Liu Hao, Li Yu, Qu Yi-Dan, Zhao Jun-Jiang, Zheng Zi-Wen, Jiao Xue-Long, Zhang Jian
Department of Colonrectal Surgery, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China.
Rheumatology and Immunology Department, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China.
World J Clin Cases. 2021 Mar 6;9(7):1563-1579. doi: 10.12998/wjcc.v9.i7.1563.
Nomograms for prognosis prediction in colorectal cancer patients are few, and prognostic indicators differ with age.
To construct a new nomogram survival prediction tool for middle-aged and elderly patients with stage III rectal adenocarcinoma.
A total of 2773 eligible patients were divided into the training cohort (70%) and the validation cohort (30%). Optimal cutoff values were calculated using the X-tile software for continuous variables. Univariate and multivariate Cox proportional hazards regression analyses were used to determine overall survival (OS) and cancer-specific survival (CSS)-related prognostic factors. Two nomograms were successfully constructed. The discriminant and predictive ability and clinical usefulness of the model were also assessed by multiple methods of analysis.
The 95%CI in the training group was 0.719 (0.690-0.749) and 0.733 (0.702-0.74), while that in the validation group was 0.739 (0.696-0.782) and 0.750 (0.701-0.800) for the OS and CSS nomogram prediction models, respectively. In the validation group, the AUC of the three-year survival rate was 0.762 and 0.770, while the AUC of the five-year survival rate was 0.722 and 0.744 for the OS and CSS nomograms, respectively. The nomogram distinguishes all-cause mortality from cancer-specific mortality in patients with different risk grades. The time-dependent AUC and decision curve analysis showed that the nomogram had good clinical predictive ability and decision efficacy and was significantly better than the tumor-node-metastases staging system.
The survival prediction model constructed in this study is helpful in evaluating the prognosis of patients and can aid physicians in clinical diagnosis and treatment.
用于预测结直肠癌患者预后的列线图较少，且预后指标因年龄而异。
构建一种用于预测中老年III期直肠腺癌患者生存情况的新型列线图预测工具。
将总共2773例符合条件的患者分为训练队列（70%）和验证队列（30%）。使用X-tile软件计算连续变量的最佳截断值。采用单因素和多因素Cox比例风险回归分析来确定总生存（OS）和癌症特异性生存（CSS）相关的预后因素。成功构建了两个列线图。还通过多种分析方法评估了模型的判别能力、预测能力和临床实用性。
训练组中OS和CSS列线图预测模型的95%CI分别为0.719（0.690 - 0.749）和0.733（0.702 - 0.74），而验证组中分别为0.739（0.696 - 0.782）和0.750（0.701 - 0.800）。在验证组中，三年生存率的AUC对于OS和CSS列线图分别为0.762和0.770，而五年生存率的AUC分别为0.722和0.744。该列线图可区分不同风险等级患者的全因死亡率和癌症特异性死亡率。时间依赖性AUC和决策曲线分析表明，该列线图具有良好的临床预测能力和决策效能，且显著优于肿瘤-淋巴结-转移分期系统。
本研究构建的生存预测模型有助于评估患者预后，并可为医生的临床诊断和治疗提供帮助。
