Zheng Honghong, Li Zhehong, Zheng Shuai, Li Jianjun, Yang Ji, Zhao Enhong
Department of Gastrointestinal Surgery, The Affiliated Hospital of Chengde Medical University, Chengde, 067000, People's Republic of China.
Department of Orthopedic, The Affiliated Hospital of Chengde Medical University, Chengde, 067000, People's Republic of China.
Int J Gen Med. 2022 May 25;15:5197-5209. doi: 10.2147/IJGM.S365947. eCollection 2022.
Patients with middle-aged and elderly rectal cancer (MERC) usually have poor prognosis after surgery. This study aimed to develop a nomogram to achieve individualized prediction of overall survival (OS) in patients with MERC and to guide follow-up and subsequent diagnosis and treatment plans.
A total of 349 patients were randomly assigned to the training and validation cohorts in a 7:3 ratio. Multivariate Cox regression analysis was performed using the results of univariate Cox regression analysis to confirm independent prognostic factors of OS. Thereafter, the nomogram was built using the "rms" package. Subsequently, discriminative ability and calibration of the nomogram were evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Integrated discrimination improvement (IDI), net reclassification improvement (NRI), and the area under the ROC curves (AUC) were compared between the nomogram and the tumor-node-metastasis (TNM) staging system (8th edition). Finally, we established a predictive model to assess the survival benefit of patients with MERC by calculating nomogram scores for each patient.
Six variables were identified as independent prognostic factors and included in the nomogram: smoking history, family history, hematochezia, tumor size, N stage, and M stage. Based on these factors, we successfully constructed a nomogram and evaluated its discriminative and predictive abilities using ROC curves, calibration curves, and DCA. ROC curves, IDI, and NRI showed that the nomogram had outstanding clinical utility compared with the TNM staging system (8th edition) for OS prediction. The predictive model successfully distinguished between high-, medium-, and low-risk MERC patients.
Our nomogram provided a more satisfactory survival prediction ability than the TNM staging system (8th edition) for MERC patients. In addition, the nomogram was able to accurately categorize patients into different risk groups after surgery.
中老年直肠癌（MERC）患者术后预后通常较差。本研究旨在开发一种列线图，以实现对MERC患者总生存期（OS）的个体化预测，并指导随访及后续的诊断和治疗方案。
总共349例患者按照7:3的比例随机分配至训练队列和验证队列。使用单因素Cox回归分析结果进行多因素Cox回归分析，以确认OS的独立预后因素。此后，使用“rms”软件包构建列线图。随后，使用受试者工作特征（ROC）曲线、校准曲线和决策曲线分析（DCA）评估列线图的判别能力和校准情况。比较列线图与肿瘤-淋巴结-转移（TNM）分期系统（第8版）之间的综合判别改善（IDI）、净重新分类改善（NRI）以及ROC曲线下面积（AUC）。最后，我们通过计算每位患者的列线图得分建立了一个预测模型，以评估MERC患者的生存获益情况。
六个变量被确定为独立预后因素并纳入列线图：吸烟史、家族史、便血、肿瘤大小、N分期和M分期。基于这些因素，我们成功构建了一个列线图，并使用ROC曲线、校准曲线和DCA评估了其判别和预测能力。ROC曲线、IDI和NRI显示，与TNM分期系统（第8版）相比，列线图在OS预测方面具有出色的临床实用性。该预测模型成功区分了高、中、低风险MERC患者。
对于MERC患者，我们的列线图比TNM分期系统（第8版）提供了更令人满意的生存预测能力。此外，列线图能够在术后准确地将患者分为不同的风险组。
