Center for Outcomes Research and Evaluation, Yale-New Haven Health System, New Haven, CT, USA.
National Clinician Scholars Program, Yale School of Medicine, New Haven, CT, USA.
Pharmacoepidemiol Drug Saf. 2018 Aug;27(8):848-856. doi: 10.1002/pds.4565. Epub 2018 Jun 12.
To estimate medical device utilization needed to detect safety differences among implantable cardioverter defibrillators (ICDs) generator models and compare these estimates to utilization in practice.
We conducted repeated sample size estimates to calculate the medical device utilization needed, systematically varying device-specific safety event rate ratios and significance levels while maintaining 80% power, testing 3 average adverse event rates (3.9, 6.1, and 12.6 events per 100 person-years) estimated from the American College of Cardiology's 2006 to 2010 National Cardiovascular Data Registry of ICDs. We then compared with actual medical device utilization.
At significance level 0.05 and 80% power, 34% or fewer ICD models accrued sufficient utilization in practice to detect safety differences for rate ratios <1.15 and an average event rate of 12.6 events per 100 person-years. For average event rates of 3.9 and 12.6 events per 100 person-years, 30% and 50% of ICD models, respectively, accrued sufficient utilization for a rate ratio of 1.25, whereas 52% and 67% for a rate ratio of 1.50. Because actual ICD utilization was not uniformly distributed across ICD models, the proportion of individuals receiving any ICD that accrued sufficient utilization in practice was 0% to 21%, 32% to 70%, and 67% to 84% for rate ratios of 1.05, 1.15, and 1.25, respectively, for the range of 3 average adverse event rates.
Small safety differences among ICD generator models are unlikely to be detected through routine surveillance given current ICD utilization in practice, but large safety differences can be detected for most patients at anticipated average adverse event rates.
估计检测植入式心脏复律除颤器 (ICD) 发生器模型之间安全性差异所需的医疗器械使用量,并将这些估计与实际使用情况进行比较。
我们进行了重复的样本量估计,以计算所需的医疗器械使用量,同时系统地改变设备特定的安全性事件发生率比值和显著水平,同时保持 80%的功率,测试了从美国心脏病学会 2006 年至 2010 年 ICD 国家心血管数据注册中心估计的 3 个平均不良事件发生率 (3.9、6.1 和 12.6 例/100 人年)。然后将其与实际医疗器械使用情况进行比较。
在显著水平 0.05 和 80%的功率下,在实际情况下,只有 34%或更少的 ICD 模型积累了足够的使用率,以检测发生率比值<1.15 和平均事件率为 12.6 例/100 人年的安全性差异。对于平均事件率为 3.9 和 12.6 例/100 人年,分别有 30%和 50%的 ICD 模型积累了足够的使用率,以达到发生率比值为 1.25,而 52%和 67%则为 1.50。由于实际 ICD 使用量在 ICD 模型之间没有均匀分布,因此在实际情况下,接受任何 ICD 的个体中,积累了足够使用率的比例为 0%至 21%、32%至 70%和 67%至 84%,分别为发生率比值为 1.05、1.15 和 1.25,用于 3 个平均不良事件率的范围。
考虑到目前实际 ICD 使用情况,检测 ICD 发生器模型之间的微小安全性差异不太可能通过常规监测来实现,但对于大多数患者来说,在预期的平均不良事件发生率下,可以检测到较大的安全性差异。