ArticlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing2016
DO CANCER CLINICAL TRIAL POPULATIONS TRULY REPRESENT CANCER PATIENTS? A COMPARISON OF OPEN CLINICAL TRIALS TO THE CANCER GENOME ATLAS.
Article in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Cost-effectiveness of physical activity interventions in cancer survivors of developed countries: a systematic review.Journal of cancer survivorship : research and practice · 2021Pooled it
- Trastuzumab-associated cardiac events in the Persephone trial.British journal of cancer · 2016Trial
- Targeting the DNA damage response prevents regrowth of colorectal peritoneal metastasis-derived organoids following treatment with mitomycin C.British journal of cancer · 2026Article
- Multi-omic diagnostics of prostate cancer in the presence of benign prostatic hyperplasia.Heliyon · 2023Article
- Real-life clinical data mining: generating hypotheses for evidence-based medicine.Annals of translational medicine · 2020Article
- Use of a Targeted Exome Next-Generation Sequencing Panel Offers Therapeutic Opportunity and Clinical Benefit in a Subset of Patients With Advanced Cancers.JCO precision oncology · 2019Article
- Epithelial-mesenchymal transition (EMT) signature is inversely associated with T-cell infiltration in non-small cell lung cancer (NSCLC).Scientific reports · 2018Article
- Grappling with the Future Use of Big Data for Translational Medicine and Clinical Care.Yearbook of medical informatics · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Open clinical trial data offer many opportunities for the scientific community to independently verify published results, evaluate new hypotheses and conduct meta-analyses. These data provide a springboard for scientific advances in precision medicine but the question arises as to how representative clinical trials data are of cancer patients overall. Here we present the integrative analysis of data from several cancer clinical trials and compare these to patient-level data from The Cancer Genome Atlas (TCGA). Comparison of cancer type-specific survival rates reveals that these are overall lower in trial subjects. This effect, at least to some extent, can be explained by the more advanced stages of cancer of trial subjects. This analysis also reveals that for stage IV cancer, colorectal cancer patients have a better chance of survival than breast cancer patients. On the other hand, for all other stages, breast cancer patients have better survival than colorectal cancer patients. Comparison of survival in different stages of disease between the two datasets reveals that subjects with stage IV cancer from the trials dataset have a lower chance of survival than matching stage IV subjects from TCGA. One likely explanation for this observation is that stage IV trial subjects have lower survival rates since their cancer is less likely to respond to treatment. To conclude, we present here a newly available clinical trials dataset which allowed for the integration of patient-level data from many cancer clinical trials. Our comprehensive analysis reveals that cancer-related clinical trials are not representative of general cancer patient populations, mostly due to their focus on the more advanced stages of the disease. These and other limitations of clinical trials data should, perhaps, be taken into consideration in medical research and in the field of precision medicine.
Indexed as
Identifiers
26776196PMC4961464What 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.