics (age, gender, ethnicity), body mass index, comorbidities (cancers, acute kidney injury, hepatic metastases, pulmonary metastasis, brain metastases, acidosis, respiratory failure, heart failure, atrial fibrillation, hypertension), treatment information (chemotherapy, parenteral nutrition, radiotherapy, mechanical ventilation), laboratory results (hematology: atypical lymphocytes, metamyelocytes, mean corpuscular hemoglobin concentration, mean corpuscular volume, mean hemoglobin content; biochemical test: pO 2 , calculated total CO 2 , pCO 2 , pH, base excess, lactate, free calcium; biochemical test: glutamic-pyruvic transaminase, alkaline phosphatase, glutamic oxaloacetic transaminase, creatinine kinase MB, albumin, total protein, anion gap, bicarbonate, calcium, creatinine, chloride, potassium), and prognosis scores(APSIII, SOFA, SAPSII), with cases with missing data excluded. For patients with multiple ICU admissions, we selected data from the first ICU admission of the patient for analysis. In addition, we used data from patients within 24 h of admission to the ICU for the analysis. If the patient had multiple measurements within 24 h of admission to the ICU, the data from the first measurement were used.

Statistical analysis

Each variable was divided into training and validation data sets, with the categorical variables described by percentage (%), non-normally distributed continuous variables expressed using median and quartiles, and normally distributed continuous variables described using mean and standard error [mean (S.E.)]. The chi-square test was adopted to compare differences in categorical variables, and the t-test or Mann–Whitney U test was used to compare differences between two groups of continuous variables. The starting point for follow-up was defined as the time the patient was admitted to the ICU. The primary outcome indicator for this study was the long-term mortality of the patients. Date of death is extracted from two sources: the hospital information system and the Massachusetts State Registry of Vital Records and Statistics. For the training cohort, feature selection was performed using univariate Cox regression and stepwise Cox regression based on AIC (Akaike Information Criterion) with both selections. Variables with P < 0.05 in the univariate analysis were included in the stepwise Cox regression, while variables with P < 0.05 in the stepwise Cox regression were included in the final Cox proportional hazard model, and the corresponding nomogram was generated. The multicollinearity of the variables in the model was detected by calculating the variance inflation factor (VIF), and a VIF higher than 2 was considered to have multicollinearity among the variables. Overall survival at 1 month, 3 months, 1 year, and 3 years was estimated using the nomograms. The discrimination ability of the model was evaluated by the area under the time-dependent receiver operating characteristic curve (time-dependent AUC). The calibration graph was used to assess the agreement between the predicted and actual values of the model. The survival package (version 3.5-7) was used for univariate Cox regression and stepwise Cox regression, the rms package (version 6.7-0) was used for plotting nomogram and calibration curves, the survivalROC package (version 1.0.3.1) was used for plotting ROC curves, and the dcurves package (version 0.4.0.9) was used for plotting decision curves. All statistical analyses were performed using R 4.2.1., with a bilateral P -value < 0.05 considered statistically significant.

Study cohort

A total of 1357 patients with bone metastases admitted to the ICU were identified from the database, and after excluding patients with missing information ( N = 329), a total of 1028 patients were finally included in the study (median survival time: 642.50 days). Including 720 in the training cohort (median survival time: 624.00 days) and 308 in the validation cohort (median survival time: 695.50 days) (Table 1 ).

