Toggle Main Menu Toggle Search

Open Access padlockePrints

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

Lookup NU author(s): Professor James WasonORCiD



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


© 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. 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.

Publication metadata

Author(s): Lin C-J, Wason JMS

Publication type: Article

Publication status: Published

Journal: Statistics in Medicine

Year: 2017

Volume: 36

Issue: 29

Pages: 4616-4626

Print publication date: 20/12/2017

Online publication date: 28/08/2017

Acceptance date: 07/08/2017

Date deposited: 13/12/2017

ISSN (print): 0277-6715

ISSN (electronic): 1097-0258

Publisher: John Wiley and Sons Ltd


DOI: 10.1002/sim.7453


Altmetrics provided by Altmetric