ArticleJNCI cancer spectrum2018
Extent of Exclusions for Chronic Conditions in Breast Cancer Trials.
Article in JNCI cancer spectrum, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Ribociclib plus letrozole in subgroups of special clinical interest with hormone receptor-positive, human epidermal growth factor receptor 2-negative advanced breast cancer: Subgroup analysis of the phase IIIb CompLEEment-1 trial.Breast (Edinburgh, Scotland) · 2022Trial
- Age, Age-Related Comorbidities and Survival in Palbociclib, Ribociclib and Abemaciclib Users With Advanced Breast Cancer: A Nation-Wide Retrospective Cohort Study.Pharmacoepidemiology and drug safety · 2026Article
- Gynecologic cancer clinical trial eligibility criteria as a marker for equitable clinical trial access.Journal of the National Cancer Institute · 2025Article
- Observational
- Eligibility criteria in clinical trials in breast cancer: a cohort study.BMC medicine · 2023Article
- Evaluating Demographic Representation in Clinical Trials: Use of the Adaptive Coronavirus Disease 2019 Treatment Trial (ACTT) as a Test Case.Open forum infectious diseases · 2023Article
- Personalized (N-of-1) Trials for Patient-Centered Treatments of Multimorbidity.Harvard data science review · 2022Article
- Cardiovascular Safety Assessment in Cancer Drug Development.Journal of the American Heart Association · 2021Review
- Multimorbidity: Implications and directions for health psychology and behavioral medicine.Health psychology : official journal of the Division of Health Psychology, American Psychological Association · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Experts have expressed concerns that patients with chronic conditions are being excessively excluded from cancer randomized clinical trials (RCTs), limiting generalizability. Accordingly, we queried clinicaltrials.gov to determine the extent to which patients with chronic conditions were excluded from phase III cancer trials, using National Cancer Institute-sponsored breast cancer RCTs as a test case. Two physicians independently coded for the presence of 19 prevalent chronic conditions within eligibility criteria. They also coded for exclusions based on performance status and vague criteria that could have broadly excluded patients with chronic conditions. The search identified 58 RCTs, initiated from 1993 to 2012. Overall, 88% of trials had at least one exclusion for a chronic condition, performance status, or vague criterion. The three most commonly excluded conditions were chronic kidney disease, heart failure, and ischemic heart disease. Our study demonstrated that patients with prevalent chronic conditions were commonly excluded from National Cancer Institute-sponsored RCTs.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.