Univ de Bordeaux, U657, 33000, Bordeaux, France,
Drug Saf. 2013 Oct;36(10):1033-44. doi: 10.1007/s40264-013-0083-1.
An updated probabilistic causality assessment method and the Liverpool algorithm presented as an improved version of the Naranjo algorithm, one of the most used and accepted causality assessment methods, have recently been proposed.
In order to test the validity of the probabilistic method in routine pharmacovigilance, results provided by the Naranjo and Liverpool algorithms, as well as the updated probabilistic method, were each compared with a consensual expert judgement taken as reference.
A sample of 59 drug-event pairs randomly sampled from spontaneous reports to the French pharmacovigilance system was assessed by expert judgement until reaching consensus and by members of a pharmacovigilance unit using the updated probabilistic method, the Naranjo and Liverpool algorithms. Probabilities given by the probabilistic method, and categories obtained by both the Naranjo and the Liverpool algorithms were compared as well as their sensitivity, specificity, positive and negative predictive values.
The median probability for drug causation given by the consensual expert judgement was 0.70 (inter-quartile range, IQR 0.54-0.84) versus 0.77 (IQR 0.54-0.91) for the probabilistic method. For the Naranjo algorithm, the 'possible' causality category was predominant (61 %), followed by 'probable' (35 %), 'doubtful', and 'almost certain' categories (2 % each). Category distribution obtained with the Liverpool algorithm was similar to that obtained by the Naranjo algorithm with a majority of 'possible' (61 %) and 'probable' (30 %) followed by 'definite' (7 %) and 'unlikely' (2 %). For the probabilistic method, sensitivity, specificity, positive and negative predictive values were 0.96, 0.56, 0.92 and 0.71, respectively. For the Naranjo algorithm, depending on whether the 'possible' category was considered in favour or in disfavour of drug causation, sensitivity was, respectively, 1 or 0.42, specificity 0.11 or 0.89, negative predictive value 1 or 0.22 and positive predictive value 0.86 or 0.95; results were identical for the Liverpool algorithm.
The logistic probabilistic method gave results closer to the consensual expert judgment than either the Naranjo or Liverpool algorithms whose performance were strongly dependent on the meaning given to the 'possible' category. Owing to its good sensitivity and positive predictive value and by providing results as continuous probabilities, the probabilistic method seems worthy to use for a trustable assessment of adverse drug reactions in routine practice.
最近提出了一种更新的概率因果关系评估方法和利物浦算法,作为最常用和最被接受的因果关系评估方法之一的 Naranjo 算法的改进版本。
为了检验概率方法在常规药物警戒中的有效性,将 Naranjo 和利物浦算法以及更新的概率方法的结果分别与共识专家判断进行比较,作为参考。
从法国药物警戒系统自发报告中随机抽取 59 对药物-事件对,由专家判断直至达成共识,并由药物警戒单位成员使用更新的概率方法、Naranjo 和利物浦算法进行评估。比较概率方法给出的概率以及 Naranjo 和利物浦算法得出的类别,以及它们的灵敏度、特异性、阳性和阴性预测值。
共识专家判断的药物因果关系中值概率为 0.70(四分位距,IQR 0.54-0.84),而概率方法为 0.77(IQR 0.54-0.91)。对于 Naranjo 算法,“可能”因果关系类别占主导地位(61%),其次是“可能”(35%)、“可疑”和“几乎确定”类别(各占 2%)。利物浦算法得出的类别分布与 Naranjo 算法相似,以“可能”(61%)和“可能”(30%)为主,其次是“确定”(7%)和“不太可能”(2%)。对于概率方法,灵敏度、特异性、阳性和阴性预测值分别为 0.96、0.56、0.92 和 0.71。对于 Naranjo 算法,取决于是否将“可能”类别视为有利于或不利于药物因果关系,灵敏度分别为 1 或 0.42,特异性分别为 0.11 或 0.89,阴性预测值分别为 1 或 0.22,阳性预测值分别为 0.86 或 0.95;对于利物浦算法,结果相同。
逻辑概率方法给出的结果比 Naranjo 或利物浦算法更接近共识专家判断,后两者的性能强烈依赖于对“可能”类别的解释。由于其良好的灵敏度和阳性预测值,并提供了连续概率的结果,概率方法似乎值得在常规实践中用于可靠地评估药物不良反应。