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Improving phase II oncology trials using best observed RECIST response as an endpoint by modelling continuous tumour measurements.

Published version
Peer-reviewed

Type

Article

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Authors

Wason, James MS 

Abstract

In many phase II trials in solid tumours, patients are assessed using endpoints based on the Response Evaluation Criteria in Solid Tumours (RECIST) scale. Often, analyses are based on the response rate. This is the proportion of patients who have an observed tumour shrinkage above a predefined level and no new tumour lesions. The augmented binary method has been proposed to improve the precision of the estimator of the response rate. The method involves modelling the tumour shrinkage to avoid dichotomising it. However, in many trials the best observed response is used as the primary outcome. In such trials, patients are followed until progression, and their best observed RECIST outcome is used as the primary endpoint. In this paper, we propose a method that extends the augmented binary method so that it can be used when the outcome is best observed response. We show through simulated data and data from a real phase II cancer trial that this method improves power in both single-arm and randomised trials. The average gain in power compared to the traditional analysis is equivalent to approximately a 35% increase in sample size. A modified version of the method is proposed to reduce the computational effort required. We show this modified method maintains much of the efficiency advantages.

Description

Keywords

continuous tumour shrinkage endpoints, longitudinal model, phase II cancer trial, Clinical Trials, Phase II as Topic, Colonic Neoplasms, Computer Simulation, Disease Progression, Endpoint Determination, Humans, Logistic Models, Medical Oncology, Neoplasms, Randomized Controlled Trials as Topic, Research Design, Treatment Outcome

Journal Title

Stat Med

Conference Name

Journal ISSN

0277-6715
1097-0258

Volume Title

36

Publisher

Wiley
Sponsorship
Medical Research Council (MR/N028171/1)
Cancer Research UK (18113)