Retrospective Study
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Jan 15, 2023; 15(1): 112-127
Published online Jan 15, 2023. doi: 10.4251/wjgo.v15.i1.112
Development and validation of a nomogram for predicting metachronous peritoneal metastasis in colorectal cancer: A retrospective study
Bo Ban, An Shang, Jian Shi
Bo Ban, An Shang, Jian Shi, Department of General Surgery, The Second Hospital of Jilin University, Changchun 130041, Jilin Province, China
Author contributions: Ban B designed and performed the research and wrote the paper; Shi J designed the research and supervised the report; Shang A designed the research and contributed to the analysis.
Supported by the Science and Technology Development Project of Jilin Province, No. 2020SCZT079.
Institutional review board statement: This study was reviewed and approved by the Ethics Committee of The Second Hospital of Jilin University (Approval No. 2021-003).
Informed consent statement: The informed consent was waived from the patients.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Jian Shi, MD, PhD, Associate Chief Physician, Associate Professor, Department of General Surgery, The Second Hospital of Jilin University, No. 218 Ziqiang Street, Nanguan District, Changchun 130041, Jilin Province, China. 383888697@qq.com
Received: September 23, 2022
Peer-review started: September 23, 2022
First decision: November 16, 2022
Revised: November 23, 2022
Accepted: December 21, 2022
Article in press: December 21, 2022
Published online: January 15, 2023
Processing time: 109 Days and 5.4 Hours
Abstract
BACKGROUND

Peritoneal metastasis (PM) after primary surgery for colorectal cancer (CRC) has the worst prognosis. Prediction and early detection of metachronous PM (m-PM) have an important role in improving postoperative prognosis of CRC. However, commonly used imaging methods have limited sensitivity to detect PM early. We aimed to establish a nomogram model to evaluate the individual probability of m-PM to facilitate early interventions for high-risk patients.

AIM

To establish and validate a nomogram model for predicting the occurrence of m-PM in CRC within 3 years after surgery.

METHODS

We used the clinical data of 878 patients at the Second Hospital of Jilin University, between January 1, 2014 and January 31, 2019. The patients were randomly divided into training and validation cohorts at a ratio of 2:1. The least absolute shrinkage and selection operator (LASSO) regression was performed to identify the variables with nonzero coefficients to predict the risk of m-PM. Multivariate logistic regression was used to verify the selected variables and to develop the predictive nomogram model. Harrell’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. The model was verified internally using bootstrapping method and verified externally using validation cohort.

RESULTS

LASSO regression analysis identified six potential risk factors with nonzero coefficients. Multivariate logistic regression confirmed the risk factors to be independent. Based on the results of two regression analyses, a nomogram model was established. The 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 status. The model achieved good predictive accuracy on both the training and validation datasets. The C-index, area under the curve, and Brier scores were 0.796, 0.796 [95% confidence interval (CI) 0.735-0.856], and 0.081 for the training cohort and 0.782, 0.782 (95%CI 0.690-0.874), and 0.089 for the validation cohort, respectively. DCA showed that when the threshold probability was between 0.01 and 0.90, using this model to predict m-PM achieved a net clinical benefit.

CONCLUSION

We have established and validated a nomogram model to predict m-PM in patients undergoing curative surgery, which shows good discrimination and high accuracy.

Keywords: Colorectal cancer; Metachronous peritoneal metastasis; Risk factor; Nomogram

Core Tip: The prediction and early detection of metachronous peritoneal metastasis remain a difficult task in clinical practice. Conventional imaging modalities have limited sensitivity for detecting peritoneal nodules < 5 mm in diameter. Second-look surgery may be an alternative means for early detection of PM; however, its invasive nature and surgical complications mean that this approach should only be applied to high-risk patients. The present study aimed to develop a nomogram to help surgeons screen out high-risk patients and select appropriate individualized follow-up and treatment strategies.