Individualized estimates of treatment benefit from hormone therapy for men with prostate cancer

前列腺癌男性激素治疗获益的个体化评估

• 批准号: 10739866
• 负责人: Matthew Schipper
• 金额: $ 38.69万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-20 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10739866
• 关键词: Address; Age; Area; Attention; Calibration; Cancer Patient; Clinical; Data; Data Set; Decision Making; Development; Distant Metastasis; Guidelines; Health; Incidence; Individual; Individual Adjustment; International; Intuition; Life Expectancy; Literature; Malignant neoplasm of prostate; Modeling; Morbidity - disease rate; National Comprehensive Cancer Network; Oncology; Outcome; Patient risk; Patients; Population; Positioning Attribute; Postoperative Period; Probability; Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; Publishing; Recommendation; Research Personnel; Risk; Risk Estimate; Risk Factors; Social Security; Statistical Methods; Work; clinical decision-making; clinical prognostic; clinically relevant; cohort; comorbidity; demographics; hazard; high risk; hormone therapy; improved; individual patient; lifetime risk; men; mortality; mortality risk; personalized medicine; phase III trial; predictive modeling; prospective; prostate cancer model; prostate cancer risk; randomized trial; survival outcome; tool; treatment effect; treatment guidelines; trial design; web app

Abstract National treatment guidelines, including those from the National Comprehensive Cancer Network (NCCN), for men with localized prostate cancer are based on prostate cancer specific mortality (PCSM) risk and life expectancy which is driven by other cause (non-cancer) mortality (OCM). While OCM is the dominant risk for many prostate cancer patients, it has received limited attention in the literature. We developed and validated a clinically relevant model for OCM and life expectancy using prospective data from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) trial. OCM varied substantially based on patient demographics and comorbidities and found that social security life expectancy estimations based on age alone generated substantially biased estimates. Our team also developed and validated a clinical prognostic model for PCSM published in JAMA Oncology in 2020 (STAR-CAP). While the importance of competing risks in prostate cancer is widely recognized, there are no models to date which provide PCSM risk estimates individualized by OCM risk. Many of the common and important treatment decisions for men with localized PC include whether to treat with hormone therapy (ADT) and for how long. Guidelines recommend ADT for many men who are treated without it due to morbidity and questions as to actual treatment benefit for individual patients. Phase III trials have provided overall estimates of the benefit of ADT in terms of reduction in PCSM over large groups of patients (e.g. intermediate risk). To date however, there are no tools which provide treatment benefit estimates for individual patients based on PCSM and OCM risk. We propose to address these shortcomings through two aims. In Aim 1 we will integrate our model for OCM risk with models for distant metastases (DM) and PCSM to provide estimates of the absolute risk of DM and PCSM that are personalized using both PCSM and OCM risk factors. We hypothesize that the integrated model estimates will differ from clinical ad hoc estimates and significantly improve upon current estimates of PCSM that do not consider OCM risk. In Aim 2 we will develop a web app which provides individualized estimates of ADT treatment effect in three common clinical scenarios: RT vs RT + short term ADT in intermediate risk, RT + short term ADT vs RT + long term ADT in high risk and RT vs RT + ADT in the salvage setting. To do this we will combine the integrated multistate model from Aim 1 with published hazard ratios for outcomes of PCSM and DM. Our group is uniquely positioned to carry out this work as we have already developed the component models, have access to the patient level data for additional analyses and have a track record of successful development of web apps to aid in clinical decision making. If successful, the tools developed in this application will provide clinicians and patients the key information they need to make informed treatment decisions.

摘要 国家治疗指南，包括国家综合癌症网络（NCCN）的指南， 局限性前列腺癌的男性是基于前列腺癌特异性死亡率（PCSM）风险和寿命 预期由其他原因（非癌症）死亡率（OCM）驱动。虽然OCM是主要风险， 许多前列腺癌患者，它在文献中受到的关注有限。我们开发并验证了 OCM和预期寿命的临床相关模型，使用来自前列腺，肺， 结肠直肠癌和卵巢癌筛查试验（PLCO）。OCM因患者而异 人口统计学和合并症，并发现社会保障预期寿命估计仅基于年龄 产生了严重偏差的估计。我们的团队还开发并验证了一种临床预后模型 2020年发表在JAMA Oncology（STAR-CAP）上的PCSM。虽然竞争性风险的重要性 前列腺癌被广泛认可，迄今为止还没有模型提供PCSM风险估计 根据OCM风险进行个性化。许多常见的和重要的治疗决定，为男性与本地PC 包括是否用激素疗法（ADT）治疗以及治疗多长时间。指南建议ADT用于许多 由于发病率和对个人实际治疗益处的问题而没有接受治疗的男性 患者III期试验提供了ADT在减少PCSM方面获益的总体估计值 大组患者（例如，中等风险）。然而，到目前为止，还没有工具提供 基于PCSM和OCM风险的个体患者治疗获益估计。我们建议解决 这些缺点有两个目的。在目标1中，我们将把我们的OCM风险模型与 远端转移（DM）和PCSM，以提供DM和PCSM的绝对风险估计， 使用PCSM和OCM风险因素进行个性化。我们假设综合模型估计 将不同于临床特别估计，并显著改善目前的PCSM估计， 考虑OCM风险。在目标2中，我们将开发一个Web应用程序，提供ADT的个性化估计 三种常见临床情况下的治疗效果：中度风险患者的RT vs RT +短期ADT， RT +短期ADT与RT +长期ADT在高风险中的比较以及RT与RT + ADT在挽救治疗中的比较。到 为此，我们将联合收割机结合目标1中的综合多状态模型和已发表的结局风险比 PCSM和DM。我们的团队在开展这项工作方面具有独特的优势，因为我们已经开发了 组件模型，可以访问患者级数据进行额外分析，并具有以下跟踪记录 成功开发Web应用程序，以帮助临床决策。如果成功的话， 应用程序将为临床医生和患者提供他们需要的关键信息，以便进行知情治疗 决策