Lehman H P, Chen J, Gould A L, Kassekert R, Beninger P R, Carney R, Goldberg M, Goss M A, Kidos K, Sharrar R G, Shields K, Sweet A, Wiholm B E, Honig P K
Merck & Co. Inc., West Point, PA, USA.
Clin Pharmacol Ther. 2007 Aug;82(2):173-80. doi: 10.1038/sj.clpt.6100233. Epub 2007 May 16.
To understand the value of computer-aided disproportionality analysis (DA) in relation to current pharmacovigilance signal detection methods, four products were retrospectively evaluated by applying an empirical Bayes method to Merck's post-marketing safety database. Findings were compared with the prior detection of labeled post-marketing adverse events. Disproportionality ratios (empirical Bayes geometric mean lower 95% bounds for the posterior distribution (EBGM05)) were generated for product-event pairs. Overall (1993-2004 data, EBGM05> or =2, individual terms) results of signal detection using DA compared to standard methods were sensitivity, 31.1%; specificity, 95.3%; and positive predictive value, 19.9%. Using groupings of synonymous labeled terms, sensitivity improved (40.9%). More of the adverse events detected by both methods were detected earlier using DA and grouped (versus individual) terms. With 1939-2004 data, diagnostic properties were similar to those from 1993 to 2004. DA methods using Merck's safety database demonstrate sufficient sensitivity and specificity to be considered for use as an adjunct to conventional signal detection methods.
为了解计算机辅助的不成比例性分析（DA）相对于当前药物警戒信号检测方法的价值，通过对默克公司的上市后安全数据库应用经验贝叶斯方法，对四种产品进行了回顾性评估。将结果与之前对已标注的上市后不良事件的检测情况进行了比较。为产品-事件对生成了不成比例率（后验分布的经验贝叶斯几何均值下限95%（EBGM05））。与标准方法相比，使用DA进行信号检测的总体结果（1993 - 2004年数据，EBGM05≥2，单个术语）为：灵敏度31.1%；特异性95.3%；阳性预测值19.9%。使用同义标注术语分组时，灵敏度有所提高（40.9%）。两种方法检测到的更多不良事件是使用DA以及分组（而非单个）术语更早检测到的。对于1939 - 2004年的数据，诊断特性与1993年至2004年的相似。使用默克公司安全数据库的DA方法显示出足够的灵敏度和特异性，可考虑用作传统信号检测方法的辅助手段。
