Statistical Model to Determine the Relationship of Response and Survival in Patients With Advanced Ovarian Cancer Treated With Chemotherapy

Abstract

A statistically appropriate analysis of the association between survival and response measures in patients with ovarian cancer could help to define the role of response rate in planning, monitoring, and interpreting the results of clinical trials. This study was designed to investigate the relationship between antitumor response determined by clinical or pathological means and survival in patients with advanced ovarian cancer with no previous treatment. We focused on avoiding the limitations of the usual approach of comparing durations of survival for patients responding to therapy with those for nonresponders. A new meta-analytic statistical model we developed was used to analyze data from 26 randomized clinical trials published between 1975 and 1989. Our model incorporates intra-study and inter-study sources of variability in the estimates of response and survival. The study also addresses the methodological problems of evaluating response as a surrogate end point and the relevance of this association to clinical decision making and the design of clinical trials. For 13 studies in which response was pathologically assessed, an improvement in surgically documented complete response rate was associated with an increase in median survival. A similar but apparently smaller effect was found for the association between objective clinical response and median survival in the 25 studies reporting these data. These results suggest that therapeutic measures must produce large improvements in clinical response rates to achieve meaningful effects on complete response rate appears to be more strongly associated with increased median survival and, hence, might be used for interim monitoring in clinical trials, but the role of second-look procedures in clinical management is controversial.[J Natl Cancer Inst 84:407–114,1992]