H. Nishikawa, R. Takata, Kazunori Yoh, H. Enomoto, N. Ishii, Y. Iwata, Takashi Nishimura, Nobuhiro Aizawa, Yoshiyuki Sakai, Naoto Ikeda, Kunihiro Hasegawa, Yukihisa Yuri, Tomoyuki Takashima, H. Iijima, S. Nishiguchi
{"title":"Mac-2-binding Protein Glycosylation isomer well correlates with the Controlling Nutritional Status Score in Hepatitis Viruses-related Liver Diseases","authors":"H. Nishikawa, R. Takata, Kazunori Yoh, H. Enomoto, N. Ishii, Y. Iwata, Takashi Nishimura, Nobuhiro Aizawa, Yoshiyuki Sakai, Naoto Ikeda, Kunihiro Hasegawa, Yukihisa Yuri, Tomoyuki Takashima, H. Iijima, S. Nishiguchi","doi":"10.37532/2041-6792.2019.9(1).147","DOIUrl":null,"url":null,"abstract":"Purpose: Examining the clinical significance of Mac-2-binding protein glycosylation isomer (M2BPGi), which was recently introduced as a novel liver fibrotic biomarker in chronic liver disease patients with unique fibrosis associated glycol chain protein alteration, other than liver fibrotic marker appears to be of importance. We sought to examine the relevance between M2BPGi and the Controlling Nutrition (CONUT) score in hepatitis B and C viruses-related patients (the HBVrelated cohort (Br-cohort, n=249) and the HCV-related cohort (Cr-cohort, n=386)) comparing with other liver fibrotic markers. Patients and Methods: We checked the correlation between the CONUT score and four liver fibrotic markers (M2BPGi, FIB-4 index, hyaluronic acid, and platelet count) in the two cohorts. Receiver operating characteristics (ROC) analyses associated with elevated CONUT score (CONUT score ≥ 1,2,3,4 or 5) were also conducted. Results: The median CONUT score (range) were 1 (0-5) in the Br-cohort and 2 (0-8) in the Crcohort (P<0.0001). In the Br-cohort, advanced fibrosis or more (F3 or F4) was noted in 60 patients (24.1%), while in the Cr-cohort, it was noted in 212 patients (54.9%). In the Br-cohort, the highest correlation coefficient was identified in the FIB-4 index (r=0.436, P<0.0001), followed by M2BPGi (r=0.376, P<0.0001). In the Cr-cohort, the highest correlation coefficient was noted in M2BPGi (r=0.690, P<0.0001), followed by the FIB-4 index (r=0.598, P<0.0001). For the ROC analyses linked to the elevated CONUT score, in the Cr-cohort, M2BPGi yielded the highest AUC in all ROC analyses, whereas in the Br-cohort, such tendencies were not noted. Conclusion: M2BPGi can be a useful marker for predicting nutritional condition as determined by the CONUT score especially in chronic hepatitis C patients.","PeriodicalId":10369,"journal":{"name":"Clinical investigation","volume":"47 1","pages":"21-32"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical investigation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37532/2041-6792.2019.9(1).147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: Examining the clinical significance of Mac-2-binding protein glycosylation isomer (M2BPGi), which was recently introduced as a novel liver fibrotic biomarker in chronic liver disease patients with unique fibrosis associated glycol chain protein alteration, other than liver fibrotic marker appears to be of importance. We sought to examine the relevance between M2BPGi and the Controlling Nutrition (CONUT) score in hepatitis B and C viruses-related patients (the HBVrelated cohort (Br-cohort, n=249) and the HCV-related cohort (Cr-cohort, n=386)) comparing with other liver fibrotic markers. Patients and Methods: We checked the correlation between the CONUT score and four liver fibrotic markers (M2BPGi, FIB-4 index, hyaluronic acid, and platelet count) in the two cohorts. Receiver operating characteristics (ROC) analyses associated with elevated CONUT score (CONUT score ≥ 1,2,3,4 or 5) were also conducted. Results: The median CONUT score (range) were 1 (0-5) in the Br-cohort and 2 (0-8) in the Crcohort (P<0.0001). In the Br-cohort, advanced fibrosis or more (F3 or F4) was noted in 60 patients (24.1%), while in the Cr-cohort, it was noted in 212 patients (54.9%). In the Br-cohort, the highest correlation coefficient was identified in the FIB-4 index (r=0.436, P<0.0001), followed by M2BPGi (r=0.376, P<0.0001). In the Cr-cohort, the highest correlation coefficient was noted in M2BPGi (r=0.690, P<0.0001), followed by the FIB-4 index (r=0.598, P<0.0001). For the ROC analyses linked to the elevated CONUT score, in the Cr-cohort, M2BPGi yielded the highest AUC in all ROC analyses, whereas in the Br-cohort, such tendencies were not noted. Conclusion: M2BPGi can be a useful marker for predicting nutritional condition as determined by the CONUT score especially in chronic hepatitis C patients.