Standardizing to specific target populations in distributed networks and multisite pharmacoepidemiologic studies

Area of Science:

• Pharmacoepidemiology
• Biostatistics
• Health Services Research

Background:

• Multisite and distributed network studies pool data to assess drug safety and effectiveness in diverse populations.
• Effect measure modifiers (EMMs) can influence study results, necessitating methods to improve precision and interpretability.

Purpose of the Study:

• To evaluate the impact of targeting specific populations using inverse odds weights (IOWs) on estimate precision and interpretability in multisite studies.
• To compare IOW-weighted estimates with standard methods in simulated and real-world pharmacoepidemiologic data.

Main Methods:

• Simulated a 4-site study, applying IOWs to standardize sites to resemble smaller sites before pooling estimates.
• Created an artificial distributed network in CPRD Aurum to compare metformin and sulfonylurea initiators regarding mortality.
• Used inverse variance weights (IVWs) to combine estimates after IOW standardization.

Main Results:

• In simulations, IOWs reduced estimate differences and increased precision when targeting smaller sites.
• The IOW + IVW approach in the CPRD Aurum study yielded a more precise mortality risk difference estimate for the targeted smallest region.

Conclusions:

• Targeting populations with IOWs in multisite and distributed network studies can enhance the precision and interpretability of drug safety and effectiveness estimates.
• This approach is valuable in pharmacoepidemiologic research, especially when EMMs are present.