Meet the Expert in the Real-World: Real-World Data in Drug Development and Utilization - Part 2

Session Description

Real-world pharmacological data analysis is generally subject to several sources of bias, which may undermine its internal validity. Information bias is induced by measurement error in any of the variables, but most importantly the drug exposure or the outcome. Selection bias results from the inclusion or exclusion of subjects on the basis of common effects of both the drug exposure and the outcome under study. Finally, confounding bias results from the imbalances in baseline covariates between the subjects exposed to the drug under study and those in the comparison group, which are also predictors of the outcome under study. While randomization balances the groups with respect to both measured and unmeasured covariates, observational studies are limited with respect to the latter, making confounding an important source of bias. Advances have been made in the design and analysis of pharmacoepidemiological studies based on RWD. This part of the workshop will present the novel epidemiologic and statistical methods used to improve causal inference in studies using real-world data, with a particular emphasis on study design and propensity score methodology for confounding adjustment.

Learning Objectives

1. Upon completion, participants will be able to understand the process of selection of a study outcome that reflect the real-world-data study question and address key considerations for the validation of real-world endpoints.
2. Upon completion, participants will be able to identify data sources and data collection approaches to capture relevant real-world patient populations and information.
3. Upon completion, participants will be able to discuss epidemiological and statistical methods for generating evidence to evaluate the effectiveness and safety of new and existing products, and various study designs that can be used to minimize bias.

Session Schedule

1:30 PM - 1:35 PM MT
Introduction
Naomi Gronich, MD and Mohamed Elmeliegy, PhD, MBA

1:35 PM - 2:00 PM MT
Do's and Don'ts: Choosing the Right Statistical Methods to Generate Real-World Evidence
Elisabetta Patorno, MD, PhD

2:00 PM - 2:30 PM MT
Panel Discussion and Q&A