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Development of a clinical score to distinguish malignant from benign esophageal disease in an undiagnosed patient population referred to an esophageal diagnostic assessment program

BACKGROUND: Esophageal cancer is associated with poor prognosis. Diagnosis is often delayed, resulting in presentation with advanced disease. We developed a clinical score to predict the risk of a malignant diagnosis in symptomatic patients prior to any diagnostic tests. METHODS: We analyzed data fr...

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Autores principales: Ahmadi, Negar, Mbuagbaw, Lawrence, Hanna, Waël C., Finley, Christian, Agzarian, John, Wen, Chuck K., Coret, Michal, Schieman, Colin, Shargall, Yaron
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7139012/
https://www.ncbi.nlm.nih.gov/pubmed/32274084
http://dx.doi.org/10.21037/jtd.2020.02.07
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author Ahmadi, Negar
Mbuagbaw, Lawrence
Hanna, Waël C.
Finley, Christian
Agzarian, John
Wen, Chuck K.
Coret, Michal
Schieman, Colin
Shargall, Yaron
author_facet Ahmadi, Negar
Mbuagbaw, Lawrence
Hanna, Waël C.
Finley, Christian
Agzarian, John
Wen, Chuck K.
Coret, Michal
Schieman, Colin
Shargall, Yaron
author_sort Ahmadi, Negar
collection PubMed
description BACKGROUND: Esophageal cancer is associated with poor prognosis. Diagnosis is often delayed, resulting in presentation with advanced disease. We developed a clinical score to predict the risk of a malignant diagnosis in symptomatic patients prior to any diagnostic tests. METHODS: We analyzed data from patients referred to a regional esophageal diagnostic assessment program between May 2013 and August 2016. Logistic regression was performed to identify predictors of malignancy based on patient characteristics and symptoms. Predicted probabilities were used to develop a score from 0 to 10 which was weighted according to beta coefficients for predictors in the model. Score accuracy was evaluated using a receiver operating characteristic (ROC) curve and internally validated using bootstrapping techniques. Patients were classified into low (0–2 points), medium (3–6 points), and high (7–10 points) risk groups based on their scores. Pathologic tissue diagnosis was used to assess the effectiveness of the developed score in predicting the risk of malignancy in each group. RESULTS: Of 530 patients, 363 (68%) were diagnosed with malignancy. Factors predictive of malignancy included male sex, family history of cancer and esophageal cancer, fatigue, chest/throat/back pain, melena and weight loss. These factors were allocated 1–2 points each for a total of 10 points. Low-risk patients had 70% lower chance of malignancy (RR =0.28, 95% CI: 0.21–0.38), medium-risk had 50% higher chance of malignancy (RR =1.5, 95% CI: 1.26–1.77), and high-risk patients were 8 times more likely to be diagnosed with malignancy (RR =8.2, 95% CI: 2.60–25.86). The area under the ROC curve for malignancy was 0.82 (95% CI: 0.77–0.87). CONCLUSIONS: A simple score using patient characteristics and symptoms reliably distinguished malignant from benign diagnoses in a population of patients with upper gastrointestinal symptoms. This score might be useful in expediting investigations, referrals and eventual diagnosis of malignancy.
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spelling pubmed-71390122020-04-09 Development of a clinical score to distinguish malignant from benign esophageal disease in an undiagnosed patient population referred to an esophageal diagnostic assessment program Ahmadi, Negar Mbuagbaw, Lawrence Hanna, Waël C. Finley, Christian Agzarian, John Wen, Chuck K. Coret, Michal Schieman, Colin Shargall, Yaron J Thorac Dis Original Article BACKGROUND: Esophageal cancer is associated with poor prognosis. Diagnosis is often delayed, resulting in presentation with advanced disease. We developed a clinical score to predict the risk of a malignant diagnosis in symptomatic patients prior to any diagnostic tests. METHODS: We analyzed data from patients referred to a regional esophageal diagnostic assessment program between May 2013 and August 2016. Logistic regression was performed to identify predictors of malignancy based on patient characteristics and symptoms. Predicted probabilities were used to develop a score from 0 to 10 which was weighted according to beta coefficients for predictors in the model. Score accuracy was evaluated using a receiver operating characteristic (ROC) curve and internally validated using bootstrapping techniques. Patients were classified into low (0–2 points), medium (3–6 points), and high (7–10 points) risk groups based on their scores. Pathologic tissue diagnosis was used to assess the effectiveness of the developed score in predicting the risk of malignancy in each group. RESULTS: Of 530 patients, 363 (68%) were diagnosed with malignancy. Factors predictive of malignancy included male sex, family history of cancer and esophageal cancer, fatigue, chest/throat/back pain, melena and weight loss. These factors were allocated 1–2 points each for a total of 10 points. Low-risk patients had 70% lower chance of malignancy (RR =0.28, 95% CI: 0.21–0.38), medium-risk had 50% higher chance of malignancy (RR =1.5, 95% CI: 1.26–1.77), and high-risk patients were 8 times more likely to be diagnosed with malignancy (RR =8.2, 95% CI: 2.60–25.86). The area under the ROC curve for malignancy was 0.82 (95% CI: 0.77–0.87). CONCLUSIONS: A simple score using patient characteristics and symptoms reliably distinguished malignant from benign diagnoses in a population of patients with upper gastrointestinal symptoms. This score might be useful in expediting investigations, referrals and eventual diagnosis of malignancy. AME Publishing Company 2020-03 /pmc/articles/PMC7139012/ /pubmed/32274084 http://dx.doi.org/10.21037/jtd.2020.02.07 Text en 2020 Journal of Thoracic Disease. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Ahmadi, Negar
Mbuagbaw, Lawrence
Hanna, Waël C.
Finley, Christian
Agzarian, John
Wen, Chuck K.
Coret, Michal
Schieman, Colin
Shargall, Yaron
Development of a clinical score to distinguish malignant from benign esophageal disease in an undiagnosed patient population referred to an esophageal diagnostic assessment program
title Development of a clinical score to distinguish malignant from benign esophageal disease in an undiagnosed patient population referred to an esophageal diagnostic assessment program
title_full Development of a clinical score to distinguish malignant from benign esophageal disease in an undiagnosed patient population referred to an esophageal diagnostic assessment program
title_fullStr Development of a clinical score to distinguish malignant from benign esophageal disease in an undiagnosed patient population referred to an esophageal diagnostic assessment program
title_full_unstemmed Development of a clinical score to distinguish malignant from benign esophageal disease in an undiagnosed patient population referred to an esophageal diagnostic assessment program
title_short Development of a clinical score to distinguish malignant from benign esophageal disease in an undiagnosed patient population referred to an esophageal diagnostic assessment program
title_sort development of a clinical score to distinguish malignant from benign esophageal disease in an undiagnosed patient population referred to an esophageal diagnostic assessment program
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7139012/
https://www.ncbi.nlm.nih.gov/pubmed/32274084
http://dx.doi.org/10.21037/jtd.2020.02.07
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