{"title":"Clinical trials of cost effectiveness in technology evaluation.","authors":"P E Valk","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>This article discusses models of efficacy, design of clinical trials and the role of mathematical modeling in diagnostic technology evaluation and determination of cost-effectiveness. A multi-tiered model of efficacy, which views diagnostic imaging as part of a global process of patient management and outcome, has been described. The first tier involves imaging efficacy, which must be determined by clinical trial. Direct comparison of new and established modalities in a single study population has major advantages over randomized controlled trials, which are extremely costly and time-consuming and are not appropriate for most evaluations of diagnostic modalities. Selection of patients for inclusion in the trial, interpretation and verification of results, and determination of a reference standard are all possible sources of bias, which need to be identified and controlled. Decision analysis modeling can be used to assess diagnostic, therapeutic, patient-outcome and cost efficacy, once imaging efficacy has been evaluated by clinical trial. Decision analysis is easier and less expensive to perform than clinical trials, and results are easily generalizable to other settings. Disadvantages arise from the nondescriptive nature of modeling and lack of transparency, which make it difficult to evaluate the appropriateness of decision tree structures and input data. Modeling is an unavoidable fact of life in technology evaluation, since the resources that would be required for full evaluation of imaging modalities by clinical trial are not available.</p>","PeriodicalId":79384,"journal":{"name":"The quarterly journal of nuclear medicine : official publication of the Italian Association of Nuclear Medicine (AIMN) [and] the International Association of Radiopharmacology (IAR)","volume":"44 2","pages":"197-203"},"PeriodicalIF":0.0000,"publicationDate":"2000-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The quarterly journal of nuclear medicine : official publication of the Italian Association of Nuclear Medicine (AIMN) [and] the International Association of Radiopharmacology (IAR)","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract

This article discusses models of efficacy, design of clinical trials and the role of mathematical modeling in diagnostic technology evaluation and determination of cost-effectiveness. A multi-tiered model of efficacy, which views diagnostic imaging as part of a global process of patient management and outcome, has been described. The first tier involves imaging efficacy, which must be determined by clinical trial. Direct comparison of new and established modalities in a single study population has major advantages over randomized controlled trials, which are extremely costly and time-consuming and are not appropriate for most evaluations of diagnostic modalities. Selection of patients for inclusion in the trial, interpretation and verification of results, and determination of a reference standard are all possible sources of bias, which need to be identified and controlled. Decision analysis modeling can be used to assess diagnostic, therapeutic, patient-outcome and cost efficacy, once imaging efficacy has been evaluated by clinical trial. Decision analysis is easier and less expensive to perform than clinical trials, and results are easily generalizable to other settings. Disadvantages arise from the nondescriptive nature of modeling and lack of transparency, which make it difficult to evaluate the appropriateness of decision tree structures and input data. Modeling is an unavoidable fact of life in technology evaluation, since the resources that would be required for full evaluation of imaging modalities by clinical trial are not available.

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技术评价中成本效益的临床试验。
本文讨论了疗效模型、临床试验设计以及数学模型在诊断技术评估和成本效益确定中的作用。已经描述了一个多层疗效模型,该模型将诊断成像视为患者管理和结果的全球过程的一部分。第一层涉及影像学疗效,必须通过临床试验来确定。与随机对照试验相比,在单一研究人群中直接比较新的和已建立的模式具有主要优势,随机对照试验非常昂贵和耗时,并且不适用于大多数诊断模式的评估。选择纳入试验的患者、结果的解释和验证以及参考标准的确定都是可能的偏倚来源,需要加以识别和控制。决策分析模型可用于评估诊断,治疗,患者结局和成本效益,一旦影像学疗效已通过临床试验评估。决策分析比临床试验更容易,成本更低,结果很容易推广到其他情况。缺点来自建模的非描述性和缺乏透明度,这使得很难评估决策树结构和输入数据的适当性。建模是技术评估中不可避免的事实,因为通过临床试验全面评估成像模式所需的资源是不可获得的。
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