基于肺癌患者营养状况构建肺癌患者营养治疗与治疗响应的预测模型  

A prediction model of nutritional management and treatment response of lung cancer patients was constructed based on the nutritional status of lung cancer patients

作　　者：梁思燕 李怡[1] 许琼[1] Liang Siyan;Li Yi;Xu Qiong(Department of Oncology,Xiaolan People's Hospital of Zhongshan,Zhongshan 528400,Guangdong,China)

机构地区：[1]中山市小榄人民医院/中山市第五人民医院肿瘤科,广东中山528400

出　　处：《肿瘤代谢与营养电子杂志》2025年第1期99-104,共6页Electronic Journal of Metabolism and Nutrition of Cancer

基　　金：广东省中山市医学科研项目(2021A020329)。

摘　　要：目的探索基于肺癌患者营养状况模型构建在肺癌患者营养管理中的效果,并建立多因素Logistic回归分析预后影响因素。方法选取中山市小榄人民医院肿瘤科2021年4月至2024年4月期间收治的178例肺癌临床资料进行回顾性分析,根据时间点分组,以2022年12月为截断点,2022年12月之前接受常规营养治疗的89例患者作为对照组,2022年12月之后接受基于营养状况构建的营养治疗的89例患者作为试验组,比较两组营养指标、人体成分指标差异后,再统计患者并发症发生情况,根据有无出现并发症分为两组,即预后较好组(n=146,未出现并发症),预后欠佳组(n=32,出现并发症),比较两组一般资料后,经多因素Logistic回归分析影响预后因素。结果试验组和对照组患者经治疗后白蛋白、总蛋白、血红蛋白、患者主观整体评估(PG-SGA)评分、内脏脂肪面积、体脂百分比、骨骼肌、蛋白质指标均较同组治疗前有所改善(P<0.05),而试验组治疗后2周的白蛋白水平(46.39±4.58)g/L、总蛋白水平(62.49±3.58)g/L、血红蛋白水平(116.68±7.78)g/L、内脏脂肪面积(80.35±4.68)cm^(2)、体脂百分比(25.57±2.51)%、骨骼肌(26.85±2.31)kg、蛋白质水平(9.85±1.26)kg高于对照组(P<0.05),PG-SGA评分(3.86±1.78)分低于对照组(P<0.05),试验组治疗后的营养指标、人体成分指标差值也更优于对照组(P<0.05)。同时,经多因素Logistic回归分析,临床分期Ⅳ期、常规营养治疗是影响肺癌患者预后情况的独立危险因素(P<0.05)。结论基于患者营养状况构建营养治疗干预效果显著,可改善肺癌患者的营养状态。然而,临床分期Ⅳ期、常规营养治疗会对肺癌患者预后产生不利影响,因此对于病情较重者需合理选择营养治疗。Objective Explore the effect of the model construction based on the nutritional status of lung cancer patients in the nutritional management of lung cancer patients,and establish a binary Logisticregression to analyze the prognostic factors.Method The clinical data of 178 cases of lung cancer admitted in Zhongshan Xiaolan People's Hospital from April 2021 to April 2024 were selected for retrospective analysis,group according to the time points,taking December 2022 as the cut-off point,of the 89 patients who received routine nutritional support before December 2022 and served as controls,89 patients who received nutritional management after December 2022constructed based on nutritional status as the observation group,after comparing the differences between nutritional indicators and human composition indexes,recount the occurrence of patient complications,Divided into two groups according to the presence of presence,that is,the better prognosis group(n=146,no complications have occurred),Group with poor prognosis(n=32,complications occur),After comparing the two groups of general data,Prognostic factors were influenced by the binary Logistic regression analysis.Result In the observation group and the control group,albumin,total protein,hemoglobin,PG-SGA score,visceral fat area,body fat percentage,skeletal muscle,and protein index all improved compared with the same group(P<0.05),however,albumin(46.39±4.58)g/L,total protein(62.49±3.58)g/L,hemoglobin(116.68±7.78)g/L,visceral fat area(80.35±4.68)cm^(2),body fat percentage(25.57±2.51)%,skeletal muscle(26.85±2.31)kg,protein(9.85±1.26)kg was higher than the control group(P<0.05),ThePG-SGA score(3.86±1.78)score was lower than that of the controlgroup(P<0.05),The difference between nutrition index and human composition index in the observation group was also better than that in the control group(P<0.05).Meanwhile,by binary Logistic regression analysis,clinical stage Ⅳ and routine nutritional support were independent factors affecting the prognosis of lung cancer

关 键 词：肺癌 营养状况 营养治疗 治疗响应 预测模型 预后 营养风险筛查 康复 

分 类 号：R73[医药卫生—肿瘤]