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In this work, we model the risk of hospitalization for a large number of drug-disease combinations. Our methodology is akin to genome-wide association studies (GWAS), in which a simple model is used to estimate the effect of a large number of loci in a hypothesis-free manner. As in GWAS, this screen risks spurious relationships and requires further analysis, but complements target-driven repurposing.

observationIntroduction, p.2

The GWAS analogy is one of the clearest framings in the paper. It belongs in the abstract. A short sentence on the broad enumeration step and the multiplicity correction does enough to place the work as a screen, not another pair-specific observational study.

weaknessCox Regression, p.6

§2.5 and the Discussion already concede that dosage, duration, and switching aren't in the data. Even so, the paper keeps calling this a treatment-effect screen. Either tone the language down to a baseline-exposure association screen, or add landmark sensitivity analyses at 1, 3, 5, and 10 years.

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