ArticleStatistical methods in medical research2017
Uncertainty in the Bayesian meta-analysis of normally distributed surrogate endpoints.
Article in Statistical methods in medical research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 4 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 4 syntheses or guidelines pooled it, 26 citations in OpenAlex.
- Handling missing within-study correlations in the evaluation of surrogate endpoints.Statistics in medicine · 2023Pooled it
- Use of copula to model within-study association in bivariate meta-analysis of binomial data at the aggregate level: A Bayesian approach and application to surrogate endpoint evaluation.Statistics in medicine · 2022Pooled it
- Carotid Intima-Media Thickness Progression as Surrogate Marker for Cardiovascular Risk: Meta-Analysis of 119 Clinical Trials Involving 100 667 Patients.Circulation · 2020Pooled it
- Bayesian bivariate meta-analysis of correlated effects: Impact of the prior distributions on the between-study correlation, borrowing of strength, and joint inferences.Statistical methods in medical research · 2018Pooled it
- Estimating the Potential Benefits of Confirmatory Trials for Drugs with Accelerated Approval: A Comprehensive Value of Information Framework.PharmacoEconomics · 2023Trial
- Bias in Meta-Analytic Modeling of Surrogate Endpoints in Cancer Screening Trials.Statistics in medicine · 2026Article
- A New Frequentist Implementation of the Daniels and Hughes Bivariate Meta-Analysis Model for Surrogate Endpoint Evaluation.Biometrical journal. Biometrische Zeitschrift · 2025Article
- 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
- Using Bayesian Evidence Synthesis Methods to Incorporate Real-World Evidence in Surrogate Endpoint Evaluation.Medical decision making : an international journal of the Society for Medical Decision Making · 2023Article
- 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
- Bivariate network meta-analysis for surrogate endpoint evaluation.Statistics in medicine · 2019Article
- Bayesian Multiparameter Evidence Synthesis to Inform Decision Making: A Case Study in Metastatic Hormone-Refractory Prostate Cancer.Medical decision making : an international journal of the Society for Medical Decision Making · 2018Article
- Bayesian meta-analytical methods to incorporate multiple surrogate endpoints in drug development process.Statistics in medicine · 2016Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
We investigate the effect of the choice of parameterisation of meta-analytic models and related uncertainty on the validation of surrogate endpoints. Different meta-analytical approaches take into account different levels of uncertainty which may impact on the accuracy of the predictions of treatment effect on the target outcome from the treatment effect on a surrogate endpoint obtained from these models. A range of Bayesian as well as frequentist meta-analytical methods are implemented using illustrative examples in relapsing-remitting multiple sclerosis, where the treatment effect on disability worsening is the primary outcome of interest in healthcare evaluation, while the effect on relapse rate is considered as a potential surrogate to the effect on disability progression, and in gastric cancer, where the disease-free survival has been shown to be a good surrogate endpoint to the overall survival. Sensitivity analysis was carried out to assess the impact of distributional assumptions on the predictions. Also, sensitivity to modelling assumptions and performance of the models were investigated by simulation. Although different methods can predict mean true outcome almost equally well, inclusion of uncertainty around all relevant parameters of the model may lead to less certain and hence more conservative predictions. When investigating endpoints as candidate surrogate outcomes, a careful choice of the meta-analytical approach has to be made. Models underestimating the uncertainty of available evidence may lead to overoptimistic predictions which can then have an effect on decisions made based on such predictions.
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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.