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Validation of a risk prediction model for Barrett’s esophagus in an Australian population

BACKGROUND: Esophageal adenocarcinoma is a disease that has a high mortality rate, the only known precursor being Barrett’s esophagus (BE). While screening for BE is not cost-effective at the population level, targeted screening might be beneficial. We have developed a risk prediction model to ident...

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Detalles Bibliográficos
Autores principales: Ireland, Colin J, Gordon, Andrea L, Thompson, Sarah K, Watson, David I, Whiteman, David C, Reed, Richard L, Esterman, Adrian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5878665/
https://www.ncbi.nlm.nih.gov/pubmed/29628770
http://dx.doi.org/10.2147/CEG.S158627
Descripción
Sumario:BACKGROUND: Esophageal adenocarcinoma is a disease that has a high mortality rate, the only known precursor being Barrett’s esophagus (BE). While screening for BE is not cost-effective at the population level, targeted screening might be beneficial. We have developed a risk prediction model to identify people with BE, and here we present the external validation of this model. MATERIALS AND METHODS: A cohort study was undertaken to validate a risk prediction model for BE. Individuals with endoscopy and histopathology proven BE completed a questionnaire containing variables previously identified as risk factors for this condition. Their responses were combined with data from a population sample for analysis. Risk scores were derived for each participant. Overall performance of the risk prediction model in terms of calibration and discrimination was assessed. RESULTS: Scores from 95 individuals with BE and 636 individuals from the general population were analyzed. The Brier score was 0.118, suggesting reasonable overall performance. The area under the receiver operating characteristic was 0.83 (95% CI 0.78–0.87). The Hosmer–Lemeshow statistic was p=0.14. Minimizing false positives and false negatives, the model achieved a sensitivity of 74% and a specificity of 73%. CONCLUSION: This study has validated a risk prediction model for BE that has a higher sensitivity than previous models.