Prediction of hepatic necroinflammatory activity in patients with chronic hepatitis B by a simple noninvasive model

Background: A model was constructed using clinical and serum variables to discriminate between chronic hepatitis B (CHB) patients with and without significant necroinflammatory activity (score 4-18 vs. score 0-3).

Methods: Consecutive CHB patients who underwent liver biopsy were divided into two sequential groups: a training group (n = 401) and a validation group (n = 401). Multivariate analysis identified alanine aminotransferase, γ-glutamyltransferase, prothrombin time and albumin as independent predictors of necroinflammatory activity.

Results: The area under the receiver operating characteristic curve was 0.826 for the training group and 0.847 for the validation group. Using a cut-off score of H ≤ 0.375, significant necroinflammatory activity (score 4-18) was excluded with high accuracy [78.2% negative predictive value (NPV), 72% positive predictive value (PPV), and 90.8% sensitivity] in 238 (59.4%) of 401 patients in the training group and with the same certainty (88.1% NPV, 61.2% PPV, and 95.1% sensitivity) among 204 (50.9%) of 401 patients in the validation group. Similarly, applying a cut-off score of H > 0.720, significant necroinflammatory activity was correctly identified with high accuracy (90.8% PPV, 57.7% NPV, and 92.0% specificity) in 150 (37.4%) of 401 patients in the training group and with the same certainty (91.8% PPV, 64.6% NPV, and 95.4% specificity) in 188 (46.9%) of 401 patients in the validation group.

Conclusions: A predictive model based on easily accessible variables identified CHB patients with and without significant necroinflammatory activity with a high degree of accuracy. This model may decrease the need for liver biopsy for necroinflammatory activity grading in 72.1% of CHB patients.