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How to use frailtypack for validating failure-time surrogate endpoints using individual patient data from meta-analyses of randomized controlled trials.

ABSTRACT: BACKGROUND AND OBJECTIVE:The use of valid surrogate endpoints can accelerate the development of phase III trials. Numerous validation methods have been proposed with the most popular used in a context of meta-analyses, based on a two-step analysis strategy. For two failure time endpoints, two association measures are usually considered, Kendall's ? at individual level and adjusted R2 ([Formula: see text]) at trial level. However, [Formula: see text] is not always available mainly due to model estimation constraints. More recently, we proposed a one-step validation method based on a joint frailty model, with the aim of reducing estimation issues and estimation bias on the surrogacy evaluation criteria. The model was quite robust with satisfactory results obtained in simulation studies. This study seeks to popularize this new surrogate endpoints validation approach by making the method available in a user-friendly R package. METHODS:We provide numerous tools in the frailtypack R package, including more flexible functions, for the validation of candidate surrogate endpoints using data from multiple randomized clinical trials. RESULTS:We implemented the surrogate threshold effect which is used in combination with [Formula: see text] to make decisions concerning the validity of the surrogate endpoints. It is also possible thanks to frailtypack to predict the treatment effect on the true endpoint in a new trial using the treatment effect observed on the surrogate endpoint. The leave-one-out cross-validation is available for assessing the accuracy of the prediction using the joint surrogate model. Other tools include data generation, simulation study and graphic representations. We illustrate the use of the new functions with both real data and simulated data. CONCLUSION:This article proposes new attractive and well developed tools for validating failure time surrogate endpoints.

SUBMITTER: Sofeu CL

PROVIDER: S-EPMC6986733 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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How to use frailtypack for validating failure-time surrogate endpoints using individual patient data from meta-analyses of randomized controlled trials.

Sofeu Casimir Ledoux CL Rondeau Virginie V

PloS one 20200128 1

<h4>Background and objective</h4>The use of valid surrogate endpoints can accelerate the development of phase III trials. Numerous validation methods have been proposed with the most popular used in a context of meta-analyses, based on a two-step analysis strategy. For two failure time endpoints, two association measures are usually considered, Kendall's τ at individual level and adjusted R2 ([Formula: see text]) at trial level. However, [Formula: see text] is not always available mainly due to ...[more]

PMID: 31990928

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Project description:BackgroundInterventional trials that evaluate treatment effects using surrogate endpoints have become increasingly common. This paper describes four linked empirical studies and the development of a framework for defining, interpreting and reporting surrogate endpoints in trials.MethodsAs part of developing the CONSORT (Consolidated Standards of Reporting Trials) and SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) extensions for randomised trials reporting surrogate endpoints, we undertook a scoping review, e-Delphi study, consensus meeting, and a web survey to examine current definitions and stakeholder (including clinicians, trial investigators, patients and public partners, journal editors, and health technology experts) interpretations of surrogate endpoints as primary outcome measures in trials.FindingsCurrent surrogate endpoint definitional frameworks are inconsistent and unclear. Surrogate endpoints are used in trials as a substitute of the treatment effects of an intervention on the target outcome(s) of ultimate interest, events measuring how patients feel, function, or survive. Traditionally the consideration of surrogate endpoints in trials has focused on biomarkers (e.g., HDL cholesterol, blood pressure, tumour response), especially in the medical product regulatory setting. Nevertheless, the concept of surrogacy in trials is potentially broader. Intermediate outcomes that include a measure of function or symptoms (e.g., angina frequency, exercise tolerance) can also be used as substitute for target outcomes (e.g., all-cause mortality)-thereby acting as surrogate endpoints. However, we found a lack of consensus among stakeholders on accepting and interpreting intermediate outcomes in trials as surrogate endpoints or target outcomes. In our assessment, patients and health technology assessment experts appeared more likely to consider intermediate outcomes to be surrogate endpoints than clinicians and regulators.InterpretationThere is an urgent need for better understanding and reporting on the use of surrogate endpoints, especially in the setting of interventional trials. We provide a framework for the definition of surrogate endpoints (biomarkers and intermediate outcomes) and target outcomes in trials to improve future reporting and aid stakeholders' interpretation and use of trial surrogate endpoint evidence.FundingSPIRIT-SURROGATE/CONSORT-SURROGATE project is Medical Research Council Better Research Better Health (MR/V038400/1) funded.

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.

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How to use frailtypack for validating failure-time surrogate endpoints using individual patient data from meta-analyses of randomized controlled trials.

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How to use frailtypack for validating failure-time surrogate endpoints using individual patient data from meta-analyses of randomized controlled trials.

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