Feature selection and model building

Feature selection by univariate Cox regression and stepwise Cox regression showed that nine features, including albumin, APSIII, chemotherapy, lactate, chloride, hepatic metastases, respiratory failure, SAPSIII, total protein, were independent predictors of prognosis in patients with secondary bone tumors in the intensive care unit (Table 2 ). The VIF of the variables in the model was calculated and the results were all below 2 (albumin: 1.166, APSIII: 1.705, chemotherapy: 1.107, chloride: 1.080, hepatic metastases: 1.084, lactate: 1.129, respiratory failure: 1.079, SAPSII: 1.733, total protein: 1.181), showing no multicollinearity. The Cox proportional hazard model was established based on the above characteristics, and the nomogram was drawn as shown in Fig. 1 . In the nomogram, the total score (Total Points) for each patient is calculated by adding the scores corresponding to each feature (Points), and the total score corresponds vertically to the scale on the predictor (1-month, 3-month, 1-year, and 3-year survival probability), i.e., the patient’s survival probability. If a patient’s ultimate total score (Total Points) is 300, then the patient’s probability of survival at 1 month, 3 months, 1 year, and 3 years is 90–95%, 80%, 60%, and 40%, respectively. In addition, for the categorical variables included in the model, we plotted Kaplan–Meier curves according to their grouping (Fig. 2 ).

The nomogram for predicting survival in patients with secondary bone tumors. RF respiratory failure, APSIII Acute Physiology Score III, SAPSII Simplified Acute Physiology Score II

A KM curves grouped by training and validation sets. B – D Kaplan–Meier curves plotted by subgroups Chemotherapy, Hepatic metastases, and RF. RF, respiratory failure

Validation of the model

The ROC curve, calibration curve, and decision curve were plotted to validate the model. The results of the ROC curve analysis showed that the AUC of the nomogram model for predicting the mortality in the training cohort at 1 month, 3 months, 1 year, and 3 years was 0.862, 0.890, 0.826, and 0.831, respectively; the AUC of the for predicting model for predicting the mortality in the validation cohort at 1 month, 3 months, 1 year, 3 years was 0.854, 0.884, 0.872, and 0.839, respectively (Fig. 3 ). And the model exhibited good predictive accuracy. The calibration curve analysis revealed that the agreement between the predicted and the actual values was within an acceptable range (Fig. 4 ). In addition, we plotted decision curves (Fig. 5 ). The green horizontal line in the figure shows the benefit if none of the patients received the intervention, the red bias line shows the benefit if all the patients received the intervention, and the blue curve shows the benefit if they received the intervention as judged by the model. The figure shows that our model has a large net gain in both the training and validation cohorts.

Time‐dependent AUC of using the nomogram to predict overall survival (OS) probability within 1 month, 3 months, 1 year, and 3 years in the training cohort ( A ) and validation cohorts ( B )

Calibration curves of the nomogram: A Calibration curves of 1-month, 3-month, 1-year, and 3-year OS for patients in the training cohort. B Calibration curves of 1-month, 3-month, 1-year, and 3-year OS for patients in the validation cohort

Decision curve analysis of the nomogram: A 1‐month survival benefit in the training cohort. B 3‐month survival benefit in the training cohort. C 1‐year survival benefit in the training cohort. D 3‐year survival benefit in the training cohort. E 1‐month survival benefit in the training cohort. F 3‐month survival benefit in the training cohort. G 1‐year survival benefit in the training cohort. H 3‐year survival benefit in the training cohort

In the present study, we studied patients with secondary bone tumors in the intensive care unit and developed a nomogram model to predict patient prognosis based on patient demographic information, laboratory test indicators, and comorbidities/surgical history. The model achieved an AUC of above 0.8 in both the training and validation cohorts, showing good predictive value.

Most current studies on secondary bone tumors have focused on bone metastases from specific tumors (Li et al. 2021 ; Lang et al. 2013 ; Huang et al. 2019 ; Sun et al. 2019 ), and few pan-cancer studies have been conducted on bone metastases in all cancer patients. However, there is a certain commonality in patients who develop secondary bone tumors, especially in patients with bone metastases admitted to the intensive care unit. An earlier similar study analyzed prognostic factors based on 216 patients with bone metastases (Teshima et al. 1990 ), but the study cohort was not limited to the intensive care unit. Independent predictors of prognosis in patients with bone metastases in the intensive care unit remain uncertain. Hence, we developed a predictive model that can predict the prognosis of patients with secondary bone tumors in the intensive care unit to provide supporting data for future studies.

