Use of Geographic Variations to Estimate Effectiveness with Non-Randomized Data

描述(由申请人提供)：美国不同地理区域的医疗支出和服务使用情况存在巨大差异。这种差异的很大一部分与使用尚未在随机试验中研究的服务有关。这种未知益处的服务的广泛差异导致了使用观察数据进行研究的呼声，以衡量医疗治疗的相对有效性。在非随机化环境中评估治疗效果需要仔细的数据收集和分析，因为患者组之间可能存在未观察到的差异。越来越多的研究人员利用服务使用的地理差异来推断其在个别患者中的有效性，前提是患者的特征在不同地理区域之间是平衡的。然而，在非随机研究中，关于生态变异可以用来获得治疗效果的有效估计的环境，人们知之甚少。使用来自监测流行病学和最终结果(SEER)-医疗保险数据库中被诊断为结直肠癌和前列腺癌的老年患者的基于人群的队列数据，我们将开发、评估和应用先进的统计方法来评估癌症干预的有效性。癌症为这种分析提供了理想的环境，因为它是一种普遍和严重的健康状况，而未知益处的新的昂贵的治疗方法正在不断地开发和推广。这些目标将通过以下三个具体目标实现：(1)开发和评估统计方法，以利用地理位置居留来模拟随机化治疗来评估治疗有效性；(2)应用这些方法来评估针对被诊断为结直肠癌和前列腺癌的患者的干预措施的比较有效性；以及(3)开发和传播软件，以促进在比较有效性研究中使用适当的统计方法。这些结果将提供有关干预措施有效性的信息，这些结果将提供有关干预措施有效性的信息，这些研究结果将提供有关干预措施有效性的信息，这些研究成果将被其他研究人员用于了解其他疾病的治疗有效性。 公共卫生相关性：该项目将提供关于结直肠癌和前列腺癌干预措施的有价值的信息，这在最近一项医学研究所关于比较有效性的优先事项的研究中得到强调。此外，开发的方法将适用于癌症和其他疾病的广泛干预措施，为未来的比较有效性研究和最终改变治疗指南提供一个框架。

DESCRIPTION (provided by applicant): There is enormous variation in medical spending and use of services across geographic areas in the United States. A large portion of this variation has been linked to use of services that have not been studied in randomized trials. This wide variation in services of unknown benefit has led to calls for research using observational data to measure the comparative effectiveness of medical treatments. Estimating treatment effectiveness in non-randomized settings requires careful data collection and analysis because of possible unobserved differences between patient groups. Increasingly, researchers are exploiting geographic variation in use of services to infer their effectiveness in individual patients, under the assumption that patient characteristics are balanced across geographic areas. However, little is understood about settings in which ecological variation can be used to obtain valid estimates of treatment effects in non-randomized studies. Using data from population-based cohorts of elderly patients diagnosed with colorectal and prostate cancer in the Surveillance Epidemiology, and End Results (SEER)-Medicare database, we will develop, evaluate, and apply advanced statistical methods to estimate the effectiveness of cancer interventions. Cancer provides an ideal setting for such an analysis because it is a prevalent and serious health condition, and new and expensive treatments of unknown benefit are continuously being developed and diffused. These goals will be accomplished through the following three specific aims: (1) develop and evaluate statistical methods to estimate treatment effectiveness using geographic residence to mimic randomization to treatment; (2) apply these methods to estimate the comparative effectiveness of interventions for patients diagnosed with colorectal and prostate cancer; and (3) develop and disseminate software to promote the use of appropriate statistical methods in comparative effectiveness studies These results will provide information about the effectiveness of interventions highlighted in a recent Institute of Medicine study on priorities for comparative effectiveness research and also provide a methodology that other researchers can use to learn about the effectiveness of treatments in other diseases. PUBLIC HEALTH RELEVANCE: This project will provide valuable information on interventions in colorectal and prostate cancer highlighted in a recent Institute of Medicine study on priorities for comparative effectiveness. In addition, the methods developed will be applicable to a broad range of interventions for cancer and other diseases, providing a framework for future comparative effectiveness studies and ultimately changes in treatment guidelines.