A Patient-Centered Approach to Integration of Life Expectancy into Treatment Decision Making for Patients with Genitourinary Malignancy

项目总结 预期寿命(Le)是泌尿生殖系(Gu)男性治疗决策的关键因素。 恶性肿瘤，由于有限的LE预测从治疗中受益的足够长寿的可能性较低，因此较高 治疗后发病率高，治疗效果下降。尽管LE在 指南中指出，局限性LE患者通常因惰性癌症而过度治疗，而对于高危患者往往治疗不足。 癌症。来自非癌症治疗环境的数据表明，这可能是由于医生水平的障碍 妨碍了LE的有效沟通。令人惊讶的是，关于LE目前是如何沟通的，人们知之甚少 在治疗咨询中，以及患者和医生关于如何理想地整合的观点。 此外，病人和社区对什么是最适合“非侵袭性治疗”的临界值提出了意见。 都是缺乏的。在此应用程序中，我们提出了一系列增量研究，总体目标是建立 一种以患者为中心的方法，将LE纳入前列腺癌、肾脏病患者的治疗决策， 和膀胱癌。(1)首先，我们将描述LE目前是如何与GU癌症患者沟通的 通过对早期前列腺癌、肾脏病患者治疗会诊成绩单的定性分析， 和肌肉浸润性膀胱癌。我们相信，目前LE的沟通将在 讨论的发生率、沟通方式、在访问中的时间定位、情绪 背景，以及在这个主题上投入的时间。(2)第二，聘请病人和专科医生 利益相关者通过结构化访谈来确定改善沟通的障碍和机会 癌症治疗决策中的LE信息。(三)三是运用网络众包方式 联合分析(CA)作为一个平台，研究患者和社区如何相对于其他 在前列腺癌、肾癌和膀胱癌的治疗决策中通常会遇到权衡。我们会 分析众包联合分析数据以确定情况(基于年龄、共病和肿瘤风险) 而LE似乎推动了“非侵袭性”的治疗选择，这将允许LE的靶向 干预措施。(4)第四，我们将在随机试验中测试患者特定的LE估计是否- 在第一个和第二个目标中确定的以患者为中心的方法进行沟通，并以 第三个目标中确定的特定高产情况--以及特定于LE的联合分析数据 改善决策冲突，讨论LE数据的质量，减少GU恶性肿瘤的过度治疗。我们 预计这种以患者为中心的方法将改善共享决策制定，并最终导致 更好的治疗选择为胃腺癌和有限的LE患者。

PROJECT SUMMARY Life expectancy (LE) is a critical factor in treatment decision making for men with genitourinary (GU) malignancies, since limited LE predicts lower likelihood of sufficient longevity to benefit from treatment, higher morbidity after treatment, and decreased effectiveness of treatment. Despite a prominent role of LE in guidelines, patients with limited LE are often overtreated for indolent cancers and undertreated for high-risk cancers. Data from non-cancer treatment settings suggest that this may be due to physician-level barriers precluding effective communication of LE. Surprisingly little is known about how LE is currently communicated in treatment consultations as well as patient and physician perspectives on how it should be ideally integrated. Furthermore, patient and community opinions on what LE cutoffs are best suited to “non-aggressive treatment” are lacking. In this application, we propose a series of incremental studies with an overarching goal of building a patient-centered approach to integrating LE into treatment decision making for patients with prostate, kidney, and bladder cancer. (1) First, we will delineate how LE is currently communicated to patients with GU cancers through qualitative analysis of treatment consultation transcripts of patients with early-stage prostate, kidney, and muscle-invasive bladder cancer. We believe that the current communication of LE will be highly variable in terms of incidence of discussion, mode of communication, temporal positioning within the visit, emotive context, and time devoted to the topic. (2) Second, we will engage patient and specialist physician stakeholders through structured interviews to identify barriers and opportunities to improve communication information about LE in cancer treatment decision making. (3) Third, we will use online crowdsourcing of conjoint analysis (CA) as a platform to study how patients and the community value LE relative to other tradeoffs typically encountered in prostate, kidney, and bladder cancer treatment decision making. We will analyze crowdsourced conjoint analysis data to identify situations (based on age, comorbidity, and tumor risk) where LE appears to drive “non-aggressive” treatment choices, which will allow for targeting of LE interventions. (4) Fourth, we will test in a randomized trial whether patient-specific LE estimates— communicated in a patient-centered approach as determined in the first and second aims and targeted to specific high-yield situations as identified in the third aim—along with LE-specific conjoint analysis data improve decisional conflict, quality of LE data discussed, and reduce overtreatment of GU malignancies. We anticipate that this patient-centered approach will improve shared decision making and ultimately result in better treatment choices for patients with GU cancers and limited LE.