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Estimation of high-dimensional propensity scores with multiple exposure levels
Maria Eberg1, Robert W Platt1,2,3,4, Pauline Reynier1
1Centre for Clinical Epidemiology, Lady Davis Research Institute, Jewish General Hospital, Montreal, Quebec, Canada.
Pharmacoepidemiology and Drug Safety
|October 2, 2019
Summary
High-dimensional propensity scores (HDPS) effectively handle multiple treatment groups, offering a valid method for confounder control in drug studies. This approach provides reliable estimates when comparing multiple smoking cessation medications.
Area of Science:
- Pharmacoepidemiology
- Biostatistics
- Health Services Research
Background:
- High-dimensional propensity scores (HDPS) are established for binary treatment comparisons.
- Limited research exists on HDPS performance with more than two exposure levels.
Purpose of the Study:
- Adapt the HDPS algorithm for multilevel treatments.
- Compare HDPS estimates with pairwise comparisons using real-world data.
- Evaluate confounder control in multilevel treatment settings.
Main Methods:
- Retrospective cohort study of cardiovascular events linked to three smoking cessation drugs (varenicline, bupropion, nicotine replacement therapy [NRT]).
- Applied binary and multinomial HDPS models adjusting for pre-specified and empirically-selected covariates.
- Estimated treatment effects using Cox proportional hazards models after propensity score trimming.
Main Results:
- Multinomial HDPS models yielded slightly more protective effect estimates compared to pairwise comparisons.
- Varenicline vs. NRT: HRMultinomial = 0.60-0.62 vs. HRPairwise = 0.64.
- Bupropion vs. NRT: HRMultinomial = 0.70-0.72 vs. HRPairwise = 0.76.
- Similar trimming rates were observed between the multinomial and pairwise approaches.
Conclusions:
- The extension of HDPS to multilevel exposures is a valid and practical confounder control method.
- This approach is beneficial for comparing different drug classes or molecules for the same indication.
- Multinomial HDPS offers a robust alternative for complex treatment comparisons in pharmacoepidemiology.
Keywords:
comparative effectivenesshigh-dimensional propensity scoresmultilevel exposurepharmacoepidemiologyMore Related Videos
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