We used Bayesian latent-class models to generate receiver operating characteristic curves and to revise the cutoff values for an enzyme-linked immunosorbent assay that has been developed previously for melioidosis. The new cutoff was unbiased towards misclassification caused by an imperfect gold standard and resulted in an increase in both sensitivity (from 66.4% to 80.2%) and specificity (82.1% and 95.0%).