SC09 - Intermediate Pharmacoepidemiology: Approaches to Unmeasured Confounders

Live Q&A Session
November 23, 2020
9:00 am EST
Watch the Q&A

Description: This course will introduce students to multiple approaches to addressing unmeasured confounders through study design and analysis, the requirements and assumptions of each, and an opportunity to compare these approaches through facilitated discussion of a case study.

Objectives:
Identify common unmeasured covariates in pharmacoepidemiology and the types of bias that can result.
Describe multiple approaches to addressing unmeasured covariates in pharmacoepidemiology through study design and analysis.
Understand the assumptions of each approach, ways of evaluating these assumptions, and when they are likely to be violated.
Compare these methods in a novel setting to identify trade-offs and considerations.

Online Modules
Introductory Video: This short video will provide an overview of the course objectives and introduce the presenting Faculty.
Use of study design to control unmeasured confounding: During the first set of modules, Drs Lund, Raman, and Gokhale will introduce three ways in which study design can be used to limit bias due to unmeasured confounding: a) the active comparator new user (ACNU) design, b) self-controlled designs, and c) instrumental variable designs. Faculty will provide foundational knowledge about each approach illustrated through real-world examples.

· Module 1: Active comparator / new user study design with Dr. Jennifer Lund
· Module 2: Self-controlled study designs with Dr. Sudha Raman
· Module 3: Instrumental variable study designs with Dr. Mugdha Gokhale

Analytic approaches to unmeasured confounding: During the second set of modules, Drs Lund, Stürmer, and Jonsson Funk will introduce three analytic approaches to reduce bias due to unmeasured confounding: a) proxy measures, b) external control for confounding, and c) quantitative bias analysis. Faculty will provide foundational knowledge about each approach illustrated through real-world examples.

· Module 4: Proxy measures with Dr. Jennifer Lund
· Module 5: Quantitative bias analysis with Dr. Michele Jonsson Funk
· Module 6: External control for confounding with Dr. Til Stürmer

Interactive Case Study and Q&A Session with Course Faculty
(60 minutes – November 23, 9-10a eastern time)

Welcome and Introduction (5 minutes)
A quick introduction of the topics covered in online material and faculty members.

Interactive Case Study led by Dr. Michele Jonsson Funk (20 minutes)
The interactive case study will pose a hypothetical research question and engage students in thinking about the likely unmeasured covariates, considering how each of the approaches might be used in that setting, and weighing the pros/cons of each. This case-study will provide integration across the approaches and give students an opportunity to work through the selection of an appropriate strategy for addressing important unmeasured covariates in light of real-world constraints.

Panel Q & A with all course Faculty (20 minutes)

Conclusion (5 minutes)