Thrane Julie Maria, Støvring Henrik, Hellfritzsch Maja, Hallas Jesper, Pottegård Anton
Clinical Pharmacology and Pharmacy, Department of Public Health, University of Southern Denmark, Odense, Denmark.
Biostatistics, Department of Public Health, Aarhus University, Aarhus, Denmark.
Pharmacoepidemiol Drug Saf. 2018 Sep;27(9):1011-1018. doi: 10.1002/pds.4581. Epub 2018 Jun 28.
In many prescription databases, the duration of treatment for the single prescription is not recorded. This study aimed to validate 2 different types of approaches for estimating prescription durations, using the oral anticoagulant warfarin as a case.
The approaches undergoing empirical validation covered assumptions of a fixed daily intake of either 0.5 or 1.0 defined daily dose (DDD), as well as estimates based on the reverse parametric waiting time distribution (rWTD), with different sets of covariates. We converted estimates of prescription duration to daily dose and compared them to prescribed daily dose as recorded in a clinical registry (using Bland-Altman plots). Methods were compared based on their average prediction error (logarithmic scale) and their limit of agreement ratio (ratio of mean error ± 1.96 SD after transformation to original scale).
Estimates of daily doses were underestimated by 19% or overestimated by 62% when assumptions of 0.5 or 1.0 DDD were applied. The limit of agreement ratio was 6.721 for both assumptions. The rWTD-based approaches performed better when using the estimated mean value of the inter-arrival density, yielding on average negligible bias (relative difference of 0 to 2%) and with limit of agreement ratios decreasing upon additional covariate adjustment (from 6.857 with no adjustment to 4.036 with the fully adjusted model).
Comparing the different methods, the rWTD algorithm performed best and led to unbiased estimates of prescribed doses and thus prescription durations and reduced misclassification on the individual level upon inclusion of covariates.
在许多处方数据库中，单次处方的治疗时长未被记录。本研究旨在以口服抗凝药华法林为例，验证两种不同类型的估计处方时长的方法。
接受实证验证的方法涵盖了每日固定摄入量为0.5或1.0定义日剂量（DDD）的假设，以及基于反向参数等待时间分布（rWTD）并使用不同协变量集的估计方法。我们将处方时长的估计值转换为每日剂量，并将其与临床登记处记录的规定每日剂量进行比较（使用布兰德-奥特曼图）。基于平均预测误差（对数尺度）和一致性限度比（转换回原始尺度后平均误差±1.96标准差的比值）对方法进行比较。
当应用0.5或1.0 DDD的假设时，每日剂量估计值被低估了19%或高估了62%。两种假设的一致性限度比均为6.721。基于rWTD的方法在使用到达间隔密度的估计平均值时表现更好，平均偏差可忽略不计（相对差异为0至2%），并且随着额外协变量调整，一致性限度比降低（从无调整时的6.857降至完全调整模型时的4.036）。
比较不同方法，rWTD算法表现最佳，能对规定剂量进行无偏估计，从而对处方时长进行无偏估计，并且在纳入协变量后可减少个体层面的错误分类。
