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Published on: June 18, 2020
A novel index using routine clinical parameters for predicting significant liver inflammation in chronic hepatitis B
1Department of Infectious Diseases, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China.
Abstract:
Identifying the degree of liver inflammation is critical for therapeutic judgement of patients with chronic hepatitis B (CHB). However, we lack indexes which can accurately predict significant liver inflammation in patients with CHB. This study aimed to develop a simple predictive index for liver inflammation in CHB using routine clinical parameters. A total of 519 patients with CHB who underwent liver biopsy were enrolled and randomly divided into training (n = 346) and validation cohorts (n = 173). Based on routine clinical parameters, gamma-glutamyl transpeptidase (GGT; P = 0.031) and platelets (PLT; P < 0.001) were identified as independent predictors of significant inflammation by multivariable analysis in the training cohort. Accordingly, the GGT to PLT ratio (GPR) was developed to amplify the opposing effects for predicting liver inflammation. In the training cohort, the AUCs of GPR in predicting significant inflammation were 0.791 (95% CI: 0.742-0.839), 0.783 (95% CI: 0.717-0.849) and 0.791 (95% CI: 0.716-0.867) in the entire patients with CHB, HBeAg-positive CHB patients and HBeAg-negative CHB patients, respectively. The diagnostic performance of GPR for significant inflammation was significantly superior to that of alanine aminotransferase (ALT), aspartate transaminase (AST) and GGT in all patients with CHB and HBeAg-positive CHB patients, but was comparable with ALT, AST and GGT in HBeAg-negative CHB patients. In the validation cohort, the diagnostic performance of GPR in assessing significant liver inflammation was also superior to other indexes in all patients with CHB and HBeAg-positive CHB patients, but was comparable with GGT in HBeAg-negative CHB patients. Thus, GPR can be a novel and simple index for predicting significant liver inflammation in CHB, especially for HBeAg-positive CHB.
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However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

