摘要
目的观察使用外源性胰岛素治疗的T2DM患者血清胰岛素/C-P比值与胰岛素抗体(IA)之间的关系。方法对2009年至2013年283例检测过IA并使用外源性胰岛素及胰岛素类似物治疗的T2DM患者进行回顾性研究,按照IA测定结果将其分为IA阳性组及IA阴性组,采用受试者工作特征(ROC)曲线评价血清胰岛素及C-P与IA阳性的关系,寻找最佳预测切点。结果 IA阳性组FIns和2 hIns与C-P比值高于IA阴性组(P<0.0001)。FIns、2 hIns、FIns/FC-P比值、2 hIns/2 hC-P比值可分别用来预测IA(P<0.0001),其中FIns/FC-P预测效果最好,达到0.881。当FIns/FC-P为8.6时,预测IA的敏感性为80%,特异性为83%。结论 IA阳性组的血清胰岛素监测值升高,血清胰岛素升高与C-P变化不成比例。使用外源性胰岛素的T2DM患者,当FIns/FC-P比值>8.6或2 hIns/2 hC-P比值>17.8时,说明体内可能存在IA,比值越高,可能性越大。
Objective To observe the relationship between serum insulin/C-peptide ratios and insulin antibody（IA） in type 2 diabetic patients（T2DM） treated with exogenous insulin Methods 283T2 DM patients treated with exogenous insulin and insulin analogues in West China Hospital from 2009 to2013 were divided into IA positive group and IA negative group.The relationships between serum insulin（Ins）,C peptide（C-P）,Ins/C-P ratio and IA were evaluated using receiver operating characteristic（ROC）curve to find the best predictive point for positive IA.Results FIns,2 hIns,FIns/FC-P and 2 hIns/2 hC-P were higher in IA positive group than in IA negative group（P〈0.0001）.The ROC curve of FIns,2 hIns,FIns/FC-P and 2 hIns/2 hC-P for IA showed that the area under the ROC curve（AUC） were0.804,0.738,0.881 and 0.865 respectively.The optimal operation point（OOP） of FIns/FC-P was 8.6with the sensitivity of 80%and the specificity of 83%.Conclusion Serum insulin increases significantly in IA positive group and the increase of insulin is not consistent with C-P change.In T2 DM patients treated with insulin,when FIns/FC-P ratio above 8.6 or 2 hIns/2 hC-P ratio above 17.8,it may indicate the existence of insulin antibodies and the higher the ratio is,the bigger the possibility is.
作者
郭蓉
田浩明
陈卫中
周方励
GUO Rong TIAN Hao-ming CHEN We＆zhong et al(Department of Endocrinology and Metabolism, West China Hospital, Chengdu 610041, China)
出处
《中国糖尿病杂志》
CAS
CSCD
北大核心
2017年第2期131-134,共4页
Chinese Journal of Diabetes
关键词
血清胰岛素/C肽比值
胰岛素抗体
受试者工作特征曲线
Insulin/C peptide ratio
Insulin antibody（IA）
Receiver operating characteristic（ROC） curve
