Department of Epidemiology, College of Public Health, University of Iowa, Iowa City, IA, USA.
Kaiser Permanente Center for Health Research-Northwest, Portland, OR, USA.
Pharmacoepidemiol Drug Saf. 2018 Jul;27(7):731-739. doi: 10.1002/pds.4420. Epub 2018 Mar 13.
The Food and Drug Administration's Sentinel System developed parameterized, reusable analytic programs for evaluation of medical product safety. Research on outpatient antibiotic exposures, and Clostridium difficile infection (CDI) with non-user reference groups led us to expect a higher rate of CDI among outpatient clindamycin users vs penicillin users. We evaluated the ability of the Cohort Identification and Descriptive Analysis and Propensity Score Matching tools to identify a higher rate of CDI among clindamycin users.
We matched new users of outpatient dispensings of oral clindamycin or penicillin from 13 Data Partners 1:1 on propensity score and followed them for up to 60 days for development of CDI. We used Cox proportional hazards regression stratified by Data Partner and matched pair to compare CDI incidence.
Propensity score models at 3 Data Partners had convergence warnings and a limited range of predicted values. We excluded these Data Partners despite adequate covariate balance after matching. From the 10 Data Partners where these models converged without warnings, we identified 807 919 new clindamycin users and 8 815 441 new penicillin users eligible for the analysis. The stratified analysis of 807 769 matched pairs included 840 events among clindamycin users and 290 among penicillin users (hazard ratio 2.90, 95% confidence interval 2.53, 3.31).
This evaluation produced an expected result and identified several potential enhancements to the Propensity Score Matching tool. This study has important limitations. CDI risk may have been related to factors other than the inherent properties of the drugs, such as duration of use or subsequent exposures.
食品和药物管理局的监测系统开发了参数化、可重复使用的分析程序,用于评估医疗产品的安全性。关于门诊抗生素暴露和艰难梭菌感染(CDI)与非使用者参考组的研究使我们预期门诊克林霉素使用者比青霉素使用者的 CDI 发生率更高。我们评估了队列识别和描述性分析以及倾向评分匹配工具识别克林霉素使用者中 CDI 发生率更高的能力。
我们将来自 13 个数据合作伙伴的门诊口服克林霉素或青霉素新使用者按倾向评分 1:1 进行匹配,并在最多 60 天内对其进行随访,以确定是否发生 CDI。我们使用 Cox 比例风险回归对数据合作伙伴和匹配对进行分层,以比较 CDI 的发生率。
3 个数据合作伙伴的倾向评分模型存在收敛警告和预测值范围有限。尽管在匹配后存在足够的协变量平衡,但我们仍排除了这些数据合作伙伴。从这些模型没有警告且收敛的 10 个数据合作伙伴中,我们确定了 807919 名新克林霉素使用者和 8815441 名新青霉素使用者符合分析条件。在 807769 对匹配对的分层分析中,克林霉素使用者中有 840 例事件,青霉素使用者中有 290 例(风险比 2.90,95%置信区间 2.53,3.31)。
这项评估产生了预期的结果,并确定了对倾向评分匹配工具的几项潜在改进。本研究存在重要的局限性。CDI 风险可能与药物固有特性以外的因素有关,例如使用时间或后续暴露。