|Table of Contents|

Construction and validation of a predictive model for the risk of postoperative abdominal infection in colorectal cancer patients with combined metabolic syndrome

Journal Of Modern Oncology[ISSN:1672-4992/CN:61-1415/R]

Issue:
2024 18
Page:
3494-3501
Research Field:
Publishing date:

Info

Title:
Construction and validation of a predictive model for the risk of postoperative abdominal infection in colorectal cancer patients with combined metabolic syndrome
Author(s):
JIN Jian; LIAO Xin; YANG Qingqiang
Department of General Surgery,Affiliated Hospital of Southwest Medical University,Sichuan Luzhou 646000,China.
Keywords:
metabolic syndrome; colorectal cancer; abdominal infection; predictive modeling
PACS:
R735.3
DOI:
10.3969/j.issn.1672-4992.2024.18.015
Abstract:
Objective:To study the effect of metabolic syndrome (MetS) on postoperative abdominal infections in colorectal cancer (CRC),to establish a model to predict the risk of postoperative abdominal infections in CRC,and to validate the effectiveness of the model.Methods:The clinical data of 354 patients who underwent radical surgery for colorectal cancer were collected from the Department of Gastrointestinal Surgery of our hospital,and the influencing factors of postoperative abdominal infections in CRC patients were explored by using univariate and multivariate analyses to find the independent risk factors to construct the prediction model,to predict the risk by drawing the forest plot model,and to test the prediction performance by internal validation.Results:Among the 354 CRC patients included,a total of 68 cases had combined MetS (19.21%),and the incidence of postoperative abdominal infection was higher in the MetS group compared with the non-MetS group (P＜0.01).One-way Logistic analysis showed that age ≥65 years,combined MetS,preoperative combined intestinal obstruction,tumor differentiation,hyperglycemia,hypertension,and hyperlipidemia had an effect on the occurrence of abdominal infection after colon cancer surgery.Multifactorial Logistic analysis showed that preoperative combined intestinal obstruction ［OR:5.729（2.55~12.871），P＜0.01］,MetS ［OR:5.324（2.825~10.034），P＜0.01］,and hyperglycemia ［OR:2.187（1.204~3.975），P=0.01］ were the independent risk factors for postoperative abdominal infection,and a prediction model was constructed to predict and quantify the risk of postoperative abdominal infection after CRC (C-index was 0.771).Using the ROC curve,the 95%CI was calculated as (0.699~0.842),and the optimal threshold cut-off point of the prediction model was 0.172,the specificity was 0.796,and the sensitivity was 0.636,which showed that the model had a better differentiation,and then by drawing the Calibrate calibration curve,the absolute error of the simulated curve and the actual curve was 0.03,which indicated that the trajectories of the two curves were basically the same.The DCA decision curve shows that the model has good clinical effectiveness and certain clinical value.Conclusion:The prediction model constructed in this study has a good predictive effect on the occurrence of postoperative abdominal infections after CRC,which is a guide and warning for high-risk patients in clinical work.

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四川省教育厅自然科学类重点项目(编号：15ZA0166)
Last Update: 1900-01-01