Our model showed that nine characteristics, including low albumin, APSIII, chemotherapy, high lactate, low chloride, hepatic metastases, respiratory failure, SAPSIII, and low total protein, were independent predictors of prognosis in patients with secondary bone tumors in the intensive care unit. Among them, albumin, chemotherapy, chloride, and total protein were shown to be protective factors; while, APSIII, hepatic metastases, SAPSIII, SOFA, and lactate were promoting factors of mortality. Among the protective biomarkers, total protein and albumin are often used as indicators of nutritional status and hepatic synthetic function (Hülshoff et al. 2013 ), and exogenous albumin is frequently treated as a nutritional support drug in critically ill patients (Farrugia 2010 ). Bone metastasis means tumor progression. Hypoproteinemia is prevalent in cancer patients due to the damage inflicted on the body by the tumor and various treatment methods (Christina et al. 2023 ; Jiang et al. 2022 ; Sun et al. 2022 ); therefore, these patients require a higher protein intake to maintain body functions (Muscaritoli et al. 2021 ). Adequate plasma albumin has been demonstrated in many studies to be the basis for improved prognosis in patients with various medical conditions (Fanali et al. 2012 ; Yu et al. 1877 ; Amouzandeh et al. 2018 ; Arques 2018 ). Meanwhile, a prospective cohort study showed a significant negative correlation between serum albumin and the inflammatory marker C-reactive protein (Sheinenzon et al. 2021 ). Serum chloride ions are important electrolytes for maintaining body fluid homeostasis and are associated with the cardiac, renal and neurohormonal systems (Zandijk et al. 2021 ). Chloride was associated with acidosis and we included acidosis for analysis, but acidosis did not show a correlation with patient prognosis. The effect of serum chloride ions on patient prognosis is controversial to some extent. A study by Yaling Zhai et al. showed that elevated serum chloride levels were associated with poor prognostic outcomes in patients with IgA nephropathy, which contradicts our findings (Zhai et al. 2021 ). Nevertheless, some studies have shown that electrolyte disorders such as hypochlorhydria are significantly associated with poor prognosis in cancer patients (Li et al. 2020 ). In addition, a study on heart failure revealed a significant inverse association between serum chloride concentration and long-term mortality of patients (HR: 0.890; 95% CI: 0.863–0.918; P < 0.001), which is consistent with our study. Therefore, we believe that the effect of serum chloride ions on patient mortality is related to the disease characteristics of patients. However, no studies have directly illustrated the effect of serum chloride concentration on the prognosis of patients with bone metastases, and more research data are needed for validation. Among the biomarkers that manifest as mortality-promoting factors, lack of oxygen in the body affects the normal function of many organs (Fenves and Emmett 2021 ). In our model, the biomarkers incorporated into the model are mostly indicators reflecting acid–base and electrolyte balance and nutritional status in the patient’s body. Hence, for patients with secondary bone tumors in the intensive care unit, the administration of adequate nutrients and maintenance of acid-base balance are important measures to improve the prognosis of patients. In addition, hepatic metastases and the prognostic score were also major risk factors. This suggests that the severity of the cancer and the patient's physical condition are equally significant in predicting prognosis.

Our model can provide valid predictive information, but some limitations need to be mentioned: first, due to the limitation of the database, we could not include some important indicators, such as the primary tumor of the patient, the size of the primary tumor, and the site of metastasis. Second, we were unable to determine whether the patient’s combined tumor was the primary tumor. Moreover, some laboratory indicators may interact with each other, but we are unable to detect the interactions between covariates. Finally, our model only used data from a single center and needs to be validated using a large sample of data from multiple centers.

A prognostic model has been developed in this study for patients with secondary bone tumors in the intensive care unit. The prediction performance of the model is robust and it can provide valid forecasting information. The indicators included in the model suggest that nutritional support and maintenance of fluid balance are important therapeutic measures to improve the prognosis of patients with bone metastases in the intensive care unit.

Data availability

All data generated or analyzed during this study are included in this published article or are available from the corresponding author on reasonable request.

