Drug exposure in register-based research - An expert-opinion based evaluation of methods
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CitationTanskanen A. Taipale H. Koponen M. Tolppanen AM. Hartikainen S. Ahonen R. Tiihonen J. (2017). Drug exposure in register-based research - An expert-opinion based evaluation of methods. PLOS ONE, 12 (9) , e0184070. 10.1371/journal.pone.0184070.
In register-based pharmacoepidemiological studies, construction of drug exposure periods from drug purchases is a major methodological challenge. Various methods have been applied but their validity is rarely evaluated. Our objective was to conduct an expert-opinion based evaluation of the correctness of drug use periods produced by different methods.
Drug use periods were calculated with three fixed methods: time windows, assumption of one Defined Daily Dose (DDD) per day and one tablet per day, and with PRE2DUP that is based on modelling of individual drug purchasing behavior. Expert-opinion based evaluation was conducted with 200 randomly selected purchase histories of warfarin, bisoprolol, simvastatin, risperidone and mirtazapine in the MEDALZ-2005 cohort (28,093 persons with Alzheimer’s disease). Two experts reviewed purchase histories and judged which methods had joined correct purchases and gave correct duration for each of 1000 drug exposure periods.
The evaluated correctness of drug use periods was 70–94% for PRE2DUP, and depending on grace periods and time window lengths 0–73% for tablet methods, 0–41% for DDD methods and 0–11% for time window methods. The highest rate of evaluated correct solutions for each method class were observed for 1 tablet per day with 180 days grace period (TAB_1_180, 43–73%), and 1 DDD per day with 180 days grace period (1–41%). Time window methods produced at maximum only 11% correct solutions. The best performing fixed method TAB_1_180 reached highest correctness for simvastatin 73% (95% CI 65–81%) whereas 89% (95% CI 84–94%) of PRE2DUP periods were judged as correct.
This study shows inaccuracy of fixed methods and the urgent need for new data-driven methods. In the expert-opinion based evaluation, the lowest error rates were observed with data-driven method PRE2DUP.