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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.
Ahmadi, Negar; Mbuagbaw, Lawrence; Hanna, Waël C; Finley, Christian; Agzarian, John; Wen, Chuck K; Coret, Michal; Schieman, Colin; Shargall, Yaron.
Afiliação
  • Ahmadi N; Division of Thoracic Surgery, McMaster University/St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada.
  • Mbuagbaw L; Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada.
  • Hanna WC; Biostatistics Unit, Father Sean O'Sullivan Research Centre, St Joseph's Healthcare Hamilton, Hamilton, ON, Canada.
  • Finley C; Centre for the Development of Best Practices in Health, Yaoundé, Cameroon.
  • Agzarian J; Division of Thoracic Surgery, McMaster University/St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada.
  • Wen CK; Division of Thoracic Surgery, McMaster University/St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada.
  • Coret M; Division of Thoracic Surgery, McMaster University/St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada.
  • Schieman C; Division of Thoracic Surgery, University of British Columbia, Surrey, BC, Canada.
  • Shargall Y; Division of Thoracic Surgery, McMaster University/St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada.
J Thorac Dis ; 12(3): 191-198, 2020 Mar.
Article em En | MEDLINE | ID: mdl-32274084
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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Texto completo: 1 Temas: ECOS / Aspectos_gerais Bases de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Aspecto: Patient_preference Idioma: En Revista: J Thorac Dis Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Canadá

Texto completo: 1 Temas: ECOS / Aspectos_gerais Bases de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Aspecto: Patient_preference Idioma: En Revista: J Thorac Dis Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Canadá