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Determination of the most appropriate method for extrapolating overall survival data from a placebo-controlled clinical trial of lenvatinib for progressive, radioiodine-refractory differentiated thyroid cancer

Authors Tremblay G, Livings C, Crowe L, Kapetanakis V, Briggs A

Received 1 March 2016

Accepted for publication 13 April 2016

Published 30 June 2016 Volume 2016:8 Pages 323—333

DOI https://doi.org/10.2147/CEOR.S107498

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Lucy Goodman

Peer reviewer comments 3

Editor who approved publication: Professor Giorgio Lorenzo Colombo


Gabriel Tremblay,1 Christopher Livings,2 Lydia Crowe,2 Venediktos Kapetanakis,2 Andrew Briggs3

1Global Health Economics and Health Technology Assessment, Eisai Inc., Woodcliff Lake, NJ, USA; 2Health Economics, Decision Resources Group, Bicester, Oxfordshire, 3Health Economics and Health Technology Assessment, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK

Background:
Cost-effectiveness models for the treatment of long-term conditions often require information on survival beyond the period of available data.
Objectives: This paper aims to identify a robust and reliable method for the extrapolation of overall survival (OS) in patients with radioiodine-refractory differentiated thyroid cancer receiving lenvatinib or placebo.
Methods: Data from 392 patients (lenvatinib: 261, placebo: 131) from the SELECT trial are used over a 34-month period of follow-up. A previously published criterion-based approach is employed to ascertain credible estimates of OS beyond the trial data. Parametric models with and without a treatment covariate and piecewise models are used to extrapolate OS, and a holistic approach, where a series of statistical and visual tests are considered collectively, is taken in determining the most appropriate extrapolation model.
Results: A piecewise model, in which the Kaplan–Meier survivor function is used over the trial period and an extrapolated tail is based on the Exponential distribution, is identified as the optimal model.
Conclusion:
In the absence of long-term survival estimates from clinical trials, survival estimates often need to be extrapolated from the available data. The use of a systematic method based on a priori determined selection criteria provides a transparent approach and reduces the risk of bias. The extrapolated OS estimates will be used to investigate the potential long-term benefits of lenvatinib in the treatment of radioiodine-refractory differentiated thyroid cancer patients and populate future cost-effectiveness analyses.

Keywords:
survival analysis, parametric extrapolation, piecewise models, decision criteria, radioiodine-refractory differentiated thyroid cancer

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