Real-world data (RWD) pharmacoepidemiology analysis: Constructed study design and performed statistical analysis on real-world data to inform clinical trial designs

Pharmacoepidemiology analysis of respiratory diseases (Asthma, COPD and Bronchiectasis)

Tools & Techniques

SQL (postgreSQL), R (RPostgreSQL, ggplot, epiR), Amazon RedShift, Github

Summary

Bronchiectasis (BE) is a significant but often overlooked, chronic airway disease that contributes considerably to both morbidity and mortality. Recent research indicates that individuals with BE frequently have comorbid airway conditions, particularly asthma and/or chronic obstructive pulmonary disease (COPD). Due to overlapping clinical symptoms with asthma and COPD, patients with BE frequently experience diagnostic delays, complicating patient characterization and potentially impacting treatment outcomes.

To better understand the epidemiology and clinical characteristics of patients with overlapping asthma, COPD, and BE, we conducted a pharmacoepidemiological analysis using the OPTUM® health claims database and the TriNetX® EHR dataset, which offers extensive and timely healthcare data. The main objective of this retrospective, observational study is to generate insights that will inform optimized treatment strategies and support the design of future clinical trials targeting these overlapping airway diseases. I’ve drafted the study protocol and statistical analysis plan (SAP) that will be used as a guide for future studies.

Info Notice: Results are confidential thus not shown here