目的 基于炎症指标和营养指标构建炎症-营养分析评分(inflammation-nutrition risk score,INRS)及其相关列线图,以预测微波消融(microwave ablation,MWA)联合免疫治疗的晚期非小细胞肺癌(non-small cell lung cancer,NSCLC)患者预后.方法 回顾性分析2020年1月1日至2021年12月31日于湖北省中西医结合医院胸外科进行MWA联合免疫治疗的晚期NSCLC患者的临床资料,根据2年随访结果将患者分为存活组和死亡组.采用t检验、卡方检验或Fisher's精确检验筛选存活组和死亡组之间存在统计学差异的炎症指标、营养指标和基线资料.采用Logistic回归探讨具有统计学差异的变量与晚期NSCLC患者预后的关系.基于多因素Lgistic回归结果构建INRS及其相关列线图.采用受试者工作特征(receiver operating characteristics,ROC)曲线、校准曲线和临床决策曲线对INRS及其相关列线图的预测效能、校准能力和临床适用性进行评估.结果 共纳入107例患者,其中存活组80例、死亡组27例.INRS由全身炎症反应指数(systemic inflammatory reponse index,SIRI)、单核细胞/高密度脂蛋白比值(monocyte to high density lipoprotein ratio,MHR)、血红蛋白-白蛋白-淋巴细胞-血小板(hemoglobin,albumin,lymphocyte,and platelet,HALP)复合指标组成,其对预测晚期NSCLC患者死亡具有良好的预测效能[曲线下面积(area under the curve,AUC)=0.804,95％CI:0.710～0.898].体重下降≥ 5％(OR=4.56,95％CI:1.32～15.76,P=0.017)、TNM 分期(Ⅳ期)(0R=4.34,95％CI:1.31～13.36,P=0.016)和 INRS ≥ 0.298(0R=36.98,95％CI:8.12～168.43,P＜0.001)是晚期NSCLC患者2年死亡的独立影响因素.INRS相关列线图模型对晚期NSCLC患者2年死亡预测效能进一步提升(AUC=0.891,95％CI:0.831～0.951).此外,校准曲线和决策曲线分析提示INRS相关列线图具有良好的校准能力和临床适用性.结论 INRS是预测MWA联合免疫治疗的晚期NSCLC患者2年死亡风险的有效生物标志物,INRS相关列线图可作为MWA联合免疫治疗的晚期NSCLC患者随访管理中降低死亡率简单方便且实用的工具.
Construction of a nomogram model for the prognosis of advanced non-small cell lung cancer patients treated with microwave ablation combined with immunotherapy based on inflammatory and nutritional indicators
Objective To construct an inflammation-nutrition risk score(INRS)and its related nomogram based on inflammatory and nutritional indicators to predict the prognosis of advanced non-small cell lung cancer(NSCLC)patients treated with microwave ablation(MWA)combined with immunotherapy.Methods The clinical data of advanced NSCLC patients who underwent MWA combined immunotherapy in the department of thoracic surgery of Hubei Provincial Hospital of Integrated Chinese&Western Medicine from January 1,2020 to December 31,2021 were retrospectively analyzed.Patients were divided into a survival group and a death group based on the 2-year follow-up results.T-test,Chi-square test,or Fisher's exact test were used to select inflammatory indicators,nutritional indicators,and baseline data that showed statistical differences between the survival and death groups.Logistic regression was used to explore the relationship between the variables with statistical differences and the prognosis of patients with advanced NSCLC.The INRS and its related nomogram were constructed based on the results of multivariate Logistic regression.The predictive performance,calibration ability,and clinical applicability of the INRS and its related nomogram were evaluated using the receiver operating characteristic(ROC)curve,calibration curve,and decision curve.Results A total of 107 patients were included,including 80 patients in the survival group and 27 patients in the death group.The INRS,composed of systemic inflammatory reponse index(SIRI),monocyte to high density lipoprotein ratio(MHR),and hemoglobin-albumin-lymphocyte-platelet(HALP),had good predictive efficacy on predicting the death of patients with advanced NSCLC[area under the curve(AUC)=0.804,95％CI:0.710-0.898].Weight loss of＞5％(OR=4.56,95％CI:1.32-15.76,P=0.017),TNM stage(stageⅣ)(OR=4.34,95％CI:1.31-13.36,P=0.016)and INRS＞0.298(OR=36.98,95％CI:8.12-168.43,P＜0.001)were independent influencing factors for the 2-year mortality of patients with advanced NSCLC.The predictive efficacy of the INRS-related nomogram model for the 2-year mortality of patients with advanced NSCLC was further improved(AUC=0.891,95％CI:0.831-0.951).In addition,the calibration curve and decision curve indicated that the INRS-related nomogram has good calibration ability and clinical applicability.Conclusion The INRS is an effective biomarker for predicting the 2-year mortality risk of advanced NSCLC patients treated with MWA combined with immunotherapy.The INRS-related nomogram can serve as a simple and practical tool to reduce mortality in the follow-up management of advanced NSCLC patients treated with MWA combined with immunotherapy.
Non-small cell lung cancerMicrowave ablationImmunotherapyNutritional indicatorsInflammatory indicatorsNomogram model
万方数据
维普
