基于血清miR-504-3p、miR-151a-5p 及VEGF 的多指标模型 预测晚期非小细胞肺癌患者长期生存与转移风险

A Multi-index Model Based on Serum miR-504-3p， miR-151a-5p，and VEGF for Predicting Long-term Survival and Metastatic Risk in Patients with Advanced Non-small Cell Lung Cancer

摘要

目的 建立并内部验证结合血清中miR-504-3p、miR-151a-5p 与血管内皮生长因子（vascular endothelial growth factor，VEGF）的多指标预测模型，评估其对预测晚期非小细胞肺癌（non-small cell lung cancer，NSCLC）患者5 年生存率及转移风险的预测价值。方法 采用回顾性队列研究，选取2016 年1 月至2019 年12月本院确诊的264 例晚期NSCLC 患者，均完成5 年追踪随访，按生存状况分为存活组（n = 58）与死亡组（n =206）。采用多因素Cox 回归筛选影响晚期NSCLC 患者5 年生存的关键因素并构建线性预后指数（prognostic index，PI）模型；绘制时间依赖受试者工作特征曲线（receiver operating characteristic curve，ROC）曲线，计算曲线下面积（area under the curve，AUC）评估模型区分度；通过Bootstrap 法（重复500 次）进行内部验证，以校准曲线及校准截距、斜率评估模型校准度；采用决策曲线分析（decision curve analysis，DCA）评估模型的临床净收益。结果 miR-151a-5p、VEGF、临床分期Ⅳ期是晚期NSCLC 患者5 年生存的独立危险因素（P < 0.05），miR-504-3p 是保护因素（P < 0.05）。时间依赖ROC 曲线显示，模型预测死亡风险的AUC 由1 年的0.703（95%CI: 0.637～0.769）提升至5 年的0.859（95%CI: 0.814～0.904），预测转移风险的AUC 由1 年的0.694（95%CI: 0.624～0.764）提升至5 年的0.847（95%CI: 0.802～0.892），区分能力随时间推移逐渐增强。校准曲线及量化指标显示，模型对3、4、5 年死亡及转移风险的预测校准度良好（校准截距接近0，校准斜率接近1），但1、2 年校准度欠佳。DCA 结果显示，在预测3 年、4 年和5 年死亡和转移风险时，PI 模型在广泛的阈值概率范围内均能提供高于“全部干预”和“全部不干预”策略的净获益。根据PI 中位数将264 例患者分为高风险组（n = 175）和低风险组（n = 89）。Kaplan-Meier 生存分析显示，低风险组患者的5 年生存率与无转移率均显著优于高风险组（P < 0.05）。结论 血清miR-504-3p、miR-151a-5p、VEGF 与晚期NSCLC 患者长期生存及转移风险密切相关。整合三者及临床分期的多指标预测模型，对晚期NSCLC 患者3 年及以上的长期生存与转移风险具有良好的预测准确性，有助于临床识别高复发转移风险的患者。

Abstract

Objective To establish and internally validate a multi-indicator predictive model incorporating serum miR-504-3p，miR-151a-5p，and vascular endothelial growth factor （VEGF） to evaluate its predictive value for the 5-year survival rate and metastasis risk in patients with advanced non-small cell lung cancer （NSCLC）. Methods A retrospective cohort study was conducted on 264 advanced NSCLC patients diagnosed between January 2016 and December 2019 at our institution，all of whom completed a 5-year follow-up. Patients were stratified into survival （n = 58） and mortality （n = 206） groups based on survival status. Multivariate Cox regression analysis was used to identify key factors affecting 5-year survival in advanced NSCLC patients，and a linear prognostic index （PI） model was constructed. Time-dependent receiver operating characteristic （ROC） curves were generated，and the area under the curve （AUC） was calculated to evaluate model discrimination. Internal validation was performed using the Bootstrap method （500 iterations），with calibration curves，intercepts，and slopes used to assess model calibration. Decision curve analysis （DCA） was employed to evaluate the clinical net benefit of the model. Results miR-151a-5p，VEGF，and clinical stage IV were independent risk factors for 5-year survival in patients with advanced NSCLC （P < 0.05），while miR-504-3p was a protective factor （P < 0.05）. Time-dependent ROC curves demonstrated that the model's AUC for predicting mortality risk increased from 0.703 （95%CI: 0.637～0.769） at 1 year to 0.859 （95%CI: 0.814～0.904） at 5 years，and for predicting metastasis risk increased from 0.694 （95%CI: 0.624～0.764） at 1 year to 0.847 （95%CI: 0.802～0.892） at 5 years，with discriminatory ability progressively strengthening over time. Calibration curves and quantitative metrics demonstrated good calibration of the model for predicting 3-，4-，and 5-year mortality and metastasis risk （calibration intercept approaching 0，calibration slope approaching 1），but suboptimal calibration at 1 and 2 years. DCA results demonstrated that for predicting 3-，4-， and 5-year mortality and metastasis risk，the PI model provided net benefit superior to both "intervene all" and “intervene none” strategies across a wide range of threshold probabilities. Using the PI median，264 patients were stratified into high-risk （n = 175） and low-risk （n = 89） groups. Kaplan-Meier survival analysis showed that 5-year survival and metastasis-free rates in the low-risk group were significantly superior to the high-risk group （P < 0.05）. Conclusion Serum miR-504-3p，miR-151a-5p，and VEGF are closely associated with long-term survival and metastasis in advanced NSCLC patients. A multi-indicator model integrating these three markers and clinical staging demonstrates good predictive accuracy for long-term survival and metastasis risk at 3 years and beyond in advanced NSCLC patients and may facilitate clinical identification of patients at high risk for recurrence and metastasis.

关键词

非小细胞肺癌 / 微小 RNA / 血管内皮生长因子 / 预测模型

Key words

Non-small cell lung cancer / microRNA / Vascular endothelial growth factor / Predictive model

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基金资助

江苏大学临床医学科技发展基金(JLY2021187)