Dataset Information

Bayesian meta-analytical methods to incorporate multiple surrogate endpoints in drug development process.

ABSTRACT: A number of meta-analytical methods have been proposed that aim to evaluate surrogate endpoints. Bivariate meta-analytical methods can be used to predict the treatment effect for the final outcome from the treatment effect estimate measured on the surrogate endpoint while taking into account the uncertainty around the effect estimate for the surrogate endpoint. In this paper, extensions to multivariate models are developed aiming to include multiple surrogate endpoints with the potential benefit of reducing the uncertainty when making predictions. In this Bayesian multivariate meta-analytic framework, the between-study variability is modelled in a formulation of a product of normal univariate distributions. This formulation is particularly convenient for including multiple surrogate endpoints and flexible for modelling the outcomes which can be surrogate endpoints to the final outcome and potentially to one another. Two models are proposed, first, using an unstructured between-study covariance matrix by assuming the treatment effects on all outcomes are correlated and second, using a structured between-study covariance matrix by assuming treatment effects on some of the outcomes are conditionally independent. While the two models are developed for the summary data on a study level, the individual-level association is taken into account by the use of the Prentice's criteria (obtained from individual patient data) to inform the within study correlations in the models. The modelling techniques are investigated using an example in relapsing remitting multiple sclerosis where the disability worsening is the final outcome, while relapse rate and MRI lesions are potential surrogates to the disability progression.

SUBMITTER: Bujkiewicz S

PROVIDER: S-EPMC4950070 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Bayesian meta-analytical methods to incorporate multiple surrogate endpoints in drug development process.

Bujkiewicz Sylwia S Thompson John R JR Riley Richard D RD Abrams Keith R KR

Statistics in medicine 20151103 7

A number of meta-analytical methods have been proposed that aim to evaluate surrogate endpoints. Bivariate meta-analytical methods can be used to predict the treatment effect for the final outcome from the treatment effect estimate measured on the surrogate endpoint while taking into account the uncertainty around the effect estimate for the surrogate endpoint. In this paper, extensions to multivariate models are developed aiming to include multiple surrogate endpoints with the potential benefit ...[more]

PMID: 26530518

Similar Datasets

Project description:BACKGROUND:Recent phase 3 trials have shown an overall survival benefit in metastatic melanoma. We aimed to assess whether progression-free survival (PFS) could be regarded as a reliable surrogate for overall survival through a meta-analysis of randomised trials. METHODS:We systematically reviewed randomised trials comparing treatment regimens in metastatic melanoma that included dacarbazine as the control arm, and which reported both PFS and overall survival with a standard hazard ratio (HR). We correlated HRs for overall survival and PFS, weighted by sample size or by precision of the HR estimate, assuming fixed and random effects. We did sensitivity analyses according to presence of crossover, trial size, and dacarbazine dose. FINDINGS:After screening 1649 reports and meeting abstracts published before Sept 8, 2013, we identified 12 eligible randomised trials that enrolled 4416 patients with metastatic melanoma. Irrespective of weighting strategy, we noted a strong correlation between the treatment effects for PFS and overall survival, which seemed independent of treatment type. Pearson correlation coefficients were 0·71 (95% CI 0·29-0·90) with a random-effects assumption, 0·85 (0·59-0·95) with a fixed-effects assumption, and 0·89 (0·68-0·97) with sample-size weighting. For nine trials without crossover, the correlation coefficient was 0·96 (0·81-0·99), which decreased to 0·93 (0·74-0·98) when two additional trials with less than 50% crossover were included. Inclusion of mature follow-up data after at least 50% crossover (in vemurafenib and dabrafenib phase 3 trials) weakened the PFS to overall survival correlation (0·55, 0·03-0·84). Inclusion of trials with no or little crossover with the random-effects assumption yielded a conservative statement of the PFS to overall survival correlation of 0·85 (0·51-0·96). INTERPRETATION:PFS can be regarded as a robust surrogate for overall survival in dacarbazine-controlled randomised trials of metastatic melanoma; we postulate that this association will hold as treatment standards evolve and are adopted as the control arm in future trials. FUNDING:None.

Project description:BackgroundClinical trials in severe falciparum malaria require a large sample size to detect clinically meaningful differences in mortality. This means few interventions can be evaluated at any time. Using a validated surrogate endpoint for mortality would provide a useful alternative allowing a smaller sample size. Here we evaluate changes in coma score and plasma lactate as surrogate endpoints for mortality in severe falciparum malaria.MethodsThree datasets of clinical studies in severe malaria were re-evaluated: studies from Chittagong, Bangladesh (adults), the African 'AQUAMAT' trial comparing artesunate and quinine (children), and the Vietnamese 'AQ' study (adults) comparing artemether with quinine. The absolute change, relative change, slope of the normalization over time, and time to normalization were derived from sequential measurements of plasma lactate and coma score, and validated for their use as surrogate endpoint, including the proportion of treatment effect on mortality explained (PTE) by these surrogate measures.ResultsImprovements in lactate concentration or coma scores over the first 24 hours of admission, were strongly prognostic for survival in all datasets. In hyperlactataemic patients in the AQ study (n = 173), lower mortality with artemether compared to quinine closely correlated with faster reduction in plasma lactate concentration, with a high PTE of the relative change in plasma lactate at 8 and 12 hours of 0.81 and 0.75, respectively. In paediatric patients enrolled in the 'AQUAMAT' study with cerebral malaria (n = 785), mortality was lower with artesunate compared to quinine, but this was not associated with faster coma recovery.ConclusionsThe relative changes in plasma lactate concentration assessed at 8 or 12 hours after admission are valid surrogate endpoints for severe malaria studies on antimalarial drugs or adjuvant treatments aiming at improving the microcirculation. Measures of coma recovery are not valid surrogate endpoints for mortality.

Dataset Information

Bayesian meta-analytical methods to incorporate multiple surrogate endpoints in drug development process.

Publications

Bayesian meta-analytical methods to incorporate multiple surrogate endpoints in drug development process.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure