DeepAI AI Chat
Log In Sign Up

Assessing contribution of treatment phases through tipping point analyses via counterfactual elicitation using rank preserving structural failure time models

07/03/2021
by   Sudipta Bhattacharya, et al.
0

This article provides a novel approach to assess the importance of specific treatment phases within a treatment regimen through tipping point analyses (TPA) of a time-to-event endpoint using rank-preserving-structural-failure-time (RPSFT) modelling. In oncology clinical research, an experimental treatment is often added to the standard of care therapy in multiple treatment phases to improve patient outcomes. When the resulting new regimen provides a meaningful benefit over standard of care, gaining insights into the contribution of each treatment phase becomes important to properly guide clinical practice. New statistical approaches are needed since traditional methods are inadequate in answering such questions. RPSFT modelling is an approach for causal inference, typically used to adjust for treatment switching in randomized clinical trials with time-to-event endpoints. A tipping-point analysis is commonly used in situations where a statistically significant treatment effect is suspected to be an artifact of missing or unobserved data rather than a real treatment difference. The methodology proposed in this article is an amalgamation of these two ideas to investigate the contribution of a specific component of a regimen comprising multiple treatment phases. We provide different variants of the method and construct indices of contribution of a treatment phase to the overall benefit of a regimen that facilitates interpretation of results. The proposed approaches are illustrated with findings from a recently concluded, real-life phase 3 cancer clinical trial. We conclude with several considerations and recommendations for practical implementation of this new methodology.

READ FULL TEXT

page 32

page 33

page 34

page 35

12/20/2021

The Predictive Individual Effect for Survival Data

The call for patient-focused drug development is loud and clear, as expr...
08/01/2019

Teasing out the overall survival benefit with adjustment for treatment switching to other therapies

In oncology clinical trials, characterizing the long-term overall surviv...
07/09/2018

Predictive Directions for Individualized Treatment Selection in Clinical Trials

In many clinical trials, individuals in different subgroups have experie...
06/03/2022

Accurate collection of reasons for treatment discontinuation to better define estimands in clinical trials

Background: Reasons for treatment discontinuation are important not only...
06/09/2020

Endpoints for randomized controlled clinical trials for COVID-19 treatments

Introduction: Endpoint choice for randomized controlled trials of treatm...
10/31/2016

Function Driven Diffusion for Personalized Counterfactual Inference

We consider the problem of constructing diffusion operators high dimensi...