Therapeutic non-adherence: a rational behavior revealing patient preferences? Karine Lamiraud1,*, Pierre-Yves Geoffard1,2,3 Article first published online: 15 FEB 2007
这篇得了06/07年HE最佳的论文让我一头雾水，好量化啊，题目叫"治疗非依附性：这是一种揭示病人偏好的理性行为吗？"我决定翻一下其摘要：
文章基于病人是否遵从他们接受的处方来提供一种对病人福祉的间接测评手段。依附行为(Adherence behavior)被认为是可揭示病人对某种治疗的主观评价。我们写了一段简单的病人依附行为的理论模型—其反应了可知成本(perceived costs)和可知疗效(observed regimen efficacy)之间的权衡。一个离散选择框架(discrete choice framework)被用来进行估计，如两种药物摄入治疗所产生受益的比较。所以实证分析是基于对"与依附性相关的病人特征和药物特征"之间的识别。经济计量方法是通过一个联合分析"与依附性、病人对治疗反应相关的影响因素"的双变量面板双方程模拟系统进行研究的。数据来自1999-2001在法国进行的一个比较两种HIV 三疗法(tritherapy)的随机临床试验。
理论和实证结果都认为，对于可比较的临床疗效和毒理级别而言，更高的依附性和更好的病人福祉是相关的，因此研究为仅仅是生物统计分析产生的结论增加了更有价值的参考信息。所以从病人感知来说，依附性增加(adherence-enhancing)的药物必定是受偏爱的。我们基于面板数据的结果还认为，无法观测的病人特征是解释病人对药物评价的主要因素，而且治疗过程中病人对药物的评价是会改变的。另外我们提供了对依附性数据分析的一个新框架。这个微观计量框架强调非依附性是内生行为，这为改进依附性提出了新的途径。
Abstract
This paper offers an indirect measure of patient welfare based on whether patients comply with the prescription they receive. Adherence behavior is supposed to reveal patients' subjective valuations of particular therapies. We write a simple theoretical model of patient adherence behavior, that reflects the trade-off between perceived costs and observed regimen efficacy. A discrete choice framework is then used for the estimation, i.e. the comparison of the incremental benefit of drug intake between two regimens. Consequently, the empirical analysis is based on the identification of patient and drug characteristics associated with adherence. The econometric approach is implemented through a bivariate panel two-equation simultaneous system studying jointly the factors associated with adherence and response to treatment. The data come from a randomized clinical trial conducted in France between 1999 and 2001 and comparing the efficacy of two tritherapy strategies in HIV disease.
Both the theoretical and empirical results suggest that, for comparable clinical efficacy and toxicity levels, a higher adherence level is associated with higher patient welfare, thus adding valuable information to conclusions drawn by a mere biostatistical analysis. Therefore, from the perspective of the patient, the adherence-enhancing drug must be favored. Our results based on panel data also stress that unobserved patient characteristics account substantially for drug valuation and that the assessment evolves during the course of the treatment. Furthermore, we provide a new framework for the analysis of adherence data. The microeconometric framework highlights that non-adherence is an endogenous behavior, thus suggesting new ways for improving adherence.
