Yu Dong-Dong, Hui Dong, Chen Wei-Kang, Xiao Yun-Bei, Wu Zhi-Gang, Wang Qin-Quan, Zhou Chao-Feng, Chen Zhi-Xia, Li Cheng-Di, Cai Jian
Department of Urology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
Department of Respiratory Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
Transl Cancer Res. 2020 Apr;9(4):2402-2415. doi: 10.21037/tcr.2020.03.59.
To develop a nomogram to predict cancer-specific survival (CSS) in patients with metastatic testicular germ cell tumors (mTGCTs).
Data were obtained from the Surveillance, Epidemiology, and End Results database. Univariate and multivariate Cox regression models were used to identify factors associated with CSS. Survival times between different groups were compared using Kaplan-Meier survival curves and the log-rank test. A nomogram visualization model was established using the R language to predict survival rates. Harrell's concordance index (C-index), the area under the receiver operating characteristic curve (AUC) and calibration plots were used to assess the performance of the model.
We analyzed the data of 949 patients. The median follow-up time was 32 months (range 0 to 83 months), and 224 (23.60%) patients died before the last follow-up, of whom 193 (20.33%) died of mTGCTs. The site of distant metastases was an independent prognostic factor for CSS. Compared to patients without involvement of the corresponding organ, patients with bone, brain, liver, and lung involvement had worse CSS. We also found that age, histological type, surgery, radiation therapy, chemotherapy, metastatic site and insurance status affected the CSS of patients with mTGCTs. We used these prognostic factors to construct our nomogram. Harrell's C-index for CSS was 0.739. The AUC and calibration plots indicated good performance of the nomogram.
A nomogram for predicting CSS in patients with mTGCTs has been developed, which can help patients and clinicians accurately predict mortality risk and recommend personalized treatment modalities.
开发一种列线图以预测转移性睾丸生殖细胞肿瘤(mTGCTs)患者的癌症特异性生存(CSS)情况。
数据来自监测、流行病学和最终结果数据库。采用单因素和多因素Cox回归模型来识别与CSS相关的因素。使用Kaplan-Meier生存曲线和对数秩检验比较不同组之间的生存时间。使用R语言建立列线图可视化模型以预测生存率。采用Harrell一致性指数(C指数)、受试者工作特征曲线下面积(AUC)和校准图来评估模型的性能。
我们分析了949例患者的数据。中位随访时间为32个月(范围0至83个月),224例(23.60%)患者在最后一次随访前死亡,其中193例(20.33%)死于mTGCTs。远处转移部位是CSS的独立预后因素。与相应器官未受累的患者相比,骨、脑、肝和肺受累的患者CSS较差。我们还发现年龄、组织学类型、手术、放疗、化疗、转移部位和保险状况会影响mTGCTs患者的CSS。我们使用这些预后因素构建了我们的列线图。CSS的Harrell C指数为0.739。AUC和校准图表明列线图性能良好。
已开发出一种用于预测mTGCTs患者CSS的列线图,其可帮助患者和临床医生准确预测死亡风险并推荐个性化的治疗方式。