Retrospective Cohort Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Surg. Aug 27, 2022; 14(8): 765-777
Published online Aug 27, 2022. doi: 10.4240/wjgs.v14.i8.765
Nomogram to predict permanent stoma in rectal cancer patients after sphincter-saving surgery
Chih-Yu Kuo, Po-Li Wei, Chia-Che Chen, Yen-Kuang Lin, Li-Jen Kuo
Chih-Yu Kuo, Department of Surgery, Taipei Medical University Hospital, Taipei 11031, Taiwan
Po-Li Wei, Chia-Che Chen, Li-Jen Kuo, Division of Colorectal Surgery, Department of Surgery, Taipei Medical University Hospital, Taipei 11031, Taiwan
Po-Li Wei, Li-Jen Kuo, Department of Surgery, School of Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan
Yen-Kuang Lin, Graduate Institute of Athletics and Coaching Science, National Taiwan Sport University, Taoyuan 33301, Taiwan
Li-Jen Kuo, Taipei Cancer Center, Taipei Medical University, Taipei 11031, Taiwan
Author contributions: Kuo CY manuscript writing; Wei PL and Chen CC participate in patients’ treatment and collection; Lin YK data interpretation and statistical analysis; Kuo LJ original idea creator, project coordinator, manuscript reviewing and proofing; Lin YK and Kuo LJ contributed equally to this work; All authors have read and approve the finial manuscript.
Supported by the Taipei Medical University, No. TMU104-AE1-B35.
Institutional review board statement: The study was reviewed and approved for publication by the Joint Institutional Review Board of Taipei Medical University (TMU-JIRB No: N202103023).
Informed consent statement: All study participants or their legal guardian provided informed written consent about personal and medical data collection prior to study enrolment.
Conflict-of-interest statement: All the Authors have no conflict of interest related to the manuscript.
Data sharing statement: The original anonymous dataset is available on request from the corresponding authors Li-Jen Kuo, MD (E-mail: kuolijen@gmail.com) and Yen-Kuang Lin, PhD (E-mail: robbinlin@ntsu.edu.tw).
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: Li-Jen Kuo, MD, Attending Doctor, Division of Colorectal Surgery, Department of Surgery, Taipei Medical University Hospital, No. 252 Wuxing Street, Sinyi District, Taipei 11031, Taiwan. kuolijen@gmail.com
Received: March 4, 2022
Peer-review started: March 4, 2022
First decision: June 12, 2022
Revised: June 21, 2022
Accepted: July 20, 2022
Article in press: July 20, 2022
Published online: August 27, 2022
ARTICLE HIGHLIGHTS
Research background

Despite innovative advancements, the management of rectal cancer remains a formidable endeavor, especially distally located rectal cancer. According to previous studies, 3%-24% of rectal cancer patients experience anastomosis complications after sphincter-saving surgery, which may lead to permanent stoma (PS).

Research motivation

Patients fail to achieve stoma closure can cause drastic changes in lifestyle and physical perceptions.

Research objectives

The purpose of this study was to determine the risk factors for PS and to develop a prediction model to predict the probability of PS in rectal cancer patients after sphincter-saving surgery.

Research methods

A retrospective cohort of 421 rectal cancer patients who underwent radical surgery at Taipei Medical University Hospital between January 2012 and December 2020 was included in this study. Univariate and multivariate analyses were performed to identify the independent risk factors for PS. A nomogram was developed according to the independent risk factors obtained in the multivariate analysis. The performance of the nomogram was assessed using a receiver operating characteristic curve and a calibration curve.

Research results

The PS stoma rate after sphincter-saving surgery was 15.1% (59/391) in our study after a median follow-up of 47.3 mo (range 7-114 mo). Multivariate logistic regression analysis demonstrated that local recurrence, perirectal abscess, anastomosis site stenosis, perineural invasion, tumor size, liver disease, and operative time were independent risk factors for PS. After exclude liver disease, these identified risk factors were incorporated into the nomogram, and the concordance index of this model was 0.903 (95%CI: 0.851-0.955). According to the calibration curves, the nomogram represents a perfect prediction model.

Research conclusions

This study reports that risk factors leading to PS were highly correlated with local recurrence, perirectal abscess, anastomosis site stenosis, perineural invasion, tumor size and operative time (min). Our established nomogram enables a relatively accurate assessment of the risk of PS after sphincter-saving surgery. The ease of use of this nomogram can improve a physician’s ability to communicate the benefits and risks of various treatment options in shared decision making.

Research perspectives

The present study has some limitations. First, this was a retrospective study and was not randomized in nature. In some incomplete patient records, the details of stoma complications after hospital discharge may be difficult to evaluate. Second, the study period was relatively long, and differences may exist in surgeon discretion and surgical techniques. Finally, this analysis was based on data from a single center. External validation using data from other centers is needed to certify the discriminatory ability of this model. More representative prediction models can be developed using data from multiple centers.