ArticleCancer investigation2022
The Big Data Paradox in Clinical Practice.
Article in Cancer investigation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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
23 citing papers in PubMed.
- Choosing real-world data for clinical and epidemiological research: methodological lessons from NHIRD and TriNetX-A narrative review.Annals of medicine · 2026Review
- Big data and psychiatry: advances, constraints and future directions.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2026Article
- Advancing clinical trials for rare renal cell carcinoma subtypes: Consensus statements from the International Kidney Cancer Symposium North America 2025 think tank.Urologic oncology · 2026Article
- Are Traditional Registries Becoming Obsolete in the Modern Digital Health Ecosystem?Journal of medical Internet research · 2026Article
- Big Data for Drug Discovery: Some Historical Landscape, Considerations, and Applications for a Medicinal Chemist.ACS omega · 2026Review
- Big Data in the Assessment of Medication Safety in Pregnancy: Opportunities and Challenges.Paediatric drugs · 2025Article
- Toward Artificial Intelligence in Oncology and Cardiology: A Narrative Review of Systems, Challenges, and Opportunities.Journal of clinical medicine · 2025Article
- Dupilumab treatment is not associated with changes in lymphoma risk in atopic dermatitis and other type 2 inflammatory diseases: data from a large-scale retrospective cohort study.Frontiers in medicine · 2025Article
- With big data comes big responsibility: Strategies for utilizing aggregated, standardized, de-identified electronic health record data for research.Clinical and translational science · 2025Article
- To weight or not to weight? The effect of selection bias in 3 large electronic health record-linked biobanks and recommendations for practice.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Risk-benefit trade-offs and precision utilities in phase I-II clinical trials.Clinical trials (London, England) · 2024Article
- Optimising the use of electronic medical records for large scale research in psychiatry.Translational psychiatry · 2024Review
- Differential Treatment Effects of Subgroup Analyses in Phase 3 Oncology Trials From 2004 to 2020.JAMA network open · 2024Article
- To weight or not to weight? Studying the effect of selection bias in three large EHR-linked biobanks.medRxiv : the preprint server for health sciences · 2024Article
- Locoregional Therapies in Immunologically "Cold" Tumors: Opportunities and Clinical Trial Design Considerations.Journal of vascular and interventional radiology : JVIR · 2024Review
- The Buzz Surrounding Precision Medicine: The Imperative of Incorporating It into Evidence-Based Medical Practice.Journal of personalized medicine · 2023Article
- Prevalence and implications of significance testing for baseline covariate imbalance in randomised cancer clinical trials: The Table 1 Fallacy.European journal of cancer (Oxford, England : 1990) · 2023Article
- Interpreting Randomized Controlled Trials.Cancers · 2023Review
- The phenotype-genotype reference map: Improving biobank data science through replication.American journal of human genetics · 2023Article
- Patterns and outcome of unplanned care in lung cancer patients: an observational study in a medical oncology department.Translational lung cancer research · 2023Article
Corrections and comments
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Authors and funding
1 author.
Funding
Abstract
The big data paradox is a real-world phenomenon whereby as the number of patients enrolled in a study increases, the probability that the confidence intervals from that study will include the truth decreases. This occurs in both observational and experimental studies, including randomized clinical trials, and should always be considered when clinicians are interpreting research data. Furthermore, as data quantity continues to increase in today's era of big data, the paradox is becoming more pernicious. Herein, I consider three mechanisms that underlie this paradox, as well as three potential strategies to mitigate it: (1) improving data quality; (2) anticipating and modeling patient heterogeneity; (3) including the systematic error, not just the variance, in the estimation of error intervals.
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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.