A Surrogate Endpoint Based Provisional Approval Causal Roadmap
Peter B. Gilbert, James Peng, Larry Han, Theis Lange, Yun Lu, Lei Nie,, Mei-Chiung Shih, Salina P. Waddy, Ken Wiley, Margot Yann, Zafar Zafari,, Debashis Ghosh, Dean Follmann, Michal Juraska, Iv\'an D\'iaz

TL;DR
This paper develops a causal framework for provisional drug approval using surrogate endpoints, combining observational and phase 3 study data to estimate treatment effects with uncertainty bounds, especially for rare diseases.
Contribution
It introduces a surrogate-based approval causal roadmap that accounts for surrogate imperfection and data transport issues, with new estimators and inference methods.
Findings
Developed two estimators for treatment effect with uncertainty bounds.
Evaluated estimators' performance through simulation studies.
Illustrated the approach with GBS vaccine development case.
Abstract
For many rare diseases with no approved preventive interventions, promising interventions exist, yet it has been difficult to conduct a pivotal phase 3 trial that could provide direct evidence demonstrating a beneficial effect on the target disease outcome. When a promising putative surrogate endpoint(s) for the target outcome is available, surrogate-based provisional approval of an intervention may be pursued. We apply the Causal Roadmap rubric to define a surrogate endpoint based provisional approval causal roadmap, which combines observational study data that estimates the relationship between the putative surrogate and the target outcome, with a phase 3 surrogate endpoint study that collects the same data but is very under-powered to assess the treatment effect (TE) on the target outcome. The objective is conservative estimation/inference for the TE with an estimated lower…
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Taxonomy
TopicsInternational Arbitration and Investment Law · Intellectual Property and Patents · Law, Economics, and Judicial Systems
