Dynamics of Hepatitis E Virus (HEV) Antibodies and Development of a Multifactorial Model To Improve the Diagnosis of HEV Infection in Resource-Limited Settings.

Abstract

Serological markers are important for the diagnosis of hepatitis E virus (HEV) infection. This study aims to compare the diagnostic performance of the anti-HEV IgM and the HEV antigen (Ag) assays and establish a multifactorial model to improve the diagnosis of current HEV infection when HEV RNA detection is not available. A total of 809 serum samples, including 325 anti-HEV IgM-positive and 484 anti-HEV IgM-negative samples, were tested for HEV RNA. The anti-HEV IgM assay had very high sensitivity (99.4%) but moderate accuracy (79.2%) and specificity (74.3%). By retrospective follow-up of 58 patients with sequential samples (n = 143) tested for anti-HEV antibodies, we found anti-HEV IgM remained positive for more than 10 months in some HEV-infected patients, when HEV RNA was already undetectable; thus, decision solely based on anti-HEV IgM may lead to misdiagnosis. In contrast, the HEV Ag assay had very high specificity (100%). However, the detection efficiency of HEV Ag greatly diminished when the HEV RNA level was low or the anti-HEV IgG level was high. By logistic regression, a model integrating anti-HEV IgM, alanine aminotransferase, and HEV Ag was proposed, and the cutoff value was determined based on the testing results of the 143 sequential samples. The model was further evaluated with 67 randomly selected IgM-positive samples from single-visit patients. Overall, the model outperformed the anti-HEV IgM or the HEV Ag assay in the diagnosis of current HEV infection (sensitivity/specificity/accuracy, 89.5%/95.2%/91.9%). The area under the receiver operating characteristics curve of the model was greater than 0.97.