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

Arash Etemadi, Christian C. Abnet, Asieh Golozar, Reza Malekzadeh, Sanford M. Dawsey

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Pages (from-to)18-21
Number of pages4
JournalArchives of Iranian Medicine
Volume15
Issue number1
StatePublished - Jan 2012
Externally publishedYes

Fingerprint

Iran
Area Under Curve
Logistic Models
Sensitivity and Specificity
Gastroenterology
Esophageal Squamous Cell Carcinoma
Case-Control Studies
Research
Population

Keywords

  • Esophagus
  • Risk modeling
  • Squamous cell carcinoma
  • Squamous dysplasia

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Etemadi, A., Abnet, C. C., Golozar, A., Malekzadeh, R., & 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), 18-21.

Modeling the risk of esophageal squamous cell carcinoma and squamous dysplasia in a high risk area in Iran. / Etemadi, Arash; Abnet, Christian C.; Golozar, Asieh; Malekzadeh, Reza; Dawsey, Sanford M.

In: Archives of Iranian Medicine, Vol. 15, No. 1, 01.2012, p. 18-21.

Research output: Contribution to journalArticle

Etemadi, A, Abnet, CC, Golozar, A, Malekzadeh, R & Dawsey, SM 2012, 'Modeling the risk of esophageal squamous cell carcinoma and squamous dysplasia in a high risk area in Iran', Archives of Iranian Medicine, vol. 15, no. 1, pp. 18-21.
Etemadi, Arash ; Abnet, Christian C. ; Golozar, Asieh ; Malekzadeh, Reza ; Dawsey, Sanford M. / Modeling the risk of esophageal squamous cell carcinoma and squamous dysplasia in a high risk area in Iran. In: Archives of Iranian Medicine. 2012 ; Vol. 15, No. 1. pp. 18-21.
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AB - 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.

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