title: Classification of therapy resistance based on longitudinal biomarker profiles.
abstract: To classify patients either as resistant or non-resistant to HIV therapy based on longitudinal viral load profiles, we applied longitudinal quadratic discriminant analysis and examined various measures, mainly derived from the Brier Score, to assess the biomarker performance in terms of discrimination and calibration. The analysis of the application data revealed an increase in performance by using longer profiles instead of single biomarker measurements. Simulations showed that the selection of mixed models for the estimation of the group-specific discriminant rule parameters should be based on BIC, rather than on the best performance measure. An incorrect model selection can lead to spuriously better or worse performance as misclassification and classification certainty regards, especially with increasing length of the profiles and for more complex models with random slopes.
authors.affiliation: Institute of Statistics, Ludwig-Maximilians University, 80539 Munich, Germany.
authors.forename: Mareike
authors.initials: M
authors.lastname: Kohlmann
authors.forename: Leonhard
authors.initials: L
authors.lastname: Held
authors.forename: Veit Peter
authors.initials: VP
authors.lastname: Grunert
mesh_terms: D019380:Anti-HIV Agents / Q000627:therapeutic use*; D015415:Biomarkers / Q000097:blood*; D016002:Discriminant Analysis; D024882:Drug Resistance, Viral; D015658:HIV Infections / Q000097:blood* / Q000188:drug therapy* / Q000453:epidemiology; D006801:Humans; D008137:Longitudinal Studies; D017063:Outcome Assessment, Health Care / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016896:Treatment Outcome
chemical_list: D019380:Anti-HIV Agents; D015415:Biomarkers