Zhang Longfu, Liu Jie, Yang Dawei, Ni Zheng, Lu Xinyuan, Liu Yalan, Liu Zilong, Wang Hao, Feng Mingxiang, Zhang Yong
Department of Pulmonary and Critical Care Medicine, Shanghai Xuhui Central Hospital, Shanghai 200031, China.
Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Diagnostics (Basel). 2023 Jul 14;13(14):2376. doi: 10.3390/diagnostics13142376.
Patients with pathological stage IA lung adenocarcinoma (LUAD) are at risk of relapse. The value of the TNM staging system is limited in predicting recurrence. Our study aimed to develop a precise recurrence prediction model for stage IA LUAD.
Patients with pathological stage IA LUAD who received surgical treatment at Zhongshan Hospital Fudan University were retrospectively analyzed. Multivariate Cox proportional hazards regression models were used to create nomograms for recurrence-free survival (RFS). The predictive performance of the model was assessed using calibration plots and the concordance index (C-index).
The multivariate Cox regression analysis revealed that CTR (0.75 < CTR ≤ 1; HR = 9.882, 95% CI: 2.036-47.959, = 0.004) and solid/micropapillary-predominance (SMPP; >5% and the most dominant) (HR = 4.743, 95% CI: 1.506-14.933, = 0.008) were independent prognostic factors of RFS. These risk factors were used to construct a nomogram to predict postoperative recurrence in these patients. The C-index of the nomogram for predicting RFS was higher than that of the eighth T-stage system (0.873 for the nomogram and 0.643 for the eighth T stage). The nomogram also achieved good predictive performance for RFS with a well-fitted calibration curve.
We developed and validated a nomogram based on CTR and SMP patterns for predicting postoperative recurrence in pathological stage IA LUAD. This model is simple to operate and has better predictive performance than the eighth T stage system, making it suitable for selecting further adjuvant treatment and follow-up.
病理分期为IA期的肺腺癌(LUAD)患者存在复发风险。TNM分期系统在预测复发方面价值有限。我们的研究旨在为IA期LUAD开发一种精确的复发预测模型。
回顾性分析在复旦大学附属中山医院接受手术治疗的病理分期为IA期LUAD患者。使用多变量Cox比例风险回归模型创建无复发生存期(RFS)的列线图。使用校准图和一致性指数(C指数)评估模型的预测性能。
多变量Cox回归分析显示,CTR(0.75 < CTR ≤ 1;HR = 9.882,95% CI:2.036 - 47.959,P = 0.004)和实性/微乳头为主型(SMPP;>5%且为最主要类型)(HR = 4.743,95% CI:1.506 - 14.933,P = 0.008)是RFS的独立预后因素。这些危险因素用于构建列线图以预测这些患者术后复发。预测RFS的列线图的C指数高于第八版T分期系统(列线图为0.873,第八版T分期为0.643)。列线图在预测RFS方面也具有良好的预测性能,校准曲线拟合良好。
我们开发并验证了一种基于CTR和SMP模式的列线图,用于预测病理分期为IA期LUAD患者的术后复发。该模型操作简单,预测性能优于第八版T分期系统,适用于选择进一步的辅助治疗和随访。