Background

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.

Objective

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.

Intervention

Patient-reported urinary, sexual, and bowel function up to 5 yr after treatment.

Outcome measurements and statistical analysis

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.

Results and limitations

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/.

Conclusions

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.

Patient summary

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.

中文翻译：

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一种基于网络的工具的开发和内部验证，用于纵向预测放射治疗、手术或观察后的性、泌尿和肠功能。

背景

指导局部前列腺癌治疗的共同决策需要提供当代治疗方案（包括根治性前列腺切除术 [RP]、调强放射治疗 [RT] 和主动监测 [AS]）的预期生活质量 (QOL) 结果. 基于个性化特征预测这些 QOL 结果是必要的。

客观的

创建一个易于使用的工具来预测 RP、RT 和 AS 后个性化的性、泌尿、肠道和激素功能结果。

设计、设置和参与者

一项前瞻性、基于人群的队列研究利用美国癌症登记处 2563 名在 2011-2012 年诊断为局限性前列腺癌的男性进行。

干涉

治疗后长达 5 年的患者报告的泌尿、性和肠道功能。

结果测量和统计分析

使用 26 项扩展前列腺指数综合 (EPIC-26) 问卷收集患者报告的治疗后 5 年的尿、性、肠道和激素功能。预测领域评分的综合模型是合适的，其中包括年龄、种族、D'Amico 分类、体重指数、EPIC-26 基线功能、治疗和衡量合并症、一般 QOL 和心理社会健康的标准化评分。我们通过删除仪器评分并用前列腺特异性抗原 (PSA) 和 Gleason 评分替换 D'Amico 分类来减少这些模型。对于最终模型，我们执行了引导程序内部验证以评估模型校准，从中开发了一个易于使用的基于网络的工具。

结果和限制

预测模型在性功能、尿失禁、尿刺激、肠道和激素领域的偏差校正 R 平方值分别为 0.386、0.232、0.183、0.214 和 0.309。综合模型和简约模型之间 R 平方值的差异幅度很小。校准非常好。基于 Web 的工具可从 https://statez.shinyapps.io/PCDSPred/ 获得。

结论

局部前列腺癌治疗后的功能结果可以在诊断时根据年龄、种族、PSA、活检分级、基线功能和关于整体健康的一般问题进行预测。提供者和患者可以使用此预测工具为共同决策提供信息。

患者总结

在本报告中，我们研究了患者在接受根治性前列腺切除术、放射治疗或局部前列腺癌主动监测治疗后 5 年内报告的性、泌尿、激素和肠道功能。我们开发了一种基于网络的预测工具，可用于根据年龄、种族、前列腺特异性抗原、活检分级、治疗前基线功能和关于整体健康的一般问题来预测治疗后的结果。我们希望患者和提供者都可以使用该工具更好地了解治疗后的预期结果，进一步加强提供者和患者之间的共同决策。