Survival Analysis for Economic Evaluations Alongside Clinical Trials-Extrapolation with Patient-Level Data: Inconsistencies, Limitations, and a Practical Guide
Survival Analysis for Economic Evaluations Alongside Clinical Trials-Extrapolation with Patient-Level Data: Inconsistencies, Limitations, and a Practical Guide
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DOI：
10.1177/0272989x12472398
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发表时间：
2013-08-01
影响因子：
3.6
通讯作者：
Latimer, Nicholas R.
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文献类型：
--
作者：
Latimer, Nicholas R.
背景在影响生存的干预措施的卫生技术评估（HTAs）中，准确估计与新治疗相关的生存获益至关重要。通常，试验数据必须外推，许多模型可用于此目的。外推模型的选择至关重要，因为不同的模型可能导致非常不同的成本效益结果。如果不能系统地证明所选择的模式是正确的，就有可能在卫生技术协定之间产生偏见和不一致。Objective.证明与HTAs生存分析部分相关的局限性和不一致性，并提出一个过程指南，以帮助将这些从未来的分析中排除。方法.我们回顾了45个HTA的生存分析组成部分进行的国家卫生和临床卓越研究所（NICE）在癌症疾病领域。我们利用我们的调查结果，以确定共同的局限性，并制定一个过程指南。结果所选择的生存模型在所审查的任何HTA中均未得到系统性证明。考虑的模型范围通常不足，选择模型的理由普遍有限：特别是，很少明确考虑拟合生存曲线外推部分的可解释性。局限性。我们并不试图描述和审查所有的方法可用于执行生存分析几种方法存在，没有提到在这篇文章中。相反，我们寻求分析HTA中常用的方法以及与其应用相关的限制。结论.在HTAs中尚未系统地进行生存分析。需要采取一种系统的办法，如这里所提议的办法，以减少成本效益结果中的偏差和技术评估之间的不一致。
Background. In health technology assessments (HTAs) of interventions that affect survival, it is essential to accurately estimate the survival benefit associated with the new treatment. Generally, trial data must be extrapolated, and many models are available for this purpose. The choice of extrapolation model is critical because different models can lead to very different cost-effectiveness results. A failure to systematically justify the chosen model creates the possibility of bias and inconsistency between HTAs. Objective. To demonstrate the limitations and inconsistencies associated with the survival analysis component of HTAs and to propose a process guide that will help exclude these from future analyses. Methods. We reviewed the survival analysis component of 45 HTAs undertaken for the National Institute for Health and Clinical Excellence (NICE) in the cancer disease area. We drew upon our findings to identify common limitations and to develop a process guide. Results. The chosen survival models were not systematically justified in any of the HTAs reviewed. The range of models considered was usually insufficient, and the rationale for the chosen model was universally limited: In particular, the plausibility of the extrapolated portion of fitted survival curves was very rarely explicitly considered. Limitations. We do not seek to describe and review all methods available for performing survival analysisseveral approaches exist that are not mentioned in this article. Instead we seek to analyze methods commonly used in HTAs and limitations associated with their application. Conclusions. Survival analysis has not been conducted systematically in HTAs. A systematic approach such as the one proposed here is required to reduce the possibility of bias in cost-effectiveness results and inconsistency between technology assessments.