Clarifying the causal contrast: An empirical example applying the prevalent new user study design.

Area of Science:

• Cardiovascular Disease Epidemiology
• Pharmacovigilance
• Real-World Evidence Studies

Background:

• New user designs in pharmacoepidemiology are crucial for understanding drug safety and efficacy.
• Incorporating patients who switch treatments adds complexity to new user designs.
• Distinguishing between incident new users and switchers is vital for accurate risk estimation.

Purpose of the Study:

• To evaluate the impact of including treatment switchers in new user designs on the estimated hazard ratio (HR) of hospitalized heart failure.
• To compare the risk of heart failure between patients initiating GLP-1 receptor agonists (GLP-1 RA) and sulfonylureas (SU).
• To analyze three distinct patient populations: incident new users, switchers, and a combined group.

Main Methods:

• Utilized MarketScan claims data from 2000-2014 for analysis.
• Employed time-conditional propensity scores (TCPS) and time-stratified standardized morbidity ratio (SMR) weighting to control for confounding.
• Calculated hazard ratios for hospitalized heart failure across different patient cohorts.

Main Results:

• Identified 76,179 GLP-1 RA new users, with 12% switching from SU within 30 days.
• GLP-1 RA demonstrated a protective effect against heart failure in incident new users (adjHR_SMR = 0.74 [0.69, 0.80]).
• No significant protective effect was observed in switchers (adjHR_SMR = 0.99 [0.83, 1.18]), with results consistent across TCPS and SMR weighting.

Conclusions:

• GLP-1 RA exhibits a protective effect for incident new users but not for those switching from SU.
• Combining incident users and switchers can obscure important treatment effect heterogeneity.
• Careful consideration of patient treatment history is essential for robust confounding control in pharmacoepidemiologic studies.