A model to determine absolute risk for esophageal adenocarcinoma

Thrift, Aaron P., Kendall, Bradley J., Pandeya, Nirmala and Whiteman, David C. (2013) A model to determine absolute risk for esophageal adenocarcinoma. Clinical Gastroenterology and Hepatology, 11 2: 138-144. doi:10.1016/j.cgh.2012.10.026


Author Thrift, Aaron P.
Kendall, Bradley J.
Pandeya, Nirmala
Whiteman, David C.
Title A model to determine absolute risk for esophageal adenocarcinoma
Journal name Clinical Gastroenterology and Hepatology   Check publisher's open access policy
ISSN 1542-3565
1542-7714
Publication date 2013-02-01
Year available 2012
Sub-type Article (original research)
DOI 10.1016/j.cgh.2012.10.026
Open Access Status Not yet assessed
Volume 11
Issue 2
Start page 138
End page 144
Total pages 9
Place of publication Maryland Heights, MO, United States
Publisher W.B. Saunders Co.
Language eng
Subject 2715 Gastroenterology
2721 Hepatology
Abstract Background & Aims: Esophageal adenocarcinoma (EAC) develops rapidly and has a high mortality rate. We aimed to develop a prediction model to estimate the absolute 5-year risks, based on different profiles of factors, for developing EAC. Methods: We derived a risk model using epidemiologic data from 364 patients with incident EAC and 1580 population controls. Significant risk factors were fitted into an unconditional multiple logistic regression model. The final model was combined with age- and sex-specific EAC incidence data to estimate absolute 5-year risks for EAC. We performed a 10-fold cross-validation of the data to assess the relative performance of the model. Results: The final risk model included terms for highest level of education, body mass index, smoking status, frequency of gastroesophageal reflux symptoms and/or use of acid-suppressant medications, and frequency of nonsteroidal anti-inflammatory drug use. The population attributable risk for the model was 0.92. A 10-fold cross-validation produced an area under the receiver operating characteristic curve statistic of 0.75 (95% confidence interval, 0.66-0.84), indicating good discrimination. Adding data on alarm symptoms, frequency of symptoms of dysphagia, and unexplained weight loss to the model significantly improved discrimination (area under the receiver operating characteristic curve, 0.85; 95% confidence interval, 0.78-0.91)Conclusions: Risk models can be used to identify people with a higher than average risk for developing EAC; these individuals might benefit from targeted cancer-prevention strategies.
Formatted abstract
Background & Aims: Esophageal adenocarcinoma (EAC) develops rapidly and has a high mortality rate. We aimed to develop a prediction model to estimate the absolute 5-year risks, based on different profiles of factors, for developing EAC.

Methods: We derived a risk model using epidemiologic data from 364 patients with incident EAC and 1580 population controls. Significant risk factors were fitted into an unconditional multiple logistic regression model. The final model was combined with age- and sex-specific EAC incidence data to estimate absolute 5-year risks for EAC. We performed a 10-fold cross-validation of the data to assess the relative performance of the model.

Results: The final risk model included terms for highest level of education, body mass index, smoking status, frequency of gastroesophageal reflux symptoms and/or use of acid-suppressant medications, and frequency of nonsteroidal anti-inflammatory drug use. The population attributable risk for the model was 0.92. A 10-fold cross-validation produced an area under the receiver operating characteristic curve statistic of 0.75 (95% confidence interval, 0.66-0.84), indicating good discrimination. Adding data on alarm symptoms, frequency of symptoms of dysphagia, and unexplained weight loss to the model significantly improved discrimination (area under the receiver operating characteristic curve, 0.85; 95% confidence interval, 0.78-0.91).

Conclusions: Risk models can be used to identify people with a higher than average risk for developing EAC; these individuals might benefit from targeted cancer-prevention strategies.
Keyword Epidemiology
Esophagus
Risk Prediction
Tumor
Q-Index Code C1
Q-Index Status Confirmed Code
Grant ID 199600
08-04
Institutional Status UQ
Additional Notes Available online: 25 October 2012.

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2013 Collection
School of Public Health Publications
School of Medicine Publications
 
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Created: Sat, 05 Jan 2013, 00:40:28 EST by Geraldine Fitzgerald on behalf of School of Public Health