Author:
Lalagkas Panagiotis Nikolaos,Melamed Rachel Dania
Abstract
AbstractBackgroundCombinations of common drugs may, when taken together, have unexpected effects on cancer. It is not feasible to test for all combination drug effects in clinical trials, but in the real world, drugs are frequently taken in combination. Then, there may be undiscovered effects protecting users from cancer–or increasing their risk. By analyzing massive health claims data containing numerous people exposed to drug combinations, we have an opportunity to evaluate the association of drug combinations with cancer risk. Discovering these effects can not only contribute to prevention of cancer, but also suggest new uses for combinations to prevent or treat cancer.MethodOur approach emulates a randomized trial where one arm would have been assigned to take a particular drug alone, while the other arm takes it together with a second drug. Because discovery of associations from observational data is prone to spurious results due to confounding, we develop strategies to distinguish confounding from biomedically relevant findings.ResultsThis tactic allows us to systematically assess effects across over 9,000 drug combinations, on all common cancers. Through multiple sensitivity analyses we identify a robustly supported beneficial drug combination that may synergistically impact lipid levels to reduce risk of cancer.ConclusionsThis study demonstrates the importance of considering confounding factors in drug-wide studies. But, we also show that our method is able to uncover associations with robust support.ImpactSearching for combinations of factors impacting cancer is crucial, but these effects can only be systematically discovered through observational data analysis.
Publisher
Cold Spring Harbor Laboratory
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