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Li, W., Li, J. & Cai, J. Development of a nomogram to predict the prognosis of patients with secondary bone tumors in the intensive care unit: a retrospective analysis based on the MIMIC IV database. J Cancer Res Clin Oncol 150 , 164 (2024). https://doi.org/10.1007/s00432-024-05667-9

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Do I have to get chemo to treat my cancer? That answer is changing as treatments evolve.

By prioritizing quality of life in treatment decisions and embracing innovative approaches, we can redefine the standard of care for cancer patients, removing chemo as a first line of defense..

Chemotherapy has long been a cornerstone of treatment when it comes to fighting cancer. Although it has proven efficacy in fighting the disease, its toll on patients both mentally and physically remains profound. While the physical effects of treatment often subside, the mental strain can persist long after.

Research shows that 58% of cancer patients feel their emotional needs are frequently overshadowed by their physical needs, with some reporting that the mental toll surpasses the physical burden.

While the main objective is to cure cancer if possible, there also needs to be an emphasis on quality of life when determining a treatment plan.

New advancements in cancer therapy are making it possible to select alternatives to chemo as a first line of defense or at least lessen the dose. While it will depend on the type of cancer, as well as the stage at diagnosis, an acute focus on quality of life can improve survival rates, as studies show.

Quality of life considerations can improve cancer patients' survival

One study tracking lung cancer patients revealed that considering quality of life significantly enhanced their five-year survival rates.

This underscores the critical importance of integrating health-related quality of life factors into the assessment of cancer therapies.

Yes, urgent care is convenient. But seeing your doctor may save your life.

It appears almost predestined that we are now in an era with a dedication to improving quality of life in cancer care as Americans are living longer , while also grappling with a notable surge in cases of cancer .

President Joe Biden also has issued an executive order called Cancer Moonshot , which aims to accelerate research and collaboration to make significant strides in prevention, diagnosis, treatment and finding a cure for cancer.

One of the Cancer Moonshot’s key objectives is to tailor treatments to individual patients, emphasizing a holistic approach beyond mere cancer eradication. This emphasizes the path for clinicians and patients to consider treatments that better align with holistic needs, including taking quality of life into account. Today there are several treatments , either as alternatives or complements to chemotherapy that can be discussed.

Patients need to engage in decisions about treatment

However, transitioning these discussions into actions demands concerted efforts from stakeholders − clinicians, researchers, industry pioneers and patients. Patients are now more engaged than ever, having a significant effect on health care delivery and expectations; after all, it is their quality of life being most directly affected by the treatment decision.

Patients aren't just participants in their care; they're the driving force behind innovation, especially when volunteering to participate in clinical trials.

When should you get a colonoscopy? How getting this medical test can save your life.

For instance, skin cancer, the most common form of cancer , presents challenges in treatment, with recurrence rates that can range between 1% and 25% depending on the type .

In individuals, where it does return, there is concern that treatment could lead to disfigurement or worse, based on the location and depth of the cancer. That has a profound impact on the patient, even once the cancer is “cured."

Coupling patient involvement in trials and clinicians' pursuit of quality of life-centered solutions − for example, a novel therapy like Alpha DaRT − offers promising alternatives to chemotherapy and surgery.

Another promising avenue in the evolution of cancer treatment is immunotherapy. By leveraging the body's immune system to combat cancer, immunotherapy represents a significant advancement. Certain types of immunotherapy have demonstrated notable improvements in patients' quality of life, marking a significant stride in cancer care.

By prioritizing quality of life in treatment decisions and embracing innovative approaches, we can redefine the standard of care for cancer patients, removing chemo as a first line of defense and improving patient experiences. Charting this new course will take continued investment, but it will reap invaluable returns as the existence extends beyond mere survival from disease but also lives enriched with quality and fulfillment.

Dr. Robert Den is chief medical officer at Alpha Tau Medical , where he leads clinical research functions. He also is an associate professor of radiation oncology, cancer biology and urology at Thomas Jefferson University.

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27 March 2024

How does a cancer vaccine work?

Liam Drew 0

Liam Drew is a freelance writer based near London, UK.

