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Accuracy of the END-PAC Model in Predicting the Risk of Developing Pancreatic Cancer in Patients with New-Onset Diabetes: A Systematic Review and Meta-Analysis

Objectives: To investigate the performance of the END-PAC model in predicting pancreatic cancer risk in individuals with new-onset diabetes (NOD). Methods: The PRISMA statement standards were followed to conduct a systematic review. All studies investigating the performance of the END-PAC model in p...

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Autores principales: Hajibandeh, Shahab, Intrator, Christina, Carrington-Windo, Eliot, James, Rhodri, Hughes, Ioan, Hajibandeh, Shahin, Satyadas, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10669673/
https://www.ncbi.nlm.nih.gov/pubmed/38002040
http://dx.doi.org/10.3390/biomedicines11113040
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author Hajibandeh, Shahab
Intrator, Christina
Carrington-Windo, Eliot
James, Rhodri
Hughes, Ioan
Hajibandeh, Shahin
Satyadas, Thomas
author_facet Hajibandeh, Shahab
Intrator, Christina
Carrington-Windo, Eliot
James, Rhodri
Hughes, Ioan
Hajibandeh, Shahin
Satyadas, Thomas
author_sort Hajibandeh, Shahab
collection PubMed
description Objectives: To investigate the performance of the END-PAC model in predicting pancreatic cancer risk in individuals with new-onset diabetes (NOD). Methods: The PRISMA statement standards were followed to conduct a systematic review. All studies investigating the performance of the END-PAC model in predicting pancreatic cancer risk in individuals with NOD were included. Two-by-two tables, coupled forest plots and summary receiver operating characteristic plots were constructed using the number of true positives, false negatives, true negatives and false positives. Diagnostic random effects models were used to estimate summary sensitivity and specificity points. Results: A total of 26,752 individuals from four studies were included. The median follow-up was 3 years and the pooled risk of pancreatic cancer was 0.8% (95% CI 0.6–1.0%). END-PAC score ≥ 3, which classifies the patients as high risk, was associated with better predictive performance (sensitivity: 55.8% (43.9–67%); specificity: 82.0% (76.4–86.5%)) in comparison with END-PAC score 1–2 (sensitivity: 22.2% (16.6–29.2%); specificity: 69.9% (67.3–72.4%)) and END-PAC score < 1 (sensitivity: 18.0% (12.8–24.6%); specificity: 50.9% (48.6–53.2%)) which classify the patients as intermediate and low risk, respectively. The evidence quality was judged to be moderate to high. Conclusions: END-PAC is a promising model for predicting pancreatic cancer risk in individuals with NOD. The score ≥3 should be considered as optimum cut-off value. More studies are needed to assess whether it could improve early pancreatic cancer detection rate, pancreatic cancer re-section rate, and pancreatic cancer treatment outcomes.
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spelling pubmed-106696732023-11-14 Accuracy of the END-PAC Model in Predicting the Risk of Developing Pancreatic Cancer in Patients with New-Onset Diabetes: A Systematic Review and Meta-Analysis Hajibandeh, Shahab Intrator, Christina Carrington-Windo, Eliot James, Rhodri Hughes, Ioan Hajibandeh, Shahin Satyadas, Thomas Biomedicines Systematic Review Objectives: To investigate the performance of the END-PAC model in predicting pancreatic cancer risk in individuals with new-onset diabetes (NOD). Methods: The PRISMA statement standards were followed to conduct a systematic review. All studies investigating the performance of the END-PAC model in predicting pancreatic cancer risk in individuals with NOD were included. Two-by-two tables, coupled forest plots and summary receiver operating characteristic plots were constructed using the number of true positives, false negatives, true negatives and false positives. Diagnostic random effects models were used to estimate summary sensitivity and specificity points. Results: A total of 26,752 individuals from four studies were included. The median follow-up was 3 years and the pooled risk of pancreatic cancer was 0.8% (95% CI 0.6–1.0%). END-PAC score ≥ 3, which classifies the patients as high risk, was associated with better predictive performance (sensitivity: 55.8% (43.9–67%); specificity: 82.0% (76.4–86.5%)) in comparison with END-PAC score 1–2 (sensitivity: 22.2% (16.6–29.2%); specificity: 69.9% (67.3–72.4%)) and END-PAC score < 1 (sensitivity: 18.0% (12.8–24.6%); specificity: 50.9% (48.6–53.2%)) which classify the patients as intermediate and low risk, respectively. The evidence quality was judged to be moderate to high. Conclusions: END-PAC is a promising model for predicting pancreatic cancer risk in individuals with NOD. The score ≥3 should be considered as optimum cut-off value. More studies are needed to assess whether it could improve early pancreatic cancer detection rate, pancreatic cancer re-section rate, and pancreatic cancer treatment outcomes. MDPI 2023-11-14 /pmc/articles/PMC10669673/ /pubmed/38002040 http://dx.doi.org/10.3390/biomedicines11113040 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Systematic Review
Hajibandeh, Shahab
Intrator, Christina
Carrington-Windo, Eliot
James, Rhodri
Hughes, Ioan
Hajibandeh, Shahin
Satyadas, Thomas
Accuracy of the END-PAC Model in Predicting the Risk of Developing Pancreatic Cancer in Patients with New-Onset Diabetes: A Systematic Review and Meta-Analysis
title Accuracy of the END-PAC Model in Predicting the Risk of Developing Pancreatic Cancer in Patients with New-Onset Diabetes: A Systematic Review and Meta-Analysis
title_full Accuracy of the END-PAC Model in Predicting the Risk of Developing Pancreatic Cancer in Patients with New-Onset Diabetes: A Systematic Review and Meta-Analysis
title_fullStr Accuracy of the END-PAC Model in Predicting the Risk of Developing Pancreatic Cancer in Patients with New-Onset Diabetes: A Systematic Review and Meta-Analysis
title_full_unstemmed Accuracy of the END-PAC Model in Predicting the Risk of Developing Pancreatic Cancer in Patients with New-Onset Diabetes: A Systematic Review and Meta-Analysis
title_short Accuracy of the END-PAC Model in Predicting the Risk of Developing Pancreatic Cancer in Patients with New-Onset Diabetes: A Systematic Review and Meta-Analysis
title_sort accuracy of the end-pac model in predicting the risk of developing pancreatic cancer in patients with new-onset diabetes: a systematic review and meta-analysis
topic Systematic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10669673/
https://www.ncbi.nlm.nih.gov/pubmed/38002040
http://dx.doi.org/10.3390/biomedicines11113040
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