目的 本研究旨在通过Cox比例风险回归分析和列线图建模,筛选对非小细胞肺癌患者预后具有影响价值的营养状况指标并构建综合预测模型,将反映患者全身状况的营养-炎症-免疫轴指标纳入评估体系。方法 本研究纳入2019年1月至2022年1月邢台市人民医院收治的177例手术治疗的非小细胞肺癌(NSCLC)患者,根据术后3年生存情况分为死亡组(n=63)和生存组(n=114)。收集两组患者的临床资料及营养状况指标[体质指数(BMI)、骨骼肌肉质量指数(SMI)、前白蛋白(PA)、转铁蛋白(TRF)、血红蛋白-白蛋白-淋巴细胞-血小板复合指标(HALP)、预后营养指数(PNI)、控制营养状况评分(CONUT)]。比较死亡组、生存组上述指标差异,采用Cox比例风险回归模型分析影响预后的因素,并基于筛选出的关键变量构建列线图预测模型。通过ROC曲线评估模型区分度,校准曲线检验预测准确性,决策曲线分析临床获益。结果 单因素分析显示,死亡组患者TNM分期(Ⅲ/Ⅳ期)和低分化占比更高,且SMI和HALP水平显著低于生存组(P<0.05)。Cox比例风险回归模型分析结果显示,肿瘤低分化是增加NSCLC患者死亡风险的独立影响因素,HALP升高是降低NSCLC患者死亡风险的独立影响因素(P<0.05)。模型效能分析显示,单一指标(分化程度、HALP)预测AUC分别为0.591、0.767,综合预测模型的AUC达0.776,校准曲线显示模型预测值与实际观察值高度一致(Bias-corrected曲线接近Ideal线)。决策曲线表明该模型临床净获益>0,优于单纯依赖TNM分期或营养指标。结论 HALP是NSCLC患者预后的独立营养学影响因素。在此基础上,整合了肿瘤分化程度这个关键的临床病理特征,成功构建了一个综合列线图预测模型。
Abstract
Objective This study aims to screen nutritional status indicators with predictive value for the prognosis of lung cancer patients through Cox proportional hazards regression analysis and nomogram modeling, and construct a comprehensive predictive model. The nutrition-inflammation-immune axis indicators reflecting the overall condition of patients will be incorporated into the evaluation system. Method This study included 177 patients with non-small cell lung cancer (NSCLC) who underwent surgical treatment and were admitted to Xingtai People's Hospital from January 2019 to January 2022. They were divided into the death group (n=63) and the survival group (n=114) based on their 3-year survival status after surgery. The clinical data and nutritional status indicators [body mass index (BMI), musculoskeletal mass index (SMI), prealbumin (PA), transferrin (TRF), hemoglobin - albumin - lymphocyte - platelet composite index (HALP), prognostic nutritional index (PNI), and controlled nutritional status score (CONUT)] of the two groups of patients were collected. The differences in the above indicators between the death group and the survival group were compared. Cox proportional hazards regression was used to analyze the independent risk factors affecting prognosis, and a nomogram prediction model was constructed based on the screened key variables. The model discrimination was evaluated by the ROC curve, the prediction accuracy was tested by the calibration curve, and the clinical benefits were analyzed by the decision curve. Result The single-factor analysis showed that the patients in the death group had a higher proportion of TNM stage (stage Ⅲ/Ⅳ) and lower degree of malignancy, and the levels of SMI and HALP were significantly lower than those in the survival group (P < 0.05). The Cox regression results indicated that the degree of tumor differentiation and HALP were the influencing factors for poor prognosis in NSCLC patients (P < 0.05). The model efficacy analysis revealed that the AUC of a single indicator (degree of differentiation, HALP) for prediction was 0.591 and 0.767 respectively, and the AUC of the comprehensive prediction model reached 0.776. The calibration curve showed that the predicted values of the model were highly consistent with the actual observations (the Bias-corrected curve was close to the Ideal line). The decision curve indicated that the clinical net benefit of this model was > 0, which was superior to relying solely on TNM stage or nutritional indicators. Conclusion This study, through Cox regression analysis, clearly confirmed that HALP is an independent nutritional predictor for the prognosis of NSCLC patients. On this basis, by integrating the key clinical pathological feature of tumor differentiation degree, a comprehensive nomogram prediction model was successfully constructed.
关键词
非小细胞肺癌 /
营养状况指标 /
预后营养指数 /
控制营养状况评分 /
预后转归 /
影响因素 /
列线图
Key words
Non-small cell lung cancer /
Nutritional sensitivity index /
Prognostic nutritional index /
Control nutritional status score /
Prognosis /
Influencing factors /
Nomograph
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基金
邢台市重点研发计划自筹项目(2024ZC116)
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