Dose Response with No Delta? A Causal Inference Application

Benjamin Ackerman Co-Author
Johnson & Johnson Innovative Medicine
 
Daniel Backenroth Co-Author
Johnson & Johnson
 
Xiaoming Li Co-Author
Johnson and Johnson Innovative Medicine
 
Zijiang Yang First Author
Johnson and Johnson
 
Zijiang Yang Presenting Author
Johnson and Johnson
 
Thursday, Aug 7: 9:20 AM - 9:35 AM
1475 
Contributed Papers 
Music City Center 
In a treat-through study evaluating two therapeutic doses, randomization occurred at Week 0, and then after the same induction treatment, patients initiated one of the two randomized doses. A key question arises when evaluating the dose response at study completion: How should we account for differences observed at intermediate milestones, when patients received identical treatment prior to initiating their randomized dose? Specifically, what if the high dose had an early advantage that it maintained through the long term, or if the low dose outperformed in the short term but was eventually overtaken by the high dose? This presentation explores the use of propensity score weighting to analyze such data, adjusting for potential treatment differences (delta) between the two doses and assess the dose response when there is, or is not, a detectable delta at the study's conclusion. Simulation analyses were carried out to evaluate its operating characteristics.

Keywords

Causal Inference

Propensity Score

Dose response

Clinical trial design 

Main Sponsor

Biopharmaceutical Section