Bordeaux PharmacoEpi, INSERM CIC1401, Université de Bordeaux, Bordeaux, France.
INSERM U1219, Université de Bordeaux, Bordeaux, France.
Pharmacoepidemiol Drug Saf. 2020 Aug;29(8):890-903. doi: 10.1002/pds.5038. Epub 2020 Jun 10.
Upper gastrointestinal bleeding (UGIB) is a severe and frequent drug-related event. In order to enable efficient drug safety alert generation in the French National Healthcare System database (SNDS), we assessed and calibrated empirically case-based designs to identify drug associated with UGIB risk.
All cases of UGIB were extracted from SNDS (2009-2014) using two definitions. Positive and negative drug controls were used to compare 196 self-controlled case series (SCCS), case-control (CC) and case-population (CP) design variants. Each variant was evaluated in a 1/10 population sample using area under the receiver operating curve (AUC) and mean square error (MSE). Parameters that had major impacts on results were identified through logistic regression. Optimal designs were replicated in the unsampled population.
Using a specific UGIB definition, AUCs ranged from 0.64 to 0.80, 0.44 to 0.61 and 0.50 to 0.67, for SCCS, CC and CP, respectively. MSE ranged from 0.07 to 0.39, 0.83 to 1.33 and 1.96 to 4.6, respectively. Univariate regressions showed that high AUCs were achieved with SCCS with multiple drug adjustment and a 30-day risk window starting at exposure. The top-performing SCCS variant in the unsampled population yielded an AUC = 0.84 and MSE = 0.14, with 10/36 negative controls presenting significant estimates.
SCCS adjusting for multiple drugs and using a 30-day risk window has the potential to generate UGIB-related alerts in the SNDS and hypotheses on its potential population impact. Negative control implementation highlighted that low systematic error was generated but that protopathic bias and confounding by indication remained unaddressed issues.
上消化道出血(UGIB)是一种严重且频繁的与药物相关的事件。为了能够在法国国家医疗保健系统数据库(SNDS)中有效地生成药物安全性警报,我们评估并经验校准了基于病例的设计,以确定与 UGIB 风险相关的药物。
使用两种定义从 SNDS(2009-2014 年)中提取所有 UGIB 病例。阳性和阴性药物对照用于比较 196 个自对照病例系列(SCCS)、病例对照(CC)和病例-人群(CP)设计变体。使用接收者操作特征曲线(AUC)和均方误差(MSE)的面积评估每个变体在 1/10 人群样本中的表现。通过逻辑回归确定对结果有重大影响的参数。在未抽样人群中复制最佳设计。
使用特定的 UGIB 定义,AUC 范围分别为 0.64 至 0.80、0.44 至 0.61 和 0.50 至 0.67,用于 SCCS、CC 和 CP。MSE 范围分别为 0.07 至 0.39、0.83 至 1.33 和 1.96 至 4.6。单变量回归表明,SCCS 具有多重药物调整和暴露开始时 30 天风险窗口,可以实现高 AUC。在未抽样人群中表现最佳的 SCCS 变体产生 AUC = 0.84 和 MSE = 0.14,其中 10/36 个阴性对照呈现出显著的估计值。
SCCS 对多种药物进行调整,并使用 30 天风险窗口,有可能在 SNDS 中生成与 UGIB 相关的警报,并对其潜在的人群影响提出假设。阴性对照的实施突出表明,系统误差生成较低,但先知偏差和适应症混杂仍然是未解决的问题。