Wang Wei, Teng Fei, Bu Shi, Xu Wei, Cai Qing-Chun, Jiang Yue-Quan, Wang Zhi-Qiang
Key Laboratory for Biorheological Science and Technology of Ministry of Education (Chongqing University), Chongqing University Cancer Hospital, Chongqing, 400030, China.
Risk Manag Healthc Policy. 2022 Aug 25;15:1581-1592. doi: 10.2147/RMHP.S373510. eCollection 2022.
This study aimed to design a nomogram survival prediction by means of the figures retrieved from the Surveillance, Epidemiology, and End Results (SEER) source bank, and to predict the overall survival (OS) of patients with stage IIA non-small cell lung cancer (NSCLC) after surgery.
Data for 4511 patients who had been diagnosed with postoperative stage IIA NSCLC were collected from the SEER databank, while information on 528 patients was acquired from the Chongqing University Cancer Hospital for the external validation cohort. The independent risk factors that affected the prognosis were identified using a multivariate Cox proportional hazards regression model (also used to conduct a nomogram). A survival analysis between the low- and the high-risk groups was performed using the Kaplan-Meier method. Furthermore, a subgroup analysis was conducted of the two groups using the Kaplan-Meier method to determine whether the patients had received adjuvant chemotherapy.
The following five variables were integrated into the nomogram: sex (female: HR 1.73, 95% CI 0.64-0.83), age (≥60: HR 1.61, 95% CI 1.39-1.87), differentiation grade (grade II: HR 2.19, 95% CI 1.66-2.88; grade III: HR 2.65, 95% CI 2.00-3.51; grade IV: HR 3.17, 95% CI 1.99-5.03), surgery (lobectomy: HR 0.72, 95% CI 0.59-0.86), and lymph node resection (>12: HR 0.82, 95% CI 0.70-0.96). Furthermore, the patients selected were categorized into high- and low-risk groups. The OS rate was significantly lower in the high-risk group than in the low-risk group (P < 0.001). Finally, adjuvant chemotherapy was highly correlated with OS in the high-risk set (P = 0.035); however, adjuvant chemotherapy was not related to OS in the low-risk set.
A nomogram was created as a reliable, convenient scheme that could predict OS, and it was determined that the high-risk feature patients identified by the nomogram gained benefits from adjuvant chemotherapy.
本研究旨在通过从监测、流行病学和最终结果(SEER)数据库中提取的数据设计一个列线图生存预测模型,以预测IIA期非小细胞肺癌(NSCLC)患者术后的总生存期(OS)。
从SEER数据库收集4511例诊断为IIA期NSCLC术后患者的数据,同时从重庆大学附属肿瘤医院获取528例患者的信息作为外部验证队列。使用多因素Cox比例风险回归模型(也用于构建列线图)确定影响预后的独立危险因素。采用Kaplan-Meier法对低风险组和高风险组进行生存分析。此外,采用Kaplan-Meier法对两组进行亚组分析,以确定患者是否接受了辅助化疗。
以下五个变量被纳入列线图:性别(女性:HR 1.73,95%CI 0.64-0.83)、年龄(≥60岁:HR 1.61,95%CI 1.39-1.87)、分化程度(II级:HR 2.19,95%CI 1.66-2.88;III级:HR 2.65,95%CI 2.00-3.51;IV级:HR 3.17,95%CI 1.99-5.03)、手术方式(肺叶切除术:HR 0.72,95%CI 0.59-0.86)和淋巴结清扫数量(>12枚:HR 0.82,95%CI 0.70-0.96)。此外,将入选患者分为高风险组和低风险组。高风险组的OS率显著低于低风险组(P < 0.001)。最后,辅助化疗与高风险组的OS高度相关(P = 0.035);然而,辅助化疗与低风险组的OS无关。
创建了一个列线图作为一种可靠、便捷的方案来预测OS,并确定通过列线图识别出的高风险特征患者可从辅助化疗中获益。