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Bayesian Estimation of Performance Measures of Cervical Cancer Screening Tests in the Presence of Covariates and Absence of a Gold Standard

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Autor(es):
Martinez, Edson Zangiacomi ; Louzada-Neto, Francisco ; Derchain, Sophie Francoise Mauricette ; Achar, Jorge Alberto ; Gontijo, Renato Clementino ; Sarian, Luis Otavio Zanatta ; Syrjanen, Kari Juhani
Número total de Autores: 7
Tipo de documento: Artigo Científico
Fonte: CANCER INFORMATICS; v. 6, p. 14-pg., 2008-01-01.
Resumo

In this paper we develop a Bayesian analysis to estimate the disease prevalence, the sensitivity and specificity of three cervical cancer screening tests (cervical cytology, visual inspection with acetic acid and Hybrid Capture II) in the presence of a covariate and in the absence of a gold standard. We use Metropolis-Hastings algorithm to obtain the posterior summaries of interest. The estimated prevalence of cervical lesions was 6.4% (a 95% credible interval [ 95% CI] was 3.9, 9.3). The sensitivity of cervical cytology (with a result of >= ASC-US) was 53.6% (95% CI: 42.1, 65.0) compared with 52.9% (95% CI: 43.5, 62.5) for visual inspection with acetic acid and 90.3% (95% CI: 76.2, 98.7) for Hybrid Capture II (with result of > 1 relative light units). The specifi city of cervical cytology was 97.0% (95% CI: 95.5, 98.4) and the specifi cities for visual inspection with acetic acid and Hybrid Capture II were 93.0% (95% CI: 91.0, 94.7) and 88.7% (95% CI: 85.9, 91.4), respectively. The Bayesian model with covariates suggests that the sensitivity and the specifi city of the visual inspection with acetic acid tend to increase as the age of the women increases. The Bayesian method proposed here is an useful alternative to estimate measures of performance of diagnostic tests in the presence of covariates and when a gold standard is not available. An advantage of the method is the fact that the number of parameters to be estimated is not limited by the number of observations, as it happens with several frequentist approaches. However, it is important to point out that the Bayesian analysis requires informative priors in order for the parameters to be identifiable. The method can be easily extended for the analysis of other medical data sets. (AU)

Processo FAPESP: 99/11264-0 - Tabagismo e infecção pelo HPV nas lesões precursoras do câncer cervical
Beneficiário:Sophie Françoise Mauricette Derchain
Modalidade de apoio: Auxílio à Pesquisa - Regular