Quantitative procedures for analyzing data for progression-free survival (PFS) and overall survival are generally well established. However, it is not clear how to analyze data efficiently for duration of response (DOR), a clinically important end point that is related to quality of life and is endorsed by regulatory agencies for drug evaluation.1,2 Duration of response is the time from response (R) to progression/death (P/D). The existing statistical procedures for DOR are valid when certain model assumptions are correctly specified.3 Therefore, in a typical report of a clinical study, DOR is summarized descriptively. Moreover, the Kaplan-Meier curves (KMCs) to estimate the distribution of DOR are generally based on observations from responders and may be biased owing to dependent censoring.2 Here, we present a simple, intuitive procedure to estimate mean DOR in a time window for which KMCs for PFS are well defined. We illustrate this method with data from a clinical trial, PROFILE-1014, to evaluate crizotinib vs chemotherapy for patients with ALK-positive lung cancer.4
Huang B, Tian L, Talukder E, Rothenberg M, Kim DH, Wei L. Evaluating Treatment Effect Based on Duration of Response for a Comparative Oncology Study. JAMA Oncol. 2018;4(6):874–876. doi:10.1001/jamaoncol.2018.0275
Customize your JAMA Network experience by selecting one or more topics from the list below.
Create a personal account or sign in to: