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Predicting Real-World Effectiveness of Cancer Therapies Using OS and PFS Clinical Trials Endpoints

Written By: Jason Shafrin - May• 30•17

Clinical trials for cancer treatments aim to demonstrate whether one treatment is better than another. What is of most interest to patients, providers and payers, however, is which treatment works best in the real-world, not in a randomized controlled trial. Further, clinical trials often use progression free survival to measure treatment outcomes rather than overall survival. Thus, the question remains, how well do clinical trials predict real-world survival and–in addition–does this prediction depend on whether overall survival or a surrogate measure are used as the endpoint of the randomized controlled trial.

Myself and co-authors Darius N. Lakdawalla, Jason Shafrin, Ningqi Hou, Desi Peneva, Seanna Vine, Jinhee Park, Jie Zhang, Ron Brookmeyer, and Robert A. Figlin aim to answer that question in our study “Predicting Real-World Effectiveness of Cancer Therapies Using Overall Survival and Progression-Free Survival from Clinical Trials: Empirical Evidence for the ASCO Value Framework.” The abstract for this paper is below.

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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One Comment

  1. It’s really great post.I got some good information.

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