Abstract
In phase II cancer trials, tumour response is either the primary or an important secondary endpoint. Tumour response is a binary composite endpoint determined, according to the Response Evaluation Criteria in Solid Tumors, by (1) whether the percentage change in tumour size is greater than a prescribed threshold and (2) (binary) criteria such as whether a patient develops new lesions. Further binary criteria, such as death or serious toxicity, may be added to these criteria. The probability of tumour response (i.e. ‘success’ on the composite endpoint) would usually be estimated simply as the proportion of successes among patients. This approach uses the tumour size variable only through a discretised form, namely whether or not it is above the threshold. In this article, we propose a method that also estimates the probability of success but that gains precision by using the information on the undiscretised (i.e. continuous) tumour size variable. This approach can also be used to increase the power to detect a difference between the probabilities of success under two different treatments in a comparative trial. We demonstrate these increases in precision and power using simulated data. We also apply the method to real data from a phase II cancer trial and show that it results in a considerably narrower confidence interval for the probability of tumour response.
Highlights
Phase II cancer trials are conducted to decide whether an experimental cancer treatment is worth testing in a large, costly phase III trial
We have proposed and assessed the augmented binary method, which makes inference about a composite success outcome defined by a continuous outcome and a binary outcome, using the continuous component to improve precision
This method is motivated by phase II cancer trials, where tumour response is a composite endpoint defined by continuous tumour shrinkage and binary non-shrinkage failure indicators, such as whether new lesions are observed
Summary
Phase II cancer trials are conducted to decide whether an experimental cancer treatment is worth testing in a large, costly phase III trial. SEAMAN agents, SD is included in treatment success, and the proportion of patients that are successful is called the disease control rate (DCR) Both ORR and DCR are partly determined from a dichotomisation of the underlying continuous shrinkage in the total diameter of pre-specified target lesions ( referred to as tumour size). To improve precision in estimation of a treatment’s ORR or DCR, we consider a composite ‘success’ endpoint determined by (1) the change in tumour size; (2) the appearance of new lesions or increase in non-target lesion size; and possibly (3) toxicity and/or death. This success endpoint has both continuous and binary components. We compare this power with those of a logistic regression approach and an approach proposed by Karrison et al [6], which directly tests the continuous shrinkage using a nonparametric test
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