Construction and validation of a diagnostic model for colorectal mucinous adenocarcinoma integrating preoperative inflammatory and clinical features
10.7659/j.issn.1005-6947.240245
- VernacularTitle:结合术前炎症指标与临床特征的结直肠黏液腺癌诊断模型的构建与验证
- Author:
Qing FANG
1
;
Shuxiang LI
;
Jinyi YUAN
;
Jie TAN
;
Hongmin LI
;
Yunhua XU
;
Guang FU
;
Qiulin HUANG
;
Shuai XIAO
Author Information
1. 南华大学附属第一医院 胃肠外科,湖南 衡阳 421001;南华大学附属第一医院 检验科,湖南 衡阳 421001
- Publication Type:Journal Article
- Keywords:
Colorectal Neoplasms;
Adenocarcinoma,Mucinous;
Inflammation;
Nomograms
- From:
Chinese Journal of General Surgery
2025;34(10):2119-2128
- CountryChina
- Language:Chinese
-
Abstract:
Background and Aims:Mucinous adenocarcinoma of the colorectum(MAC)is a distinct histologic subtype of colorectal cancer characterized by high malignancy and low diagnostic accuracy of preoperative biopsy,posing challenges for clinical decision-making.Given the critical role of the inflammatory microenvironment in tumor progression,this study aimed to develop and validate a nomogram model integrating preoperative systemic inflammatory indicators and clinical features to improve the preoperative diagnosis of MAC.Methods:Clinical data of 293 patients with colorectal cancer who underwent radical resection between June 2017 and June 2022 at the First Affiliated Hospital of the University of South China were retrospectively analyzed.Based on postoperative pathology,patients were classified into the mucinous adenocarcinoma(MAC)group and the non-specific adenocarcinoma(AC)group.Propensity score matching(PSM,1∶1)was used to balance age,T stage,and N stage.Differences in preoperative inflammatory indices were compared between groups.Univariate and multivariate logistic regression analyses were performed to identify independent predictors of MAC,which were incorporated into a diagnostic nomogram.The model's discrimination,calibration,and clinical utility were evaluated using the area under the receiver operating characteristic curve(AUC),calibration plots,and decision curve analysis(DCA).Results:Among the 293 patients,46 had MAC and 247 had AC,with a preoperative colonoscopic diagnostic rate of 54%for MAC.After PSM(43 pairs),platelet count,platelet lymphocyte ratio(PLR),systemic immune inflammation index(SII),inflammation related prognostic index(IPI),and systemic inflammation score(SIS)were significantly higher in the MAC group,while lymphocyte monocyte ratio(LMR)was lower(all P<0.05).Multivariate analysis identified tumor location,maximum tumor diameter,and preoperative IPI as independent predictors.The AUCs of the nomogram in the training(n=206)and validation(n=87)cohorts were 0.759(95%CI=0.662-0.856)and 0.776(95%CI=0.649-0.903),respectively.Calibration plots showed good agreement between predicted and observed probabilities,and DCA demonstrated satisfactory clinical applicability.Conclusion:A nomogram model integrating tumor location,tumor size,and preoperative IPI was successfully developed and validated for preoperative diagnosis of colorectal MAC.This model provides a practical,quantitative tool with good predictive performance to assist clinicians in individualized treatment planning,particularly for patients ineligible for surgical biopsy.
