ArticleBMJ open2025
Development and validation of a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection after radical colorectal cancer surgery.
Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07321262 (An Interpretable and Clinically Deployable Machine Learning Model for Predicting Early Postoperative Pneumonia of Brain Tumor), which is not on this map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
An Interpretable and Clinically Deployable Machine Learning Model for Predicting Early Postoperative Pneumonia of Brain Tumor: a Multicenter Diagnostic Study
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Preoperative inflammatory and immune-nutritional markers and postoperative pulmonary complications after gastric and colorectal cancer surgery: a systematic review and narrative synthesis.Frontiers in surgery · 2026Pooled it
- Immunologically-based nutritional status assessment amongst preoperative colorectal cancer patients - does it link to TNM stage.Frontiers in immunology · 2026Article
- Early risk stratification of postoperative pneumonia after brain tumor surgery using routine perioperative variables: development and prospective multicenter validation of an interpretable prediction model.Frontiers in cellular and infection microbiology · 2026Article
- Development and validation of a hypoglycemia risk prediction model for hospitalized type 2 diabetes patients following laparoscopic colorectal cancer resection: a retrospective cohort study.Frontiers in endocrinology · 2026Article
- A prediction model based on nutritional variables of postoperative pulmonary infection after colorectal cancer surgery.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo develop and validate a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection (POI) after radical colorectal cancer (CRC) surgery.
designCross-sectional study.
participantsThis study analysed 866 CRC patients after radical surgery at a tertiary hospital in China.
methodsUnivariable and multivariable logistic regression (LR) analyses were used to explore influence factors of POI. Predictive models were constructed using LR, random forest, support vector machine, K-nearest neighbours, naive Bayes and XGBoost. The LR model was used to generate a nomogram for POI prediction. The discrimination and calibration of the nomogram were assessed using receiver operating characteristic (ROC) curves and calibration curves. The contributions of inflammatory and nutritional indexes to the nomogram were evaluated through Net Reclassification Improvement and integrated discrimination improvement, while clinical practicability was assessed using decision curve analysis.
main outcome measuresPOI during hospitalisation.
resultsIndependent factors identified from multivariable LR for prediction POI included age, respiratory disease, Systemic Inflammation Response Index, albumin-to-globulin ratio, operative method and operative duration. The LR model demonstrated the best performance, with an area under the ROC curve of 0.773 (95% CI: 0.674 to 0.872). The nomogram has good differentiation ability, calibration and net benefit. Incorporating inflammatory and nutritional indexes into the nomogram enhanced predictive value compared with models excluding either factor.
conclusionThe nomogram related to inflammatory and nutritional indexes may represent a promising tool for predicting POI after radical surgery in CRC patients.
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