Department of Urology and Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY, USA.
BJU Int. 2012 Mar;109(6):855-9. doi: 10.1111/j.1464-410X.2011.10391.x. Epub 2011 Jul 1.
To evaluate the performance of the Isbarn nomogram for predicting 90-day mortality following radical cystectomy in a contemporary series.
We identified 1141 consecutive radical cystectomy patients treated at our institution between 1995 and 2005 with at least 90 days of follow-up. We applied the published nomogram to our cohort, determining its discrimination, with the area under the receiver operating characteristic curve (AUC), and calibration. We further compared it with a simple model using age and the Charlson comorbidity score.
Our cohort was similar to that used to develop the Isbarn nomogram in terms of age, gender, grade and histology; however, we observed a higher organ-confined (≤pT2, N0) rate (52% vs 24%) and a lower overall 90-day mortality rate [2.8% (95% confidence interval 1.9%, 3.9%) vs 3.9%]. The Isbarn nomogram predicted individual 90-day mortality in our cohort with moderate discrimination [AUC 73.8% (95% confidence interval 64.4%, 83.2%)]. In comparison, a model using age and Charlson score alone had a bootstrap-corrected AUC of 70.2% (95% confidence interval 67.2%, 75.4%).
The Isbarn nomogram showed moderate discrimination in our cohort; however, the exclusion of important preoperative comorbidity variables and the use of postoperative pathological stage limit its utility in the preoperative setting. The use of a simple model combining age and Charlson score yielded similar discriminatory ability and underscores the significance of individual patient variables in predicting outcomes. An accurate tool for predicting postoperative morbidity/mortality following radical cystectomy would be valuable for treatment planning and counselling. Future nomogram design should be based on preoperative variables including individual risk factors, such as comorbidities.
评估伊萨本诺罗格模型在预测根治性膀胱切除术 90 天后死亡率的表现。
我们在本机构确定了 1141 例连续接受根治性膀胱切除术的患者,这些患者在 1995 年至 2005 年间接受了治疗,并且有至少 90 天的随访。我们将发表的诺罗格模型应用于我们的队列,确定其判别能力,使用接受者操作特征曲线(ROC)下的面积(AUC)和校准。我们还将其与使用年龄和 Charlson 合并症评分的简单模型进行了比较。
我们的队列在年龄、性别、分级和组织学方面与用于开发伊萨本诺罗格模型的队列相似;然而,我们观察到更高的器官局限(≤pT2,N0)率(52%对 24%)和总体 90 天死亡率较低[2.8%(95%置信区间 1.9%,3.9%)对 3.9%]。伊萨本诺罗格模型在我们的队列中预测个体 90 天死亡率具有中等判别力[AUC 73.8%(95%置信区间 64.4%,83.2%)]。相比之下,仅使用年龄和 Charlson 评分的模型的自举校正 AUC 为 70.2%(95%置信区间 67.2%,75.4%)。
伊萨本诺罗格模型在我们的队列中表现出中等的判别力;然而,排除重要的术前合并症变量和使用术后病理分期限制了其在术前环境中的应用。使用结合年龄和 Charlson 评分的简单模型产生了相似的判别能力,并强调了个体患者变量在预测结果中的重要性。一种用于预测根治性膀胱切除术后发病率/死亡率的准确工具对于治疗计划和咨询将是有价值的。未来的诺罗格设计应基于包括合并症等个体危险因素的术前变量。