Cytokeratin 18 can help predict liver fibrosis in HCV infected patients with type 2 diabetes mellitus

Author:

Li Fang,Lei Feifei,Wen Chengcai,Ge Qiu,Zhu Liyao

Abstract

Abstract Background To investigate the predictive values of cytokeratin 18 for liver fibrosis in hepatitis C virus (HCV) infected patients with type 2 diabetes mellitus (T2DM). Methods 252 HCV-infected patients with T2DM between January 2012 and August 2017 were retrospectively reviewed. Pearson/spearman correlation analysis was used to detect the correlation in the entire cohort. Multivariate linear regression was used to identify independent predictors and logistic regression was for establishing models. Combination models that incorporated CK18 and other methods (i.e. transient elastography, aspartate transaminase-to-platelet ratio index (APRI) and fibrosis-4 index (FIB-4)] were developed in a training cohort of 132 patients. Performance of models was evaluated through discrimination ability and clinical benefits. An internal validation was conducted in 120 consecutive patients. Results CK18 was found significantly associated with fibrosis scores (r = 0.452, P < .001). CK18 and albumin were confirmed as independent predictors for fibrosis. For predicting significant fibrosis in the validation cohort, the observed AUC values of APRI + CK18 (AUC 0.83) and FIB-4 + CK18 (AUC 0.84) were higher than those of APRI (AUC 0.61) and FIB-4 (AUC 0.65). For predicting advanced fibrosis and cirrhosis, the AUC values of FIB-4 + CK18 (AUC 0.74 and 0.77, respectively) were significantly higher than those of FIB-4 (AUC 0.61 of both). Decision curve analysis confirmed the more clinical benefits can be provided by being combined with CK18. Conclusions CK18 is an independent predictor of liver fibrosis for HCV-infected patients with T2DM. Noninvasive methods incorporate CK18 and other biomarker indices can have better performance for diagnosing fibrosis and help clinical decision-making.

Publisher

Springer Science and Business Media LLC

Subject

Gastroenterology,General Medicine

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