Latent-class analysis was used to evaluate the usefulness of markers of hep
atitis C virus (HCV) infection in characterizing the true, underlying infec
tion in a community-based Japanese population. Antibodies to HCV were detec
ted in 24%, HCV RNA in 22%, and HCV core protein in 19% of stored serum sam
ples from 372 adults. A 2-class model suggested that positive results for a
ny 2 virus markers defined the current HCV infection class, with an estimat
ed prevalence of 22% (95% confidence interval, 18%-26%). The sensitivity fo
r detection of current HCV infection was highest for anti-HCV (97%) and was
more moderate for HCV RNA (91%) and HCV core protein (85%). The specificit
y for each marker was greater than or equal to 96%. In general, the associa
tion between demographic factors and current HCV infection status was stren
gthened by use of latent-class analysis that combined data for markers of H
CV infection, when compared with results of logistic regression analysis fo
r each marker separately.