Development and validation of a nomogram for predicting metachronous peritoneal metastasis in colorectal cancer:A retrospective study

作     者：Bo Ban An Shang Jian Shi 

作者机构：Department of General SurgeryThe Second Hospital of Jilin UniversityChangchun 130041Jilin ProvinceChina 

出 版 物：《World Journal of Gastrointestinal Oncology》 (世界胃肠肿瘤学杂志（英文版）（电子版）)

年 卷 期：2023年第15卷第1期

页      面：112-127页

核心收录：

学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学] 

基　　金：Supported by the Science and Technology Development Project of Jilin Province No.2020SCZT079 

主　　题：Colorectal cancer Metachronous peritoneal metastasis Risk factor Nomogram 

摘      要：BACKGROUND Peritoneal metastasis(PM)after primary surgery for colorectal cancer(CRC)has the worst *** and early detection of metachronous PM(m-PM)have an important role in improving postoperative prognosis of ***,commonly used imaging methods have limited sensitivity to detect PM *** aimed to establish a nomogram model to evaluate the individual probability of m-PM to facilitate early interventions for high-risk *** To establish and validate a nomogram model for predicting the occurrence of m-PM in CRC within 3 years after *** We used the clinical data of 878 patients at the Second Hospital of Jilin University,between January 1,2014 and January 31,*** patients were randomly divided into training and validation cohorts at a ratio of 2:*** least absolute shrinkage and selection operator(LASSO)regression was performed to identify the variables with nonzero coefficients to predict the risk of *** logistic regression was used to verify the selected variables and to develop the predictive nomogram ***’s concordance index,receiver operating characteristic curve,Brier score,and decision curve analysis(DCA)were used to evaluate discrimination,distinctiveness,validity,and clinical utility of this nomogram *** model was verified internally using bootstrapping method and verified externally using validation *** LASSO regression analysis identified six potential risk factors with nonzero *** logistic regression confirmed the risk factors to be *** on the results of two regression analyses,a nomogram model was *** nomogram included six predictors:Tumor site,histological type,pathological T stage,carbohydrate antigen 125,v-raf murine sarcoma viral oncogene homolog B mutation and microsatellite instability *** model achieved good predictive accuracy on both the training and validation *** C-index,area under the curve,and