PURPOSE - Intermittent androgen deprivation (IAD) has been widely tested in prostate cancer. However, phase III trials testing continuous androgen deprivation (CAD) versus IAD have reached inconclusive and seemingly contradictory results.
Different design and conduct issues must be critically evaluated to better interpret the results.
PATIENTS AND METHODS - Seven published phase III trials were examined for prespecified design and outcomes. Treatment specifications; primary end point; superiority versus noninferiority design assumptions, including magnitude of assumed versus observed noninferiority margin (NIM); duration of follow-up; and quality-of-life (QOL) outcomes were considered in terms of the results and conclusions reported.
RESULTS - Five trials had a superiority and three had a noninferiority primary hypothesis. Only three trials had a uniform population and overall survival (OS) end point. All trials observed better outcomes in terms of OS and progression-free survival (PFS) than assumed at time of study design, translating into prespecified NIMs or hazard ratios that reflected larger absolute differences in OS or PFS between arms. Lower-than-expected event rates also reduced statistical power for the trials. Other factors, including length of follow-up, cause of death, QOL, and primary end point, and their impact on trial interpretation are discussed.
CONCLUSIONS - No trial to date has demonstrated survival superiority of IAD compared with CAD. Trials concluding IAD is noninferior to CAD were based on wide NIMs that included clinically important survival differences, not likely to be considered comparable by physicians or patients. Interim analyses relying on short follow-up and including a majority of non-prostate cancer deaths will favor a noninferiority conclusion and should be interpreted cautiously. Adequate follow-up is required to ensure capture of prostate cancer deaths in both superiority and noninferiority trials.
Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2015 Nov 09 [Epub ahead of print]
Maha Hussain, Catherine Tangen, Celestia Higano, Nicholas Vogelzang, Ian Thompson
Maha Hussain, University of Michigan Comprehensive Cancer Center, Ann Arbor, MI; Catherine Tangen, SWOG Statistical Center; Celestia Higano, University of Washington, Seattle, WA; Nicholas Vogelzang, US Oncology, Las Vegas, NV; and Ian Thompson, University of Texas Health Science Center, San Antonio, TX. Maha Hussain, University of Michigan Comprehensive Cancer Center, Ann Arbor, MI; Catherine Tangen, SWOG Statistical Center; Celestia Higano, University of Washington, Seattle, WA; Nicholas Vogelzang, US Oncology, Las Vegas, NV; and Ian Thompson, University of Texas Health Science Center, San Antonio, TX. , Maha Hussain, University of Michigan Comprehensive Cancer Center, Ann Arbor, MI; Catherine Tangen, SWOG Statistical Center; Celestia Higano, University of Washington, Seattle, WA; Nicholas Vogelzang, US Oncology, Las Vegas, NV; and Ian Thompson, University of Texas Health Science Center, San Antonio, TX. , Maha Hussain, University of Michigan Comprehensive Cancer Center, Ann Arbor, MI; Catherine Tangen, SWOG Statistical Center; Celestia Higano, University of Washington, Seattle, WA; Nicholas Vogelzang, US Oncology, Las Vegas, NV; and Ian Thompson, University of Texas Health Science Center, San Antonio, TX. , Maha Hussain, University of Michigan Comprehensive Cancer Center, Ann Arbor, MI; Catherine Tangen, SWOG Statistical Center; Celestia Higano, University of Washington, Seattle, WA; Nicholas Vogelzang, US Oncology, Las Vegas, NV; and Ian Thompson, University of Texas Health Science Center, San Antonio, TX.