ABSTRACT

Effective post-market safety surveillance of medical devices is critical for public health. However, many current statistical methods for safety signal detection do not control for type I error when assessing multiple device and adverse event (AE) combinations. This can result in increased false signals, underscoring the need for more robust statistical methods. Moreover, the duration of medical device use can be an important factor to consider in safety surveillance. In this study, we adapted a likelihood ratio test (LRT) based method, which was initially developed and applied to drugs, to identify safety signals for left ventricular assist devices (LVAD). Among patients with chronic, advanced left ventricular failure, we analyzed AE data for HeartWare and HeartMate II patients during a two-year period and further incorporated person-years (henceforth exposure-time). The novel modified LRT and conventional Z-test with p-values adjusted by the Benjamini-Hochberg (BH) procedure were used to explore safety signals by comparing HeartWare and HeartMate II patients in the presence of multiple adverse events. Both methods identified greater incidence of stroke among HeartWare as compared to HeartMate II patients without exposure-time (p = .025 for LRT and p = .027 for Z-test with BH) and with exposure-time (p = .002 for LRT and p = .005 for Z-test with BH). By using improved statistical methods for safety signal detection, potential safety issues can be identified and addressed in a more timely manner to enhance public safety.

摘要

对医疗器械进行有效的上市后安全监督对公共卫生至关重要。然而，在评估多个设备和不良事件 (AE) 组合时，许多当前用于安全信号检测的统计方法无法控制 I 类错误。这会导致错误信号增加，强调需要更强大的统计方法。此外，医疗器械使用的持续时间可能是安全监督中需要考虑的重要因素。在这项研究中，我们采用了一种基于似然比检验 (LRT) 的方法，该方法最初是开发并应用于药物的，以识别左心室辅助装置 (LVAD) 的安全信号。在慢性晚期左心室衰竭患者中，我们分析了两年期间 HeartWare 和 HeartMate II 患者的 AE 数据，并进一步纳入了人年（以下称为暴露时间）。新的改良 LRT 和传统的 Z 检验通过在存在多种不良事件的情况下比较 HeartWare 和 HeartMate II 患者，使用由 Benjamini-Hochberg (BH) 程序调整的p 值来探索安全信号。与没有暴露时间（LRT 的p = .025 和BH 的 Z 检验p = .027）和暴露时间（LRT 的p = .002和p = 0.005对于Z-测试用BH）。通过使用改进的安全信号检测统计方法，可以更及时地识别和解决潜在的安全问题，以提高公共安全。