Use of Individual-level Covariates to Improve Latent Class Analysis of Trypanosoma cruzi Diagnostic Tests

Aaron W. Tustin 1 , Dylan S. Small 2 , Stephen Delgado 3 , Ricardo Castillo Neyra 4 , Manuela R. Verastegui 5 , Jenny M. Ancca Juárez 6 , Víctor R. Quispe Machaca 7 , Robert H. Gilman 8 , Caryn Bern 9  and Michael Z. Levy 10
  • 1 Vanderbilt University School of Medicine
  • 2 University of Pennsylvania
  • 3 University of Arizona
  • 4 Johns Hopkins University
  • 5 Universidad Peruana Cayetano Heredia, Lima, Peru
  • 6 Universidad Peruana Cayetano Heredia, Lima, Peru
  • 7 Universidad Peruana Cayetano Heredia, Lima, Peru
  • 8 Johns Hopkins University
  • 9 Centers for Disease Control and Prevention
  • 10 University of Pennsylvania Perelman School of Medicine

Abstract

Statistical methods such as latent class analysis can estimate the sensitivity and specificity of diagnostic tests when no perfect reference test exists. Traditional latent class methods assume a constant disease prevalence in one or more tested populations. When the risk of disease varies in a known way, these models fail to take advantage of additional information that can be obtained by measuring risk factors at the level of the individual. We show that by incorporating complex field-based epidemiologic data, in which the disease prevalence varies as a continuous function of individual-level covariates, our model produces more accurate sensitivity and specificity estimates than previous methods. We apply this technique to several simulated populations and to actual Chagas disease test data from a community near Arequipa, Peru. Results from our model estimate that the first-line enzyme-linked immunosorbent assay has a sensitivity of 78% (95% CI: 62-100%) and a specificity of 100% (95% CI: 99-100%). The confirmatory immunofluorescence assay is estimated to be 73% sensitive (95% CI: 65-81%) and 99% specific (95% CI: 96-100%).

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Epidemiologic Methods is devoted entirely to methodology in the field of epidemiology. The journal aims to bring novel methodology more quickly to the epidemiologic community and to provide a forum for longer or more technical papers on epidemiologic methods. It serves as a repository of methodologic contributions focused on advancing and improving epidemiologic analysis.

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