Persistence of statin treatment – the impact of analytic method when estimating drug survival

Background: There is ample evidence for several pharmaceutical treatments that adherence in terms of treatment duration and dose is suboptimal. The actual drug intake cannot be observed directly in prescription databases, which only register drug redeemed and a limited number of patient characteristics. Consequently, the actual dose and duration of treatment must be inferred from observed redemptions. Persistence can then be expressed as treatment duration (also referred to as drug survival). Method: We used data from the Norwegian Prescription Database (NorPD) on redemptions of statins (ATCcode C10AA) for the period 2010-2019 to explore three methods for determining prescription durations and in turn persistence (treatment duration): (i) The DDD-method using the number of DDD redeemed; (ii) The dose-unit approach using the number of tablets redeemed; (iii) The reverse waiting time distribution method (WTD), which estimates prescription duration as the 90th percentile of the distribution within which patients in ongoing treatment will have a new subsequent redemption. The three methods for estimating prescription duration were then used to estimate treatment duration using Kaplan Meier (KM) survival functions. For the DDD-method and the dose-unit approach we conducted sensitivity analyses assuming that one DDD or one tablet would last for 1.00, 1.25 or 2.00 days. We also tested the impact of grace periods in sensitivity analyses. Results: Treatment duration and drug survival varied substantially for the same patients depending on the chosen method, duration of a DDD or a tablet, and inclusion of grace periods. The 25th percentile of treatment duration was 100 days for the DDD approach with one DDD per day, 100 days with the dose-unit approach with one tablet per day and 453 days with the WTD approach. Conclusion: When estimating treatment duration from prescription databases one should be aware that these measures of persistence are highly influenced by the chosen methodology. The choice of method should be informed by the clinical context with a preference for use of methods based on a formal model.