Rescue Drugs, Data Imputation and Study Outcomes in Analgesic Clinical Trials

In placebo-controlled pain studies, provisions for study subjects to receive adequate analgesic therapy must be made. As such, most protocols allow study subjects to receive a prespecified regimen of rescue drugs as-needed. The selection of a rescue regimen is a critical experimental design choice.

Despite the importance of rescue as a study design feature, until recently there were no published review articles or meta-analyses focusing on the impact of rescue therapy on experimental outcomes. In this talk, Dr. Singla will discuss findings from a recently published meta-analysis relevant to rescue therapy, data imputation and study outcomes. For this paper, Dr. Singla and colleagues reviewed literature on every published clinical trial using the bunionectomy surgical pain model. The team analyzed the effects of studies’ various rescue regimens on both subject dropout rates and treatment/ placebo effect sizes, as well as reviewing imputation methods for handling missing data.

The goals of this talk are to (1) create a framework for discussion of rescue as a study design feature, (2) discuss the interplay between data imputation techniques and rescue drugs, and (3) inform researchers regarding the impact of data imputation techniques on the validity of study conclusions.