ArticleBMC surgery2023
Development of nomogram for predicting major complications in patients with esophageal cancer in the early postoperative period.
Article in BMC surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Development and internal validation of a prognostic model for esophageal cancer liver metastases using the Surveillance, Epidemiology, and End Results database.Journal of thoracic disease · 2026Article
- Risk factors for postoperative intensive care unit admission after minimally invasive esophagectomy following neoadjuvant chemoimmunotherapy in patients with esophageal squamous cell carcinoma: a retrospective cohort study.Frontiers in oncology · 2026Article
- Nomographic predictive models for complications after minimally invasive esophagectomy: Current status and future perspectives.World journal of gastrointestinal surgery · 2025Review
- Article
- Preoperative prognostic nutritional index as a predictive factor for postoperative pneumonia in esophageal cancer patients undergoing esophagectomy.Frontiers in nutrition · 2025Article
- Utilizing machine learning approaches to investigate the relationship between cystatin C and serious complications in esophageal cancer patients after esophagectomy.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024Observational
- Development and validation of a machine learning model for predicting stroke-associated pneumonia in older patients with acute ischemic stroke.Frontiers in neurologyArticle
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo investigate the predictive value of the Prognostic Nutrition Index (PNI) in major complications after esophagectomy for esophageal cancer and to develop a Nomogram risk prediction model.
methodThe clinical data of 386 patients who underwent radical esophageal cancer surgery from May 2019 to March 2022 were retrospectively analyzed. Logistic regression analysis was performed to screen independent risk factors associated with major postoperative complications. A nomogram risk prediction model for major postoperative complications was developed based on the predictors, and the clinical utility of the model was assessed by decision curve analysis(DCA).
resultIn this study logistic univariate regression analysis found that age, preoperative radiotherapy, American Society of Anesthesiologists physical status (ASA score), length of surgery, and PNI may be associated with the development of major postoperative complications. logistic multifactorial analysis showed that the above risk factors were independent risk factors for the development of major postoperative complications in esophageal cancer. Nomogram was developed by incorporating the above risk factors with ASA classification. The calibration curves showed that the model had a good agreement. The decision curves showed that the model has good clinical application.
conclusionIndividualized nomograms based on PNI combined with clinical indicators can be used to predict major complications in the early postoperative period and help to enhance perioperative management.
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