ReviewContemporary clinical trials communications2020
Current status of Bayesian clinical trials for oncology, 2020.
Review in Contemporary clinical trials communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Design and analysis of umbrella trials: Where do we stand?Frontiers in medicine · 2022Pooled it
- A Bayesian Treatment Selection Design for Phase II Randomised Cancer Clinical Trials.Statistics in medicine · 2026Article
- Insights into the adoption of innovative clinical trials across therapeutic areas using clinical trials registry data and large Language models.Scientific reports · 2025Article
- Bayesian generalized method of moments applied to pseudo-observations in survival analysis.Lifetime data analysis · 2025Article
- Use of Bayesian techniques in clinical trials for rheumatoid arthritis and systemic sclerosis: a scoping review.BMC rheumatology · 2025Article
- SPIRIT 2025 explanation and elaboration: updated guideline for protocols of randomised trials.BMJ (Clinical research ed.) · 2025Article
- CONSORT 2025 explanation and elaboration: updated guideline for reporting randomised trials.BMJ (Clinical research ed.) · 2025Article
- Adaptive Universal Principles for Real-world Observational Studies (AUPROS): an approach to designing real-world observational studies for clinical, epidemiologic, and precision oncology research.British journal of cancer · 2025Review
- Use of Bayesian approaches in oncology clinical trials: A cross-sectional analysis.Frontiers in pharmacology · 2025Article
- Challenges, Complexities, and Considerations in the Design and Interpretation of Late-Phase Oncology Trials.Seminars in radiation oncology · 2023Review
- The Future of Precision Oncology.International journal of molecular sciences · 2023Review
- Improving the efficiency of clinical trials in multiple sclerosis.Multiple sclerosis (Houndmills, Basingstoke, England) · 2023Review
- Implementation of platform trials in the COVID-19 pandemic: A rapid review.Contemporary clinical trials · 2022Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bayesian methods had established a foothold in developing therapies in oncology trials.
methodsWe identified clinical trials posted on the ClinicalTrials.gov database focused on Oncology trials with a Bayesian approach in their design. Differences in study characteristics such as design, study phase, randomization, masking, purpose of study, main outcomes, gender, age and funding involvement according to Bayesian approach were assessed using Chi-squared or Fisher's exact tests.
resultsWe identified 225 studies with Bayesian components in their design addressing oncological diseases. The most common designs were Bayesian Toxicity Monitoring (26.4%), Model-based designs (36%) Model-assisted designs (8%). Statistical methods such as Bayesian logistic regression model (59.4%), Bayesian piecewise exponential survival regression (10.9%) and the Continual reassessment method (9.4%) were the most used.
conclusionsBayesian trials are more common in the early phases of drug development specifically in phase II trials (43.6%). Cancer institutes or Hospitals funded most of the studies retrieved. This type of design has increased over time and represent an innovative means of increasing trial efficiency.
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.