Department of Urology, University Hospitals Leuven, Leuven, Belgium.
Department of Urology, Selçuk University, Konya, Turkey.
BJU Int. 2020 Dec;126(6):704-714. doi: 10.1111/bju.15163. Epub 2020 Aug 12.
To perform an external validation of the Cancer of the Bladder Risk Assessment (COBRA) score for estimating cancer-specific survival (CSS) after radical cystectomy (RC) in a large bi-institutional cohort of patients.
Patients treated with RC and lymph node dissection (LND) between May 1996 and July 2017 were retrieved from the RC databases of Leuven and Turin. Collected variables were age at RC, tumour stage, lymph node (LN) density, neoadjuvant chemotherapy, the extent of LND, and nodal stage. The primary outcome was CSS visualised using Kaplan-Meier plots. Cox proportional hazard models were used to assess the impact of variables on CSS. We performed a pairwise comparison between the COBRA score levels using a log-rank test corrected by Bonferroni, and developed a simplified COBRA score with three risk categories. To compare models, we assessed concordance indices (C-indices), receiver operating characteristic curves with area under the curve (AUC), calibration plots, and decision curve analysis (DCA). Finally, we compared both COBRA and simplified COBRA models with the established American Joint Committee on Cancer (AJCC) model.
A total of 812 patients were included. All COBRA score variables had a significant impact on CSS in a Cox proportional hazard model. However, pairwise comparison of the COBRA subscores could not differentiate significantly between all COBRA score levels. Based on these findings, we developed a simplified COBRA score by introducing three categories within the following COBRA score ranges: low- (0-1) vs intermediate- (2-4) vs high-risk (5-7). A pairwise comparison could discriminate significantly between all COBRA risk categories. When finally comparing COBRA and simplified COBRA models with the AJCC model, AJCC performed better than both. C-indices, AUCs, calibration plots and DCA for AJCC were all better compared with the original and simplified COBRA models.
We performed an external validation of the COBRA score in a large bi-institutional cohort. We observed that several risk groups had overlapping CSS, demonstrating suboptimal performance of the COBRA score. Therefore, we constructed a simplified model with three COBRA score risk categories. This model resulted in demarcated risk groups with non-overlapping CSS and good predictive accuracy. However, both COBRA score models were outperformed by the AJCC staging system. Therefore, we conclude that the AJCC staging system should remain the current standard for stratifying patients after RC for CSS.
在一个大型的双机构患者队列中，对用于估计根治性膀胱切除术 (RC) 后癌症特异性生存 (CSS) 的膀胱癌风险评估 (COBRA) 评分进行外部验证。
从鲁汶和都灵的 RC 数据库中检索了 1996 年 5 月至 2017 年 7 月期间接受 RC 和淋巴结清扫术 (LND) 的患者。收集的变量包括 RC 时的年龄、肿瘤分期、淋巴结 (LN) 密度、新辅助化疗、LND 的范围和淋巴结分期。主要结局是通过 Kaplan-Meier 图观察 CSS。Cox 比例风险模型用于评估变量对 CSS 的影响。我们使用对数秩检验对 COBRA 评分水平进行了两两比较，并通过 Bonferroni 进行了校正，并开发了一个具有三个风险类别的简化 COBRA 评分。为了比较模型，我们评估了一致性指数 (C 指数)、曲线下面积 (AUC) 的接收者操作特征曲线、校准图和决策曲线分析 (DCA)。最后，我们将 COBRA 和简化 COBRA 模型与既定的美国癌症联合委员会 (AJCC) 模型进行了比较。
共纳入 812 例患者。在 Cox 比例风险模型中，COBRA 评分的所有变量对 CSS 均有显著影响。然而，COBRA 亚评分的两两比较不能显著区分所有 COBRA 评分水平。基于这些发现，我们通过在以下 COBRA 评分范围内引入三个类别，引入了简化的 COBRA 评分：低危 (0-1) 与中危 (2-4) 与高危 (5-7)。可以显著区分 COBRA 所有风险类别。当最终将 COBRA 和简化 COBRA 模型与 AJCC 模型进行比较时，AJCC 的表现优于两者。与原始和简化的 COBRA 模型相比，C 指数、AUC、校准图和 DCA 均有所改善。
我们在一个大型的双机构队列中对 COBRA 评分进行了外部验证。我们观察到，几个风险组的 CSS 有重叠，表明 COBRA 评分的表现不佳。因此，我们构建了一个具有三个 COBRA 评分风险类别的简化模型。该模型产生了具有非重叠 CSS 的明确风险组和良好的预测准确性。然而，COBRA 评分模型均优于 AJCC 分期系统。因此，我们得出结论，AJCC 分期系统应继续成为 RC 后 CSS 患者分层的当前标准。
