Bagaria Sanjay P, Wagie Amy E, Gray Richard J, Pockaj Barbara A, Attia Steven, Habermann Elizabeth B, Wasif Nabil
Department of Surgery, Mayo Clinic Florida, Jacksonville, FL, USA.
Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Surgical Outcomes Branch, Rochester, MN, USA.
Ann Surg Oncol. 2015 Dec;22 Suppl 3:S398-403. doi: 10.1245/s10434-015-4849-9. Epub 2015 Sep 9.
A nomogram to predict disease-specific mortality (DSM) following surgery for soft tissue sarcoma (STS) has been developed by the Memorial Sloan Kettering Cancer Center (MSKCC). The goal of this study was to validate this nomogram by assessing discrimination and calibration at the population level using a national cancer database.
Retrospective review of the Surveillance, Epidemiology, and End Results cancer registries identified patients undergoing surgery for STS from 1988 to 2011. Data for patient age, tumor size, tumor grade, histologic subtype, sex, primary tumor location, and tumor depth were entered into the nomogram calculator for each patient. Discrimination was quantified using a concordance index. Calibration was assessed by comparing quintiles of nomogram-predicted probabilities of disease-specific mortality (DSM) with American Joint Committee on Cancer (AJCC) stage DSM.
Overall, 9237 patients were identified with complete information needed for the nomogram. With a mean follow-up of 45 months, the concordance index for nomogram-predicted DSM with actual DSM was 0.74 for the entire cohort. For low- and high-grade tumors, this was 0.71 and 0.66, respectively. Kaplan-Meier curves showed better calibration for nomogram-predicted DSM when compared with AJCC staging.
Our results validate the use of the MSKCC STS nomogram in the general population, with better predictive ability than AJCC staging. However, a concordance index of 0.74 suggests that further improvement in prognostication is needed, perhaps with biological markers or additional clinical variables.
纪念斯隆凯特琳癌症中心(MSKCC)已开发出一种用于预测软组织肉瘤(STS)手术后疾病特异性死亡率(DSM)的列线图。本研究的目的是通过使用国家癌症数据库在人群水平评估区分度和校准度来验证该列线图。
对监测、流行病学和最终结果癌症登记处进行回顾性审查,以确定1988年至2011年接受STS手术的患者。将患者年龄、肿瘤大小、肿瘤分级、组织学亚型、性别、原发肿瘤位置和肿瘤深度的数据输入每位患者的列线图计算器。使用一致性指数对区分度进行量化。通过比较列线图预测的疾病特异性死亡率(DSM)概率的五分位数与美国癌症联合委员会(AJCC)分期的DSM来评估校准度。
总体而言,共识别出9237例具有列线图所需完整信息的患者。平均随访45个月,整个队列中列线图预测的DSM与实际DSM的一致性指数为0.74。对于低级别和高级别肿瘤,该指数分别为0.71和0.66。与AJCC分期相比,Kaplan-Meier曲线显示列线图预测的DSM校准度更好。
我们的结果验证了MSKCC STS列线图在一般人群中的应用,其预测能力优于AJCC分期。然而,0.74的一致性指数表明预后预测仍需进一步改进,或许可通过生物标志物或其他临床变量来实现。