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Research Letter
June 2018

Evaluating Treatment Effect Based on Duration of Response for a Comparative Oncology Study

Author Affiliations
  • 1Pfizer Inc, Groton, Connecticut
  • 2Stanford Medical School, Stanford University, Stanford, California
  • 3Pfizer Inc, New York, New York
  • 4Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
  • 5Department of Biostatistics, Harvard University, Boston, Massachusetts
JAMA Oncol. 2018;4(6):874-876. doi:10.1001/jamaoncol.2018.0275

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

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