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Modeling the risk of esophageal squamous cell carcinoma and squamous dysplasia in a high risk area in Iran

Etemadi, A. and Abnet, C.C. and Golozar, A. and Malekzadeh, R. and Dawsey, S.M. (2012) Modeling the risk of esophageal squamous cell carcinoma and squamous dysplasia in a high risk area in Iran. Archives of Iranian Medicine, 15 (1). pp. 18-21. ISSN 10292977

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Background: Identifying people at higher risk of having squamous dysplasia, the precursor lesion for esophageal squamous cell carcinoma (ESCC), would allow targeted endoscopic screening. Methods: We used multivariate logistic regression models to predict ESCC and dysplasia as outcomes. The ESCC model was based on data from the Golestan Case-Control Study (total n = 871; cases = 300), and the dysplasia model was based on data from a cohort of subjects from a gastroenterology clinic in Northeast Iran (total n = 724; cases = 26). In each of these analyses, we fit a model including all risk factors known in this region to be associated with ESCC. Individual risks were calculated using the linear combination of estimated regression coefficients and individual-specific values for covariates. We used cross-validation to determine the area under the curve (AUC) and to find the optimal cut points for each of the models. Results: The model had an area under the curve of 0.77 (95 CI: 0.74-0.80) to predict ESCC with 74 sensitivity and 70.4 specificity for the optimum cut point. The area under the curve was 0.71 (95 CI: 0.64-0.79) for dysplasia diagnosis, and the classification table optimized at 61.5 sensitivity and 69.5 specificity. In this population, the positive and negative predictive values for diagnosis of dysplasia were 6.8 and 97.8, respectively. Conclusion: Our models were able to discriminate between ESCC cases and controls in about 77, and between individuals with and without squamous dysplasia in about 70 of the cases. Using risk factors to predict individual risk of ESCC or squamous dysplasia still has limited application in clinical practice, but such models may be suitable for selecting high risk individuals in research studies, or increasing the pretest probability for other screening strategies.

Item Type: Article
Additional Information: cited By 6
Uncontrolled Keywords: article; cancer risk; controlled study; disease association; disease classification; dysplasia; esophageal squamous cell carcinoma; high risk population; human; Iran; linear system; major clinical study; multivariate analysis; outcome assessment; predictive value; process optimization; receiver operating characteristic; regression analysis; risk assessment; risk factor; sensitivity and specificity; statistical model, Area Under Curve; Carcinoma, Squamous Cell; Esophageal Neoplasms; Humans; Iran; Logistic Models; Models, Statistical; Risk Assessment; Risk Factors; ROC Curve; Sensitivity and Specificity
Subjects: کهورت
مقالات نمایه شده محققین دانشگاه در سایت ,Web of Science ,Scopus
موارد کلی
Divisions: معاونت تحقیقات و فناوری
Depositing User: GOUMS
Date Deposited: 20 Apr 2015 06:02
Last Modified: 16 Apr 2018 09:09
URI: http://eprints.goums.ac.ir/id/eprint/2559

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