The James Buchanan Brady Urological Institute and Department of Urology, The Johns Hopkins University School of Medicine , Baltimore , Maryland.
Division of Urology, Beth Israel Deaconess Medical Center , Boston , Massachusetts.
J Urol. 2019 May;201(5):886-892. doi: 10.1097/JU.0000000000000033.
We sought to identify predictors of active surveillance in a prospective cohort study of patients with a small renal mass demonstrating favorable outcomes. We generated a summary score to discriminate patients selected for active surveillance or primary intervention.
We analyzed the records of 751 patients from 2009 to 2018 who were enrolled in the DISSRM (Delayed Intervention and Surveillance for Small Renal Masses) Registry to compare active surveillance and primary intervention in the domains of demographics, tumor characteristics, comorbidity and patient reported quality of life. Regression models were created to assess univariable and multivariable model discrimination by the AUC and quality by the AIC (Akaike information criterion). The DISSRM score was based on the most predictive combination of variables and validated for its association with overall survival by Kaplan-Meier survival curves and a Cox proportional hazards regression model.
Of the patients 410 (55%) elected active surveillance and 341 (45%) elected primary intervention. Of the domains patient age, the Charlson comorbidity index, tumor diameter and the SF-12® Physical Component Score had the greatest discrimination for clinical selection into active surveillance. These domains made up the DISSRM score (AUC 0.801). The maximum DISSRM score was 7. The average score for active surveillance was 4.19 (median 4, IQR 2-6) and 72% of scores were 4 or greater. The average score for primary intervention was 3.03 (median 3, IQR 1-5) and 63% of scores were 3 or less. A higher DISSRM score was associated with worse overall survival, for example a score of 6-7 had a HR of 10.45 (95% CI 1.25-87.49, p = 0.03).
The DISSRM score represents a measure of oncologic and competing risks of death in various important domains in patients with a small renal mass. It could be used to guide the management selection. Patients with intermediate scores that express illness uncertainty may require additional workup, such as confirmatory biopsy, to reach a treatment decision.
我们旨在通过一项前瞻性队列研究，确定具有良好预后的小肾肿瘤患者接受主动监测的预测因素。我们生成了一个综合评分，以区分选择主动监测或主要干预的患者。
我们分析了 2009 年至 2018 年间纳入 DISSRM（延迟干预和小肾肿瘤监测）登记处的 751 例患者的记录，以比较主动监测和主要干预在人口统计学、肿瘤特征、合并症和患者报告的生活质量等领域的差异。通过 AUC 评估单变量和多变量模型的区分能力，通过 AIC（Akaike 信息准则）评估质量。DISSRM 评分基于最具预测性的变量组合，并通过 Kaplan-Meier 生存曲线和 Cox 比例风险回归模型验证其与总生存的相关性。
751 例患者中，410 例（55%）选择主动监测，341 例（45%）选择主要干预。在患者年龄、Charlson 合并症指数、肿瘤直径和 SF-12® 生理成分评分等领域，对临床选择主动监测的预测性最强。这些领域构成了 DISSRM 评分（AUC 0.801）。DISSRM 评分最高为 7 分。主动监测的平均评分（中位数 4，四分位距 2-6）为 4.19，72%的评分大于等于 4 分。主要干预的平均评分（中位数 3，四分位距 1-5）为 3.03，63%的评分小于等于 3 分。更高的 DISSRM 评分与总生存较差相关，例如，评分 6-7 的 HR 为 10.45（95%CI 1.25-87.49，p=0.03）。
DISSRM 评分代表了小肾肿瘤患者多个重要领域肿瘤学和死亡竞争风险的衡量标准。它可用于指导管理选择。对于表达疾病不确定性的中等评分患者，可能需要进一步检查，如确认性活检，以做出治疗决策。
