ArticleSurgical endoscopy2024
LASSO-based nomogram predicts the risk factors of low anterior resection syndrome for middle and low rectal cancer underwent robotic surgery.
Article in Surgical endoscopy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Effectiveness of intraoperative stay sutures and postoperative anal dilatation in preventing anastomotic stricture after low rectal cancer resection with defunctioning stoma.BMC gastroenterology · 2026Trial
- Biomarker-integrated machine learning models for predicting treatment-related bowel dysfunction after rectal cancer surgery: a multicenter development and external validation study.Frontiers in medicine · 2026Article
- Development and validation of a LASSO-based nomogram for predicting anastomotic leakage in elderly patients after laparoscopic gastrectomy.Journal of gastrointestinal oncology · 2025Article
- Development and validation of a risk prediction model for dyslipidemia in community-dwelling middle-aged and older adults in China: a nationwide survey.Frontiers in public health · 2024Article
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Authors and funding
8 authors.
Funding
Abstract
backgroundThis study aims to analyze the influencing factors of postoperative Low Anterior Resection Syndrome (LARS) in patients with middle and low rectal cancer who underwent robotic surgery. It also seeks to predict the probability of LARS through a visual, quantitative, and graphical nomogram. This approach is expected to lower the risk of postoperative LARS in these patients and improve their quality of life through effective prevention and early intervention. PATIENTS AND
methodsThis research involved patients with middle and low rectal cancer who underwent robotic surgery in the Department of Gastrointestinal Surgery at the First Affiliated Hospital of Nanchang University from January 2015 to October 2022. A series of intestinal dysfunction symptoms arising from postoperative rectal cancer were diagnosed and graded using LARS scoring criteria. After the initial screening of all variables related to LARS with Lasso regression, they were included in logistic regression for further univariate and multivariate analysis to identify independent risk factors for LARS. A prediction model was then constructed.
resultsThe study included 358 patients. The parameters identified by Lasso regression included obstruction, BMI, tumor localization, maximum tumor diameter, AJCC stage, stoma, neoadjuvant therapy (NAT), and postoperative adjuvant therapy (AT). Univariate and multivariate analyses indicated that a higher BMI, lower tumor localization, higher AJCC stage, neoadjuvant therapy, and postoperative adjuvant therapy were independent risk factors for total LARS. The AUC of the prediction nomogram was 0.834, with a sensitivity of 0.825 and specificity of 0.741. The calibration curve demonstrated excellent concordance with the nomogram, indicating the prediction curve fit the diagonal well.
conclusionHigher BMI, lower tumor localization, higher AJCC stage, neoadjuvant therapy, and adjuvant therapy were identified as independent risk factors for total LARS. A new predictive nomogram for postoperative LARS in patients with middle and low rectal cancer undergoing robotic surgery was developed, proving to be stable and reliable. This tool will assist clinicians in managing the postoperative treatment of these patients, facilitating better clinical decision-making and maximizing patient benefits.
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