摘要
目的探讨预后营养指数(prognostic nutritional index,PNI)及淋巴细胞与单核细胞比值(lymphocyte-monocyte ratio,LMR)对头颈肿瘤(head and neck cancer,HNC)患者治疗期间发生重度放射性口腔黏膜炎(radiotherapy-induced oral mucositis,RIOM)的预测价值,构建风险预测模型并检验预测效果。方法选取2021年9月~2023年10月就诊于中南大学湘雅医院行放射治疗的502例HNC患者作为研究对象,回顾性分析相关资料,将所有研究对象以7:3的比例随机分为建模组和验证组。根据是否发生重度RIOM将建模组的研究对象分为重度RIOM组和非重度RIOM组,通过单因素分析和Logistic回归分析筛选HNC患者治疗期间发生重度RIOM的危险因素并建立预测模型,采用受试者工作特征(ROC)曲线评价其预测效果,采用R4.3.2软件绘制可视化列线图和决策曲线。结果HNC患者治疗期间发生重度RIOM的风险预测模型纳入合并症数量(OR=2.221,95%CI=1.185~4.165)、手术史(OR=2.938,95%CI=1.393~6.198)、肿瘤分化程度(OR=1.511,95%CI=1.090~2.094)、PNI(OR=0.892,95%CI=0.852~0.934)、LMR(OR=0.512,95%CI=0.254~1.030)共5个预测因子。模型公式:Y=2.102+0.413×分化程度+0.798×合并症数量+1.078×手术史-0.114×PNI-0.669×LMR。验证结果显示,建模组和验证组ROC曲线下面积分别为0.847(P<0.001)、0.808(P<0.001)。建模组和验证组Hosmer-Lemeshow检验P均>0.05。决策曲线在大部分高风险阈值范围内高于参考线。结论该研究构建的风险预测模型效果良好,可作为临床人员预测HNC患者治疗期间重度RIOM的发生风险,为采取预防性管理措施提供参考。
OBJECTIVE To investigate the predictive value of prognostic nutritional index(PNI)and lymphocyte-monocyte ratio(LMR)in severe radiotherapy-induced oral mucositis(RIOM)during treatment of patients with head and neck cancer,and to construct a risk prediction model and test the prediction effect.METHODS A total of 502 patients with head and neck cancer who underwent radiotherapy were recruited from September 2021 to October 2023 in Xiangya Hospital Central South University.The participants were randomly divided into training group and validation group at a ratio of 7∶3.According to whether severe RIOM occurred,they were divided into severe RIOM group and non-severe RIOM group.Univariate analysis and logistic regression analysis were used to screen the risk factors of severe RIOM.The receiver operating characteristic(ROC)curve was used to evaluate its prediction effect and R4.3.2 software was used to draw nomograms and decision curve.RESULTS The risk prediction model for patients with head and neck cancer during treatment had five factors,including the number of comorbidities(OR=2.221,95%CI=1.185-4.165),surgical history(OR=2.938,95%CI=1.393-6.198),the degree of tumor differentiation(OR=1.511,95%CI=1.090-2.094),PNI(OR=0.892,95%CI=0.852-0.934),LMR(OR=0.512,95%CI=0.254-1.030).Model formula:Y=2.102+0.413×degree of differentiation+0.798×number of comorbidities+1.078×surgical history-0.114×PNI-0.669×LMR.The validation results of the prediction model showed that the area under the ROC curve of the training group was 0.847(P<0.001),the area under the curve of the validation group was 0.808(P<0.001),and the P values of the Hosmer-Lemeshow test of the modeling group and the validation group were both greater than 0.05.The decision curve was above the reference line within most of the high-risk thresholds.CONCLUSION The risk prediction model constructed in this study has good effect,which can predict the risk of severe RIOM during radiotherapy in patients with head and neck cancer,providing the reference for taking preventive intervention measures for high-risk patients.
作者
高菲
刘美子
吴子童
安然
陈文凤
GAO Fei;LIU Meizi;WU Zitong;AN Ran;CHEN Wenfeng(Xiangya School of Nursing,Changsha,Hunan,410013,China;Department of Head and Neck Cancer,Xiangya Hospital Central South University,Changsha,Hunan,410008,China;School of Nursing and Rehabilitation,Nantong University,Nantong,Jiangsu,226019,China)
出处
《中国耳鼻咽喉头颈外科》
CSCD
2024年第9期559-564,共6页
Chinese Archives of Otolaryngology-Head and Neck Surgery
基金
湖南省卫生健康委科研课题(D202309038051)。
关键词
头颈部肿瘤
重度放射性口腔黏膜炎
预后营养指数
淋巴细胞与单核细胞比值
预测模型
Head and Neck Neoplasms
severe radiotherapy-induced oral mucositis
prognostic nutritional index
lymphocyte-to-monocyte ratio
prediction model
