ArticleStatistics in medicine2020
Bayesian hierarchical meta-analytic methods for modeling surrogate relationships that vary across treatment classes using aggregate data.
Article in Statistics in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 4 of them syntheses that pooled it.
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Who cites it
17 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Evaluating amyloid-beta as a surrogate endpoint in trials of anti-amyloid-beta drugs in Alzheimer's disease: a Bayesian meta-analysis.Journal of comparative effectiveness research · 2026Pooled it
- Multi-indication Evidence Synthesis in Oncology Health Technology Assessment: Meta-analysis Methods and Their Application to a Case Study of Bevacizumab.Medical decision making : an international journal of the Society for Medical Decision Making · 2025Pooled it
- Handling missing within-study correlations in the evaluation of surrogate endpoints.Statistics in medicine · 2023Pooled it
- Correlation Between Early Time-to-Event Outcomes and Overall Survival in Patients With Locally Advanced Head and Neck Squamous Cell Carcinoma Receiving Definitive Chemoradiation Therapy: Systematic Review and Meta-Analysis.Frontiers in oncology · 2022Pooled it
- Methods of multi-indication meta-analysis for health technology assessment: A simulation study.Research synthesis methods · 2026Article
- A New Frequentist Implementation of the Daniels and Hughes Bivariate Meta-Analysis Model for Surrogate Endpoint Evaluation.Biometrical journal. Biometrische Zeitschrift · 2025Article
- Use of surrogate endpoints in health technology assessment: a review of selected NICE technology appraisals in oncology.International journal of technology assessment in health care · 2025Review
- Assessing heterogeneity in surrogacy using censored data.Statistics in medicine · 2024Article
- Reporting of surrogate endpoints in randomised controlled trial protocols (SPIRIT-Surrogate): extension checklist with explanation and elaboration.BMJ (Clinical research ed.) · 2024Article
- Reporting of surrogate endpoints in randomised controlled trial reports (CONSORT-Surrogate): extension checklist with explanation and elaboration.BMJ (Clinical research ed.) · 2024Article
- Comparing Bayesian hierarchical meta-regression methods and evaluating the influence of priors for evaluations of surrogate endpoints on heterogeneous collections of clinical trials.BMC medical research methodology · 2024Article
- Flexible evaluation of surrogacy in platform studies.Biostatistics (Oxford, England) · 2023Article
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- Development of a framework and decision tool for the evaluation of health technologies based on surrogate endpoint evidence.Health economics · 2022Article
- Bayesian hierarchical meta-analytic methods for modeling surrogate relationships that vary across treatment classes using aggregate data.Statistics in medicine · 2020Article
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Authors and funding
7 authors.
Funding
Abstract
Surrogate endpoints play an important role in drug development when they can be used to measure treatment effect early compared to the final clinical outcome and to predict clinical benefit or harm. Such endpoints are assessed for their predictive value of clinical benefit by investigating the surrogate relationship between treatment effects on the surrogate and final outcomes using meta-analytic methods. When surrogate relationships vary across treatment classes, such validation may fail due to limited data within each treatment class. In this paper, two alternative Bayesian meta-analytic methods are introduced which allow for borrowing of information from other treatment classes when exploring the surrogacy in a particular class. The first approach extends a standard model for the evaluation of surrogate endpoints to a hierarchical meta-analysis model assuming full exchangeability of surrogate relationships across all the treatment classes, thus facilitating borrowing of information across the classes. The second method is able to relax this assumption by allowing for partial exchangeability of surrogate relationships across treatment classes to avoid excessive borrowing of information from distinctly different classes. We carried out a simulation study to assess the proposed methods in nine data scenarios and compared them with subgroup analysis using the standard model within each treatment class. We also applied the methods to an illustrative example in colorectal cancer which led to obtaining the parameters describing the surrogate relationships with higher precision.
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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.