机构地区:[1]沧州市人民医院耳鼻喉科,河北沧州061000
出 处:《山东医药》2023年第33期27-31,共5页Shandong Medical Journal
基 金:河北省2021年度医学科学研究课题计划项目(20211073)。
摘 要:目的分析喉癌(LC)治疗后复发的影响因素,并构建LC治疗后复发的预测模型。方法接受手术切除、放化疗或靶向治疗等治疗方案的LC患者80例,按照随访期内复发情况分为复发组17例、未复发组63例。收集患者的年龄、性别、体质量指数(BMI)、吸烟史、饮酒史、LC家族史、基础疾病、肿瘤分期、肿瘤位置、肿瘤病理分型、肿瘤直径、肿瘤浸润深度、治疗方案等基本资料,采用qRT-PCR法检测血清细胞骨架蛋白4(CKAP4)、N-乙酰氨基半乳糖转移酶2(pp-GalNAc-T2)、跨膜蛋白2(TMEM2)mRNA。采用COX回归分析法分析LC患者治疗后复发的影响因素,采用Logistic回归分析法构建LC治疗后复发的预测模型,采用受试者工作特征曲线(ROC)评估预测模型对LC治疗后复发的预测价值。结果复发组患者肿瘤分期Ⅲ~Ⅳ期占比、血清CKAP4 mRNA相对表达量、血清pp-GalNAc-T2 mRNA相对表达量、血清TMEM2 mRNA相对表达量均显著高于未复发组(P均<0.05)。血清CKAP4 mRNA相对表达量、血清pp-GalNAc-T2 mRNA相对表达量、血清TMEM2 mRNA相对表达量是LC患者治疗后复发的影响因素(P均<0.05)。构建了LC治疗后复发的预测模型,预测概率=-8.967+0.724×血清CKAP4 mRNA相对表达量+0.081×血清pp-GalNAc-T2 mRNA相对表达量+1.132×血清TMEM2 mRNA相对表达量。预测模型的ROC结果显示,该模型对于LC治疗后复发具有较好的预测价值(AUC=0.872,95%CI=0.779~0.962,Cut off值≥0.229,P<0.001),该模型预测LC治疗后复发的灵敏度为88.23%、特异度为79.36%、阴性预测值为96.13%、阳性预测值为53.57%。结论血清CKAP4mRNA相对表达量、血清pp-GalNAc-T2mRNA相对表达量、血清TMEM2 mRNA相对表达量是LC患者治疗后复发的影响因素,基于上述影响因素构建的预测模型对LC治疗后复发具有较高的预测价值。Objective To analyze the factors influencing the recurrence of laryngeal cancer(LC)after treatment and to construct a predictive model for LC recurrence.Methods Eighty patients with LC who had been treated(with sur⁃gical resection,radiotherapy,chemotherapy,or targeted therapy)were divided into the recurrence group(17 cases)and non-recurrence group(63 cases)according to whether a relapse occurred during the follow-up period.The information on the patients'age,sex,body mass index,smoking history,alcohol consumption history,LC family history,underlying dis⁃eases,tumor staging,tumor location,tumor pathological classification,tumor diameter,tumor infiltration depth,treat⁃ment plan,and other factors was collected.Serum mRNA levels of cytoskeletal protein 4(CKAP4),polypeptide N-acetyl⁃galactosamine transferase 2(pp-GalNAc-T2),and transmembrane protein 2(TMEM2)were measured using qRT PCR.Cox regression analysis was performed to analyze the influencing factors for LC recurrence.Logistic regression analysis was performed to construct a predictive model for LC recurrence,and the predictive value of the model for LC recurrence was evaluated using the receiver operating characteristic(ROC)curve.Results The recurrence group showed a significant⁃ly higher proportion of tumors of stages III-IV and significantly higher relative mRNA expression of serum CKAP4,pp-Gal⁃NAc-T2,and TMEM2 than the non-recurrence group(all P<0.05).The relative mRNA expression levels of CKAP4,pp-GalNAc-T2,and TMEM2 in serum were influencing factors for the recurrence of patients with LC after treatment(all P<0.05).We constructed a predictive model for LC recurrence after treatment:predictive probability=−8.967+0.724×the relative expression level of serum CKAP4 mRNA+0.081×the relative expression level of serum pp-GalNAc-T2 mRNA+1.132×the relative expression level of serum TMEM2 mRNA.The ROC curve analysis revealed that the model showed good predictive value for LC recurrence(AUC=0.872,95%CI:0.779-0.962,the cut-off value≥0.229,P<0.001).Th
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