Development and validation of a nomogram for predicting anastomotic leakage after esophagectomy: integrating baseline characteristics and early postoperative biomarkers
Year: 2026
Type: article
Abstract: Background: Anastomotic leakage (AL) is a devastating complication following esophagectomy. Current predictive models relying solely on static preoperative factors fail to capture the evolving postoperative physiological stressors. This study aimed to develop and validate a multidimensional nomogram integrating baseline vulnerability with early dynamic biomarkers to predict AL. Methods: A retrospective cohort of 298 esophageal cancer patients who underwent esophagectomy between January 2020 and December 2025 was analyzed. Independent risk factors were identified using multivariate logistic regression. A predictive nomogram was constructed, evaluated using the area under the curve (AUC), internally validated via 1,000 bootstrap resamplings, and assessed for clinical utility using decision curve analysis (DCA). Results: AL occurred in 38 patients (12.8%). Multivariate analysis identified five independent predictors: body mass index (BMI), chronic obstructive pulmonary disease (COPD), anastomosis site, postoperative day (POD) 2 serum lactate, and POD 3 neutrophil-to-lymphocyte ratio (NLR). The nomogram demonstrated excellent discrimination with an AUC of 0.873 and a bootstrap-corrected AUC of 0.859. Furthermore, DCA confirmed that the model provided superior clinical net benefit across a wide range of threshold probabilities. Notably, preexisting COPD and postoperative pulmonary complications (PPCs) drove AL incidence. The model accurately identified high-risk patients by POD 3, well before the median clinical AL diagnosis on POD 8. Conclusions: Integrating static baseline factors with dynamic physiological feedback yields a highly accurate AL prediction tool. However, this model is currently only internally validated. By stratifying risk as early as POD 3, this nomogram provides a critical 5-day window for targeted interventions, though its broader clinical implementation strictly requires confirmation in independent cohorts.
Source: Journal of Thoracic Disease
Authors: Zhongjian Chong, Le Zhou, Zijian Ma, Aiping Zhang
Institutions: Nanjing First Hospital, Nanjing Medical University
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7223282691