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Vaccines are usually used to prevent infectious diseases. A therapeutic cancer vaccine is different. Rather than teaching the immune system to recognize pathogens in advance of an infection, these vaccines use identifying proteins produced by cancer cells, known as antigens, to provoke a powerful immune response to existing tumours.

A variety of approaches

The first step is to deliver antigens to immune cells called dendritic cells. These present antigens to other immune cells, and stimulate a response. In the past decade, several approaches have emerged 1 . One delivers antigens that are shared by many people with the same type of cancer ( 2 ). Others, including those that make use of messenger RNA (mRNA) technology, are highly personalized to the unique neoantigens produced by an individual’s tumour ( 3 ). Other personalized approaches involve injecting dendritic cells that are pre-loaded with cancer antigens ( 1 ), or generating antigens inside the body and promoting their uptake by dendritic cells in situ ( 4 ).

An infographic illustrating four approaches for presenting antigens to immune cells to stimulate an immune response.

Infographic: Alisdair Macdonald

Mounting a response

Unlike preventive vaccines, which focus mainly on activating antibody-producing B cells, a therapeutic cancer vaccine must generate a strong T-cell response. Dendritic cells loaded with tumour antigens bind and activate CD8 + cytotoxic T cells, which can then mount an attack on the tumour 2 .

Dendritic cells loaded with tumour antigens bind and activate CD8+ cytotoxic T cells, which can then mount an attack on the tumour.

Promising results

Numerous therapeutic cancer vaccines, on the basis of a variety of approaches, are showing encouraging results in trials.

Pancreatic cancer: In a phase I trial of a personalized mRNA vaccine, half of the participants developed T cells targeted to cancer neoantigens 6 . Recurrence-free survival in this group was longer compared with those who did not respond.

Melanoma: A phase II trial of a personalized mRNA vaccine showed a 44% decrease in the risk of post-surgical recurrence or death 7 . A phase III trial is under way, with final results expected in 2029.

Lymphoma: A phase I/II trial of an in situ vaccine that combined radiotherapy with signalling molecules that mobilize and activate dendritic cells showed evidence of tumour regression in 8 of 11 people who were treated 1 .

Obstacles ahead

The future development and the clinical uptake of therapeutic cancer vaccines will be shaped by several factors.

Unwieldy trials. Testing multiple combinations of agents makes clinical trials more complex. Another complicating factor is timing when to give a vaccine relative to other interventions, such as surgery.

Immunity monitoring. Tracking acquired immunity is important for assessing vaccine efficacy. For cancer vaccines, new T-cell monitoring techniques are needed.

Scalability. Personalized cancer vaccines could pose logistical challenges. Streamlining production will be essential to keep costs down and availability high.

Nature 627 , S34-S35 (2024)

doi: https://doi.org/10.1038/d41586-024-00841-y

This article is part of Nature Outline: Cancer vaccines , a supplement produced with the financial support from Moderna . Nature maintains full independence in all editorial decisions related to the content. About this content .

