Assessing drug compliance using longitudinal marker data, with application to AIDS.
Assessing drug compliance using longitudinal marker data, with application to AIDS.
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使用纵向标记数据评估药物依从性，并应用于艾滋病。
DOI：
10.1002/sim.4780131921
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发表时间：
1994
影响因子：
2
通讯作者：
Lagakos,SW
中科院分区：
文献类型：
--
作者：
Kim,HM;Lagakos,SW
研究药物不依从性的评估是自我给药临床试验评估中的一个重要问题。评估受试者依从性的传统方法包括自我报告问卷和随机抽取血液样本中药物水平的药理学测定，但这些方法均具有重要的局限性。本文采用并扩展了变化点方法，以评估受药物影响的实验室标记物的纵向数据的依从性。开发并检查了两个模型的最大似然估计。药物对标记过程的影响以及标记过程的观察间隔相对于不合规时间决定了哪些模型参数是可估计的。对于所检查的情况，发现最大似然法在大多数情况下表现良好。然而，当不合规情况在最后一次观察标记过程之前不久开始时，这些（以及任何其他）估计器无法可靠地区分不合规与合规情况。通过最近一项针对艾滋病毒感染者的临床试验的例子来说明这些方法。
The assessment of non‐compliance to a study medication is an important issue in the evaluation of clinical trials of self‐administered drugs. Traditional methods for evaluating the compliance of subjects include self‐reported questionnaires and pharmacologic assays of drug levels in randomly‐drawn blood samples, but each of these has important limitations. This paper adapts and extends changepoint methods to assess compliance from longitudinal data on laboratory markers that are affected by the drug. The maximum likelihood estimators for two models are developed and examined. The effect of the drug on the marker process, as well as the spacing of the observations of the marker process relative to the time of noncompliance determine which model parameters are estimable. For the situations examined, the method of maximum likelihood is found to perform well in most cases. However, when non‐compliance begins shortly before the last observation of the marker process, these (as well as any other) estimators cannot reliably distinguish non‐compliance from compliance. The methods are illustrated with an example from a recent clinical trial of persons infected with HIV.