PROMISS - Prostate Modeling to Identify Surveillance Strategies

描述(申请人提供)：这项申请解决了前列腺癌管理中最关键的难题，前列腺癌是美国男性中仅次于皮肤癌的最常见的癌症。20世纪90年代，美国广泛采用PSA筛查，在这个国家造成了低风险前列腺癌的流行。绝大多数低风险病例不会死于他们的疾病，但他们继续寻求治疗。主动监测(AS)已经被一个权威小组认可为管理低风险前列腺癌的一种可行的选择，但如何实施它还没有基于证据的标准。在强直性脊柱炎中，病例受到密切监测，如果有任何疾病进展的证据，就打算进行治疗。有几项AS研究正在进行中，但它们是不同方法的松散集合，其结果不容易比较或综合。此应用程序的首要目标是确定一种最佳方法，以满足给定的患者特征和偏好。认识到许多潜在的AS治疗方法无法在临床试验中进行比较，我们将利用我们在前列腺癌进展和预后建模方面的丰富经验来预测候选AS策略的短期和长期结果。该模型将建立在对5项最高质量和最大AS研究的疾病进展的荟萃分析的基础上。这将得到一个在缺乏治疗的情况下疾病进展的独立模型的补充，该模型将使现有的基于人群的前列腺癌自然历史模型适应AS环境。我们将根据已发表的关于初治后复发、发病率和效用的研究，将候选作为策略，并将进展和治疗事件与治疗后的存活率和生活质量联系起来。由此产生的模型将预测一系列结果，包括无治疗间隔、疾病特定生存时间和质量调整后的生命年。结果将被打包在一个界面中，患者可以使用该界面来比较根据他们的个人特征和偏好定制的不同策略的结果。我们的具体目标是：目标1：在AS候选的低风险前列腺癌患者中，模拟前列腺癌在缺乏治疗的情况下的进展。作为这一目标的一部分，我们将对正在进行的AS研究进行第一次元分析。目的2：使用在目标1中开发的模型以及先前关于AS和局部疾病治疗的研究中的生存和生活质量信息，计划并比较不同AS方案的短期和长期结果。目的3：开发、测试和发布一个使用这些模型的界面，以帮助患者根据他们诊断时的临床和病理特征、他们的健康状况和个人喜好来识别个性化的AS方法。这项应用将推进AS的证据基础，并将是第一次，因为在一致的医疗决策框架内使用相同的指标对战略进行了比较。这项工作的主要影响在于，它有可能为患者的决策提供信息，从而变得更被接受，并提高美国每年许多被诊断为低风险前列腺癌的男性的质量调整后的预期寿命。

DESCRIPTION (provided by applicant): This application addresses the most critical conundrum in the management of prostate cancer, the most common cancer after skin cancer in US men. The widespread adoption of PSA screening in the US during the 1990s has created an epidemic of low-risk prostate cancer in this country. The vast majority of low-risk cases will not die of their disease yet they continue to seek curative treatment. Active surveillance (AS) has been endorsed by an authoritative panel as a viable option for managing low-risk prostate cancer, but no evidence- based standard exists for how to implement it. In AS, cases are closely monitored and intent to treat if there is any evidence of disease progression. Several AS studies are ongoing but they constitute a loose collection of different approaches and their results cannot be readily compared or integrated. The overarching objective of this application is to determine an optimal approach to AS given patient characteristics and preferences. Recognizing that the many potential approaches to AS cannot be compared in clinical trials, we will draw on our extensive experience modeling prostate cancer progression and prognosis to project the short- and long-term outcomes of candidate AS strategies. The model will build on a meta-analysis of disease progression across 5 of the highest quality and largest AS studies. This will be complemented by an independent model of disease progression in the absence of treatment that will adapt an existing, population-based model of prostate cancer natural history to the AS setting. We will superimpose candidate AS strategies and link the progression and treatment events with post-treatment survival and quality of life based on published studies of relapse, morbidity, and utilities following primary treatment. The resulting model will project a range of outcomes, including the treatment-free interval, disease-specific survival, and quality-adjusted life years. The outcomes will be pack- aged in an interface that patients can use to compare outcomes of different strategies tailored to their individual characteristics and preferences. Our Specific Aims are: Aim 1: Model prostate cancer progression in the absence of treatment among low-risk prostate cancer cases who are candidates for AS. As part of this aim we will conduct the first meta-analysis of ongoing AS studies. Aim 2: Project and compare short- and long-term outcomes on various AS protocols, using the models developed in Aim 1 along with survival and quality of life information from prior studies of AS and curative treatments for localized disease. Aim 3: Develop, test and release an interface using these models to help patients identify a personalized AS approach based on their clinical and pathologic characteristics at the time of diagnosis, their health status, and personal preferences. This application will advance the evidence base for AS and will be the first time AS strategies have been com- pared using the same metrics within a coherent medical decision-making framework. The main impact of the work lies in its potential to inform patient decision-making so that AS becomes more accepted and improves quality-adjusted life expectancy for the many men diagnosed low-risk prostate cancer each year in the US.