Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.] · 2026
Re-evaluating routinely collected clinical and laboratory parameters in the preoperative risk assessment of intraductal papillary mucinous neoplasms: model development and internal validation.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод в очереди
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Hidalgo Salinas Camila, Grewal Mahip, Jayaprakash Vishnu, Habib Joseph R, Hewitt D Brock, Kaplan Brian J, Morgan Katherine A, Gonda Tamas A, Wolfgang Christopher L, Perera Rafael, Sacks Greg D, Javed Ammar A
Аннотация
BACKGROUND: Accurate preoperative malignancy risk assessment in intraductal papillary mucinous neoplasm (IPMN) is essential to balance timely intervention for high-grade dysplasia or invasive cancer (HGD/IC) against avoiding unnecessary or premature surgery in low-grade IPMN. This study aimed to externally validate the 2023 International Association of Pancreatology (IAP)/Kyoto guidelines and develop a combined prediction model incorporating routinely collected clinical data and laboratory parameters.
METHODS: We conducted a retrospective cohort study of 194 patients who underwent resection for IPMN between 2012 and 2024. We evaluated the predictive performance of the current IAP/Kyoto criteria ("Kyoto model"), developed a clinical model using routinely available laboratory and clinical variables, and integrated both into a combined model. Model performance was assessed using discrimination and calibration metrics, with internal validation via bootstrapping and five-fold cross-validation.
RESULTS: The Kyoto model demonstrated modest discrimination (AUC 0.62). The clinical model, incorporating neutrophil-to-lymphocyte ratio (NLR), smoking history, blood glucose, CA19-9, and alkaline phosphatase, achieved an optimism-corrected AUC of 0.76. Compared to the Kyoto model, the combined model (AUC 0.77) significantly improved discrimination and calibration (p < 0.001). At a predicted probability threshold of >0.75, the combined model achieved a 90% specificity and 91% positive predictive value for HGD/IC, identifying a high-risk subgroup suitable for surgical intervention.
CONCLUSIONS: Integrating routinely collected clinical and laboratory parameters with guideline-based imaging features shows promise to enhance preoperative identification of high-risk IPMN in patients already being considered for surgical resection. The combined model offers a practical, high-specificity tool to support surgical decision-making in this selected population, though its performance metrics should not be extrapolated to unselected surveillance cohorts. External validation is required before broader clinical implementation.
METHODS: We conducted a retrospective cohort study of 194 patients who underwent resection for IPMN between 2012 and 2024. We evaluated the predictive performance of the current IAP/Kyoto criteria ("Kyoto model"), developed a clinical model using routinely available laboratory and clinical variables, and integrated both into a combined model. Model performance was assessed using discrimination and calibration metrics, with internal validation via bootstrapping and five-fold cross-validation.
RESULTS: The Kyoto model demonstrated modest discrimination (AUC 0.62). The clinical model, incorporating neutrophil-to-lymphocyte ratio (NLR), smoking history, blood glucose, CA19-9, and alkaline phosphatase, achieved an optimism-corrected AUC of 0.76. Compared to the Kyoto model, the combined model (AUC 0.77) significantly improved discrimination and calibration (p < 0.001). At a predicted probability threshold of >0.75, the combined model achieved a 90% specificity and 91% positive predictive value for HGD/IC, identifying a high-risk subgroup suitable for surgical intervention.
CONCLUSIONS: Integrating routinely collected clinical and laboratory parameters with guideline-based imaging features shows promise to enhance preoperative identification of high-risk IPMN in patients already being considered for surgical resection. The combined model offers a practical, high-specificity tool to support surgical decision-making in this selected population, though its performance metrics should not be extrapolated to unselected surveillance cohorts. External validation is required before broader clinical implementation.