Darius N Lakdawalla1, Jason Shafrin2, Ningqi Hou2, Desi Peneva2, Seanna Vine2, Jinhee Park3, Jie Zhang3, Ron Brookmeyer4, Robert A Figlin5. 1. Leonard D. Schaeffer Center for Health Policy and Economics, University of Southern California, Los Angeles, CA, USA. Electronic address: dlakdawa@usc.edu. 2. Precision Health Economics, Los Angeles, CA, USA. 3. Novartis Pharmaceuticals, East Hanover, NJ, USA. 4. University of California, Los Angeles, CA, USA. 5. Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Abstract
OBJECTIVES: To measure the relationship between randomized controlled trial (RCT) efficacy and real-world effectiveness for oncology treatments as well as how this relationship varies depending on an RCT's use of surrogate versus overall survival (OS) endpoints. METHODS: We abstracted treatment efficacy measures from 21 phase III RCTs reporting OS and either progression-free survival or time to progression endpoints in breast, colorectal, lung, ovarian, and pancreatic cancers. For these treatments, we estimated real-world OS as the mortality hazard ratio (RW MHR) among patients meeting RCT inclusion criteria in Surveillance and Epidemiology End Results-Medicare data. The primary outcome variable was real-world OS observed in the Surveillance and Epidemiology End Results-Medicare data. We used a Cox proportional hazard regression model to calibrate the differences between RW MHR and the hazard ratios on the basis of RCTs using either OS (RCT MHR) or progression-free survival/time to progression surrogate (RCT surrogate hazard ratio [SHR]) endpoints. RESULTS: Treatment arm therapies reduced mortality in RCTs relative to controls (average RCT MHR = 0.85; range 0.56-1.10) and lowered progression (average RCT SHR = 0.73; range 0.43-1.03). Among real-world patients who used either the treatment or the control arm regimens evaluated in the relevant RCT, RW MHRs were 0.6% (95% confidence interval -3.5% to 4.8%) higher than RCT MHRs, and RW MHRs were 15.7% (95% confidence interval 11.0% to 20.5%) higher than RCT SHRs. CONCLUSIONS: Real-world OS treatment benefits were similar to those observed in RCTs based on OS endpoints, but were 16% less than RCT efficacy estimates based on surrogate endpoints. These results, however, varied by tumor and line of therapy.
OBJECTIVES: To measure the relationship between randomized controlled trial (RCT) efficacy and real-world effectiveness for oncology treatments as well as how this relationship varies depending on an RCT's use of surrogate versus overall survival (OS) endpoints. METHODS: We abstracted treatment efficacy measures from 21 phase III RCTs reporting OS and either progression-free survival or time to progression endpoints in breast, colorectal, lung, ovarian, and pancreatic cancers. For these treatments, we estimated real-world OS as the mortality hazard ratio (RW MHR) among patients meeting RCT inclusion criteria in Surveillance and Epidemiology End Results-Medicare data. The primary outcome variable was real-world OS observed in the Surveillance and Epidemiology End Results-Medicare data. We used a Cox proportional hazard regression model to calibrate the differences between RW MHR and the hazard ratios on the basis of RCTs using either OS (RCT MHR) or progression-free survival/time to progression surrogate (RCT surrogate hazard ratio [SHR]) endpoints. RESULTS: Treatment arm therapies reduced mortality in RCTs relative to controls (average RCT MHR = 0.85; range 0.56-1.10) and lowered progression (average RCT SHR = 0.73; range 0.43-1.03). Among real-world patients who used either the treatment or the control arm regimens evaluated in the relevant RCT, RW MHRs were 0.6% (95% confidence interval -3.5% to 4.8%) higher than RCT MHRs, and RW MHRs were 15.7% (95% confidence interval 11.0% to 20.5%) higher than RCT SHRs. CONCLUSIONS: Real-world OS treatment benefits were similar to those observed in RCTs based on OS endpoints, but were 16% less than RCT efficacy estimates based on surrogate endpoints. These results, however, varied by tumor and line of therapy.
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