Retrospective Cohort Study
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Oct 21, 2023; 29(39): 5483-5493
Published online Oct 21, 2023. doi: 10.3748/wjg.v29.i39.5483
Development and validation of a nomogram for preoperative prediction of tumor deposits in colorectal cancer
Hui-Da Zheng, Yun-Huang Hu, Kai Ye, Jian-Hua Xu
Hui-Da Zheng, Yun-Huang Hu, Kai Ye, Jian-Hua Xu, Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou 362000, Fujian Province, China
Author contributions: Zheng HD designed/planned the study and wrote the paper; Zheng HD, Hu YH and Ye K acquired and analyzed data and performed computational modeling; Xu JH participated in discussion of related data; All authors read and approved the final manuscript.
Supported by Fujian Province Science and Technology Innovation Joint Fund Project, No. 2021Y9029.
Institutional review board statement: The study was reviewed and approved for publication by our Institutional Reviewer.
Informed consent statement: As the study used anonymous and pre-existing data, the requirement for the informed consent from patients was waived.
Conflict-of-interest statement: All the Authors have no conflict of interest related to the manuscript.
Data sharing statement: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
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-Hua Xu, MD, Chief Physician, Dean, Research Dean, Surgeon, Surgical Oncologist, Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Fujian Medical University, No. 950 Donghai Street, Fengze District, Quanzhou 362000, Fujian Province, China. xjh630913@126.com
Received: July 11, 2023
Peer-review started: July 11, 2023
First decision: September 18, 2023
Revised: September 21, 2023
Accepted: September 28, 2023
Article in press: September 28, 2023
Published online: October 21, 2023
Processing time: 100 Days and 3 Hours
ARTICLE HIGHLIGHTS
Research background

Colorectal cancer (CRC) poses a serious threat to human life and health. Previous studies have shown that tumor deposits (TDs) are significantly associated with early metastasis and poor prognosis. However, research on related risk factors is limited, and accurate prediction of TDs remains challenging. We developed a model based on preoperative clinical and pathological features to accurately predict the likelihood of TDs in CRC patients.

Research motivation

At present, the diagnosis of TDs in CRC requires postoperative pathology, which is passive for clinicians. If TDs can be accurately identified before patients receive treatment, it is of great importance for evaluating clinical staging, selecting reasonable treatment plans, and judging the prognosis of CRC patients.

Research objectives

To develop and validate a nomogram with good predictive ability for the preoperative prediction of TDs in patients with CRC.

Research methods

We retrospectively collected the data of 645 eligible patients with CRC. SPSS 27.0 and R (version 4.2.1) were used for statistical analysis, and a prediction model for TDs in CRC patients was established.

Research results

A total of 51 patients with CRC had TDs in this study. The areas under the curve of the training cohort and the validation cohort were 0.839 and 0.853, respectively. The model showed good accuracy and discrimination ability and has broad clinical practicability. The results of this study suggest the value of preoperative indicators in predicting TDs in CRC patients and can assist in guiding clinical decision making.

Research conclusions

This nomogram based on preoperative indicators can effectively predict the preoperative TD status of CRC.

Research perspectives

In the future, we will try to apply radiomics combined with clinical indicators to construct a model to predict the status of TDs in CRC patients.