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Using administrative claims data to estimate virologic failure rates among human immunodeficiency virus-infected patients with antiretroviral regimen switches

机译:使用行政声明数据来估计人类免疫缺陷病毒感染的抗逆转录病毒方案切换患者的病毒学失败率

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Objective. To develop and validate a claims signature model that estimates proportions of HIV-infected patients in administrative claims databases who switched combination antiretroviral therapy (cART) regimens because of virologic failure. Methods. The authors used an HIV-specific registry (development data set) to develop logistic regression models to estimate odds of virologic failure among patients who switched cART regimens. Models were validated in a sample of administrative claims with laboratory values (validation data set). The final model was applied to an application data set as a worked example. Results. There were 1691, 1073, and 3954 eligible patients with cART switches in the development, validation, and application data sets, respectively. In the development data set, virologic failure before a switch was observed 21.8% of the time. Failure more likely caused the regimen switch among patients who were treatment experienced, had been receiving their baseline regimen for > 180 days, had a‰¥ 2 or more physician visits within 90 days, had > 1 HIV RNA or CD4 cell count test within 30 days, had any resistance test within 180 days, or had a change in regimen type. The final model had good discriminatory ability (C = 0.885) and fit (Hosmer-Lemeshow P = 0.8692). Failure was estimated to occur in 18.9% (v. 18.6% observed) of switches in the validation data set and 13.8% in the application data set. Conclusions. This claims signature model allows payers to use claims data to estimate virologic failure rates in their patient populations, thereby better understanding plan costs of failure.
机译:目的。要开发和验证索赔签名模型,该模型可以估计在行政索赔数据库中因病毒学失败而改用组合抗逆转录病毒疗法(cART)方案的HIV感染患者的比例。方法。作者使用HIV专用注册表(开发数据集)开发了logistic回归模型,以评估转换cART方案的患者中病毒学失败的几率。在带有实验室值(验证数据集)的行政索赔样本中对模型进行了验证。最终模型已作为工作示例应用于应用程序数据集。结果。在开发,验证和应用数据集中分别有1691、1073和3954名符合条件的cART开关患者。在开发数据集中,有21.8%的时间观察到转换前的病毒学失败。失败更可能导致经历过治疗,已接受基线治疗> 180天,在90天内接受≥2次或两次以上的医师就诊,在30天内接受了> 1个HIV RNA或CD4细胞计数测试的患者中的治疗方案转换天,在180天内进行了任何抗药性测试或方案类型发生了变化。最终模型具有良好的判别能力(C = 0.885)和拟合度(Hosmer-Lemeshow P = 0.8692)。估计在验证数据集中的交换机中发生故障的比例为18.9%(观察到18.6%),在应用程序数据集中发生故障的比例为13.8%。结论该索赔签名模型允许付款人使用索赔数据来估计其患者群体中的病毒学失败率,从而更好地了解计划失败的成本。

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