Brown Joshua D, Adams Val R
Institute for Pharmaceutical Outcomes and Policy, Department of Pharmacy Practice and Science, College of Pharmacy, University of Kentucky, Lexington, KY 40536, USA.
Healthcare (Basel). 2016 Feb 26;4(1):16. doi: 10.3390/healthcare4010016.
Multiple myeloma (MM) has an inherent high risk of thromboembolic events associated with patient as well as disease- and treatment-related factors. Previous studies have assessed the association of MM-related thromboembolism using "traditional" Kaplan-Meier (KM) and/or Cox proportional hazard (PH) regression. In the presence of high incidence of death, as would be the case in cancer patients with advanced age, these statistical models will produce bias estimates. Instead, a competing risk framework should be used. This study assessed the baseline patient demographic and clinical characteristics associated with MM-related thromboembolism and compared the cumulative incidence and the measures of association obtained using each statistical approach. The cumulative incidence of thromboembolism was 9.2% using the competing risk framework and nearly 12% using the KM approach. Bias in the measures of covariate risk associations was highest for factors related to risk of death such as increased age (75% bias) and severe liver disease (50%) for the Cox PH model compared to the competing risk model. These results show that correct specification of statistical techniques can have a large impact on the results obtained.
多发性骨髓瘤(MM)存在与患者以及疾病和治疗相关因素相关的固有高血栓栓塞事件风险。先前的研究使用“传统”的 Kaplan-Meier(KM)和/或Cox 比例风险(PH)回归评估了MM相关血栓栓塞的关联。在存在高死亡率的情况下,如老年癌症患者的情况,这些统计模型将产生偏差估计。相反,应该使用竞争风险框架。本研究评估了与MM相关血栓栓塞相关的基线患者人口统计学和临床特征,并比较了使用每种统计方法获得的累积发病率和关联度量。使用竞争风险框架时血栓栓塞的累积发病率为9.2%,使用KM方法时接近12%。与竞争风险模型相比,Cox PH模型中与死亡风险相关的因素(如年龄增加(75%偏差)和严重肝病(50%))的协变量风险关联度量偏差最高。这些结果表明,统计技术的正确规范对所获得的结果可能有很大影响。