Development and validation of a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection after radical colorectal cancer surgery
Objective To develop and validate a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection (POI) after radical colorectal cancer (CRC) surgery.Design Cross-sectional study.Participants This study analysed 866 CRC patients after radical surgery at...
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BMJ Publishing Group
2025-01-01
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| author | He Huang Yanli Wang Chengfei Liu Jingxiang Han Tian Yao Linna Gao Huiyang Gao Yuhao Chen Yinglei Cao Fubin Qiu Kai Jia |
| author_facet | He Huang Yanli Wang Chengfei Liu Jingxiang Han Tian Yao Linna Gao Huiyang Gao Yuhao Chen Yinglei Cao Fubin Qiu Kai Jia |
| author_sort | He Huang |
| collection | DOAJ |
| description | Objective To develop and validate a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection (POI) after radical colorectal cancer (CRC) surgery.Design Cross-sectional study.Participants This study analysed 866 CRC patients after radical surgery at a tertiary hospital in China.Methods Univariable 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 measures POI during hospitalisation.Results Independent 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.Conclusion The nomogram related to inflammatory and nutritional indexes may represent a promising tool for predicting POI after radical surgery in CRC patients. |
| format | Article |
| id | doaj-art-5b22f4ca30c641b3baaa2b5019736ec2 |
| institution | Kabale University |
| issn | 2044-6055 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj-art-5b22f4ca30c641b3baaa2b5019736ec22025-01-09T11:05:11ZengBMJ Publishing GroupBMJ Open2044-60552025-01-0115110.1136/bmjopen-2024-087426Development and validation of a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection after radical colorectal cancer surgeryHe Huang0Yanli Wang1Chengfei Liu2Jingxiang Han3Tian Yao4Linna Gao5Huiyang Gao6Yuhao Chen7Yinglei Cao8Fubin Qiu9Kai Jia10Department of Nutrition and Food Hygiene, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, ChinaDepartment of Nutrition and Food Hygiene, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, ChinaDepartment of Gastrointestinal Surgery, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, ChinaDepartment of Nutrition and Food Hygiene, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, ChinaDepartment of Gastrointestinal Surgery, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, ChinaDepartment of Gastrointestinal Surgery, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, ChinaDepartment of Gastrointestinal Surgery, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, ChinaDepartment of Gastrointestinal Surgery, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, ChinaDepartment of Nutrition and Food Hygiene, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, ChinaDepartment of Nutrition and Food Hygiene, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, ChinaDepartment of Gastrointestinal Surgery, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, ChinaObjective To develop and validate a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection (POI) after radical colorectal cancer (CRC) surgery.Design Cross-sectional study.Participants This study analysed 866 CRC patients after radical surgery at a tertiary hospital in China.Methods Univariable 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 measures POI during hospitalisation.Results Independent 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.Conclusion The nomogram related to inflammatory and nutritional indexes may represent a promising tool for predicting POI after radical surgery in CRC patients.https://bmjopen.bmj.com/content/15/1/e087426.full |
| spellingShingle | He Huang Yanli Wang Chengfei Liu Jingxiang Han Tian Yao Linna Gao Huiyang Gao Yuhao Chen Yinglei Cao Fubin Qiu Kai Jia Development and validation of a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection after radical colorectal cancer surgery BMJ Open |
| title | Development and validation of a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection after radical colorectal cancer surgery |
| title_full | Development and validation of a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection after radical colorectal cancer surgery |
| title_fullStr | Development and validation of a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection after radical colorectal cancer surgery |
| title_full_unstemmed | Development and validation of a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection after radical colorectal cancer surgery |
| title_short | Development and validation of a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection after radical colorectal cancer surgery |
| title_sort | development and validation of a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection after radical colorectal cancer surgery |
| url | https://bmjopen.bmj.com/content/15/1/e087426.full |
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