Department of Urology, Vanderbilt University Medical Center, Nashville, TN, USA.
Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA.
Eur Urol. 2020 Aug;78(2):248-255. doi: 10.1016/j.eururo.2020.02.007. Epub 2020 Feb 22.
Shared decision making to guide treatment of localized prostate cancer requires delivery of the anticipated quality of life (QOL) outcomes of contemporary treatment options (including radical prostatectomy [RP], intensity-modulated radiation therapy [RT], and active surveillance [AS]). Predicting these QOL outcomes based on personalized features is necessary.
To create an easy-to-use tool to predict personalized sexual, urinary, bowel, and hormonal function outcomes after RP, RT, and AS.
DESIGN, SETTING, AND PARTICIPANTS: A prospective, population-based cohort study was conducted utilizing US cancer registries of 2563 men diagnosed with localized prostate cancer in 2011-2012.
Patient-reported urinary, sexual, and bowel function up to 5 yr after treatment.
Patient-reported urinary, sexual, bowel, and hormonal function through 5 yr after treatment were collected using the 26-item Expanded Prostate Index Composite (EPIC-26) questionnaire. Comprehensive models to predict domain scores were fit, which included age, race, D'Amico classification, body mass index, EPIC-26 baseline function, treatment, and standardized scores measuring comorbidity, general QOL, and psychosocial health. We reduced these models by removing the instrument scores and replacing D'Amico classification with prostate-specific antigen (PSA) and Gleason score. For the final model, we performed bootstrap internal validation to assess model calibration from which an easy-to-use web-based tool was developed.
The prediction models achieved bias-corrected R-squared values of 0.386, 0.232, 0.183, 0.214, and 0.309 for sexual function, urinary incontinence, urinary irritative, bowel, and hormonal domains, respectively. Differences in R-squared values between the comprehensive and parsimonious models were small in magnitude. Calibration was excellent. The web-based tool is available at https://statez.shinyapps.io/PCDSPred/.
Functional outcomes after treatment for localized prostate cancer can be predicted at the time of diagnosis based on age, race, PSA, biopsy grade, baseline function, and a general question regarding overall health. Providers and patients can use this prediction tool to inform shared decision making.
In this report, we studied patient-reported sexual, urinary, hormonal, and bowel function through 5 yr after treatment with radical prostatectomy, radiation therapy, or active surveillance for localized prostate cancer. We developed a web-based predictive tool that can be used to predict one's outcomes after treatment based on age, race, prostate-specific antigen, biopsy grade, pretreatment baseline function, and a general question regarding overall health. We hope both patients and providers can use this tool to better understand expected outcomes after treatment, further enhancing shared decision making between providers and patients.
为了指导局限性前列腺癌的治疗,需要提供当代治疗方案(包括根治性前列腺切除术[RP]、调强放疗[RT]和主动监测[AS])预期的生活质量(QOL)结果。基于个性化特征预测这些 QOL 结果是必要的。
创建一个易于使用的工具,以预测 RP、RT 和 AS 后患者的个性化性功能、尿控功能、肠功能和激素功能。
设计、地点和参与者:这是一项前瞻性、基于人群的队列研究,利用美国癌症登记处的数据,纳入了 2011-2012 年间诊断为局限性前列腺癌的 2563 名男性。
治疗后长达 5 年的患者报告的尿控、性功能和肠功能。
通过使用 26 项扩展前列腺指数综合评分(EPIC-26)问卷,收集了治疗后长达 5 年的患者报告的尿控、性功能、肠功能和激素功能。综合模型被用于预测各域评分,包括年龄、种族、D'Amico 分类、体重指数、EPIC-26 基线功能、治疗以及衡量合并症、一般 QOL 和心理社会健康的标准化评分。我们通过去除仪器评分和用前列腺特异性抗原(PSA)和 Gleason 评分代替 D'Amico 分类来简化这些模型。对于最终模型,我们进行了 bootstrap 内部验证,以评估模型校准情况,并在此基础上开发了一个易于使用的网络工具。
性功能、尿失禁、尿激惹、肠功能和激素功能域的预测模型的偏倚校正 R-squared 值分别为 0.386、0.232、0.183、0.214 和 0.309。综合模型和简化模型之间 R-squared 值的差异在幅度上很小。校准效果很好。网络工具可在 https://statez.shinyapps.io/PCDSPred/ 上获取。
基于年龄、种族、PSA、活检分级、基线功能和一般健康问题,可以在诊断局限性前列腺癌时预测治疗后的功能结局。医生和患者可以使用该预测工具来辅助做出共同决策。
在这项研究中,我们通过问卷调查,评估了 2563 名局限性前列腺癌患者在接受根治性前列腺切除术、放疗或主动监测治疗后 5 年内的性功能、尿控、激素和肠功能。我们开发了一个基于网络的预测工具,用于预测患者在接受治疗后的结局。该工具基于患者的年龄、种族、前列腺特异性抗原、活检分级、治疗前的基线功能和一般健康问题。我们希望医生和患者都可以使用该工具来更好地了解治疗后的预期结果,从而进一步加强医患之间的共同决策。