We’re developing a general-purpose causal inference platform to estimate drug effects on a large scale, primarily using a new user cohort study design. As a first step, we’d like to assess its performance using an established ground truth set, and consider using the OMOP drug safety reference set and replicating the results in Ryan at al’s paper (link). We’d appreciate any help and thoughts re the following:
- For a given target drug, the control cohort (or comparator group) is defined using an active comparator drug (or set of such drugs) which “shares the same indication as the target drug but falls within a different therapeutic class”. What vocabularies were used to determine drugs’ indication and therapeutic class?
- AFAIK indication and therapeutic class are characteristics of drugs, but the reference set’s concepts are ingredients. So, what drugs are considered for a given active ingredient, all or some subset (e.g., having an ingredient as the single active one)?
- Also, the mapping of drugs, and even more so ingredients, to indication/therapeutic class is a one-to-many mapping; does “same indication” requires that the target and comparator drugs have identical sets of indications or just that they share an indication? Similarly, does “different therapeutic class” mean disjoint sets or non-identical?
- Finally, is the specific list of the drugs used in each comparison available and can be shared?
In addition, we’d be happy to learn of any additional reference sets that can be used, or studies we can try to replicate, to evaluate our platform performance.