Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina.
Associate Editor.
JAMA Cardiol. 2019 Apr 1;4(4):375-379. doi: 10.1001/jamacardio.2019.0198.
IMPORTANCE: Despite its documented undercapture of mortality data, the US Social Security Administration Death Master File (SSDMF) is still often used to provide mortality end points in retrospective clinical studies. Changes in death data reporting to SSDMF in 2011 may have further affected the reliability of mortality end points, with varying consequences over time and by state. OBJECTIVE: To evaluate the reliability of mortality rates in the SSDMF in a cohort of patients with atherosclerotic cardiovascular disease (ASCVD). DESIGN, SETTING, AND PARTICIPANTS: This observational analysis used the IBM MarketScan Medicare and commercial insurance databases linked to mortality information from the SSDMF. Adults with ASCVD who had a clinical encounter between January 1, 2012, and December 31, 2013, at least 2 years of follow-up, and from states with 1000 or more eligible adults with ASCVD were included in the study. Data analysis was conducted between April 18 and May 21, 2018. MAIN OUTCOMES AND MEASURES: Kaplan-Meier analyses were conducted to estimate state-level mortality rates for adults with ASCVD, stratified by database (commercial or Medicare). Constant hazards of mortality by state were tested, and individual state Kaplan-Meier curves for temporal changes were evaluated. For states in which the hazard of death was constant over time, mortality rates for adults with ASCVD were compared with state-level, age group-specific overall mortality rates in 2012, as reported by the National Center for Health Statistics (NCHS). RESULTS: This study of mortality data of 667 516 adults with ASCVD included 274 005 adults in the commercial insurance database cohort (171 959 male [62.8%] and median [interquartile range (IQR)] age of 58 [52-62] years) and 393 511 in the Medicare database cohort (245 366 male [62.4%] and median [IQR] age of 76 [70-83] years). Of the 41 states included, 11 states (26.8%) in the commercial cohort and 18 states (43.9%) in the Medicare cohort had a change in the hazard of death after 2012. Among states with constant hazard, state-level mortality rates using the SSDMF ranged widely, from 0.06 to 1.30 per 100 person-years (commercial cohort) and from 0.83 to 6.07 per 100 person-years (Medicare cohort). Variability between states in mortality estimates for adults with ASCVD using SSDMF data greatly exceeded variability in overall mortality from the NCHS. No correlation was found between NCHS mortality estimates and those from the SSDMF (ρ = 0.29 [P = .06] for age 55-64 years; ρ = 0.18 [P = .27] for age 65-74 years). CONCLUSIONS AND RELEVANCE: The SSDMF appeared to markedly underestimate mortality rates, with variable undercapture among states and over time; this finding suggests that SSDMF data are not reliable and should not be used alone by researchers to estimate mortality rates.
重要性:尽管美国社会保障管理局死亡主文件(SSDMF)记录的死亡率数据存在漏报,但它仍然经常被用于提供回顾性临床研究的死亡率终点。2011 年 SSDMF 中死亡数据报告方式的变化可能进一步影响了死亡率终点的可靠性,随着时间的推移和各州的不同,其后果也不同。 目的:评估 SSDMF 中动脉粥样硬化性心血管疾病(ASCVD)患者死亡率的可靠性。 设计、地点和参与者:本观察性分析使用 IBM MarketScan 医疗保险和商业保险数据库,这些数据库与 SSDMF 的死亡率信息相关联。2012 年 1 月 1 日至 2013 年 12 月 31 日期间至少有 2 年随访时间的 ASCVD 临床就诊的成年人,且来自至少有 1000 名符合 ASCVD 条件的成年人的州,被纳入了这项研究。数据分析于 2018 年 4 月 18 日至 5 月 21 日进行。 主要结果和措施:对 ASCVD 成年人的州级死亡率进行 Kaplan-Meier 分析,按数据库(商业或医疗保险)进行分层。测试各州死亡率的恒定风险,并评估各州随时间变化的个体 Kaplan-Meier 曲线。对于死亡风险在时间上保持不变的州,将 ASCVD 成年人的死亡率与 2012 年国家卫生统计中心(NCHS)报告的各州、年龄组特定的总体死亡率进行比较。 结果:这项涉及 667516 名 ASCVD 成年人死亡率数据的研究包括商业保险数据库队列中的 274005 名成年人(171959 名男性[62.8%],中位数[四分位距(IQR)]年龄为 58 [52-62]岁)和医疗保险数据库队列中的 393511 名成年人(245366 名男性[62.4%],中位数[IQR]年龄为 76 [70-83]岁)。在纳入的 41 个州中,商业队列中有 11 个州(26.8%)和医疗保险队列中有 18 个州(43.9%)在 2012 年后死亡风险发生了变化。在死亡风险恒定的州中,使用 SSDMF 的州级死亡率范围很广,从每 100 人年 0.06 到 1.30 人(商业队列)和每 100 人年 0.83 到 6.07 人(医疗保险队列)。使用 SSDMF 数据对 ASCVD 成年人死亡率的估计各州之间的差异大大超过了 NCHS 总体死亡率的差异。NCHS 死亡率估计值与 SSDMF 之间没有相关性(55-64 岁年龄组 ρ=0.29[P=0.06];65-74 岁年龄组 ρ=0.18[P=0.27])。 结论和相关性:SSDMF 似乎明显低估了死亡率,各州和随时间的死亡率漏报情况存在差异;这一发现表明 SSDMF 数据不可靠,研究人员不应单独使用这些数据来估计死亡率。
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