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Introduction. Recent discoveries and rapidly accumulating data are providing novel insights into the extrinsic and intrinsic causes and mechanisms in the development and progression of cancer. 1 These and earlier advances in cancer prevention, early detection, and treatment have contributed to the continuous decline in the age-standardized cancer death rate from 1991 to 2017 by a total of 29%.
About Cancer Research
About Cancer Research Scope. Cancer Research publishes impactful original studies, reviews, and opinion pieces of high significance to the broad cancer research community.Cancer Research seeks manuscripts that offer conceptual or technological advances leading to basic and translational insights into cancer biology. Manuscripts that focus on convergence science, the bridging of two or more ...
Understanding Cancer Research Study Design and How to Evaluate Results
Medical journals publish many cancer research studies each year. This is good for adding to the scientific knowledge about cancer that lead to better treatment and care. However, the fast pace makes it hard for doctors, people with cancer, and caregivers to keep up with all of the new advances. Research studies are always shaping and reshaping ...
Two Years of Cancer Research Communications: A Conversation with the
Mardis: One clear area of distinction that we planned from the very beginning was the breadth of the journal. Cancer research encompasses multiple areas of expertise. It's very interdisciplinary, so we wanted to capture that breadth in the content we publish. ... I think Cancer Research Communications would be a very good fit for it, assuming ...
Understanding the Publication and Format of Cancer Research Studies
Most cancer research studies include background information, the researcher's methods, results, and the meaning of the findings. Studies published in many journals present this data in a certain format known as Introduction, Methods, Results, and Discussion (IMRAD). The IMRAD format allows other scientists to do similar studies to see if there ...
Home page
Aims and Scope. BMC Cancer is an open access, peer-reviewed journal that considers articles on all aspects of cancer research, including the pathophysiology, prevention, diagnosis and treatment of cancers. The journal welcomes submissions in broad areas of cancer research including molecular and cellular biology, genetics, epidemiology, and ...
Nature Reviews Cancer
Extrachromosomal DNA (ecDNA) is now accepted as a major contributor to cancer pathogenesis. In this Review, Yan, Mischel and Chang highlight the recent advancements in ecDNA research, providing ...
The Lancet Oncology
In 2015, the Lancet Oncology Commission on Global Cancer Surgery focused on access to safe, affordable, and timely cancer surgery worldwide. It highlighted cancer surgery as integral to national cancer control plans and critically examined the state of global cancer surgery and changes in policy that might drive improvements in research, education, and systems of care across all income settings.
Cancers
Cancers is a peer-reviewed, open access journal of oncology, published semimonthly online by MDPI.The Irish Association for Cancer Research (IACR), Spanish Association for Cancer Research (ASEICA), Biomedical Research Centre (CIBM), British Neuro-Oncology Society (BNOS) and Spanish Group for Cancer Immuno-Biotherapy (GÉTICA) are affiliated with Cancers and their members receive a discount on ...
Cancer screening and early detection in the 21st century
Nurses are well-positioned to lead the implementation of cancer screening recommendations in the 21 st Century through their practice, research, educational efforts and advocacy. Keywords: cancer screening, sensitivity, specificity, screening recommendations, decision-making, early detection. The goal of cancer screening and early detection is ...
Year in Review: Cancer Research Insights from 2019
Overall, the US cancer death rate is continuing to decrease, but there's more to that story. Throughout 2019, the recurring themes of cancer research news included the link between obesity and cancer, increased rates of certain cancers in people younger than 50, and continued barriers to cancer care due to poverty, race, where people live, and other factors.
One in five people with cancer participate in medical research studies
Cancer clinical research is a true partnership between those with cancer and those who study and treat cancer." More information: Joseph Unger et al, Journal of Clinical Oncology (2024).
Can cancer research shift its focus?
One study published in June states that just 4.2% of the US$24.5 billion in public and philanthropic grants for cancer research went to surgery and radiotherapy research in 2016-20, despite ...
Development of a nomogram to predict the prognosis of ...
Purpose The present study aimed to develop a nomogram to predict the prognosis of patients with secondary bone tumors in the intensive care unit to facilitate risk stratification and treatment planning. Methods We used the MIMIC IV 2.0 (the Medical Information Mart for Intensive Care IV) to retrieve patients with secondary bone tumors as a study cohort. To evaluate the predictive ability of ...
Is chemo necessary? Cancer patients need to consider quality of life
While the main objective is to cure cancer if possible, there also needs to be an emphasis on quality of life when determining a treatment plan. ... Research shows that 58% of cancer patients feel ...
Frequently asked questions about Molecular Cancer
Molecular Cancer is embedded in a family of related on-line journals, all with BioMed Central's open-access policy. Molecular Cancer focuses on all areas of cancer-related science, from bench and bedside [ 11] and publishes immediately after accepting; this concept is paying us back [ 12 - 19 ]. We, the editors of Molecular Cancer, are willing ...
How does a cancer vaccine work?
Pancreatic cancer: In a phase I trial of a personalized mRNA vaccine, half of the participants developed T cells targeted to cancer neoantigens 6. Recurrence-free survival in this group was longer ...