PRE2DUP-R, advanced, open science method to estimate drug use periods for pharmacoepidemiology.

INTRODUCTION

Valid outcome estimation in pharmacoepidemiological studies requires accurate estimation of drug use periods. This estimation becomes more precise when person-specific drug use patterns are considered. PRE2DUP is a method to estimate drug use periods from drug purchases, based on purchased amount, sliding average of daily dose, utilizing package-level parameters, hospital care periods and personal purchase regularity over time. Objective of this study was to develop openly shared R-package of PRE2DUP named PRE2DUP-R, to compare the drug use periods created by PRE2DUP and PRE2DUP-R, and to assess the impact of using package durations derived from the study population for single purchases.

METHODS

PRE2DUP-R follows the same core principles as original PRE2DUP. The main change is forming blocks of purchases to which estimation of personal use pattern calculation is restricted to. We created drug use periods with PRE2DUP and PRE2DUP-R using the same data and guiding parameters and compared the difference in the number of drug use periods and total exposure time per person and drug. In addition, the impact of updating typical package durations with PRE2DUP-R estimated package durations from study population was assessed.

RESULTS

The number of drug use periods created with PRE2DUP-R was slightly larger (mean number of periods per person and drug 2.01 vs 1.88, rate ratio (RR) 1.07, 95% CI 1.07-1.08) and total exposure time was shorter (∼4 days, 1,085 vs 1,089 days). Using data driven package durations led to slightly higher number of periods (RR 1.01, 95% CI 1.01-1.02), but exposure time reduced mean of 23.8 days compared to results with original parameters.

CONCLUSION

PRE2DUP and PRE2DUP-R results differed slightly, but expectedly considering the restriction in calculation of personal pattern. Change in the results after updating typical package durations highlights the importance of thorough consideration on use patterns of single purchases.