Evidence map›Paper›PMID 39735602›Full record

ArticleFrontiers in oncology2024

Prediction model construction for the occurrence of LARS after neoadjuvant therapy combined with laparoscopic total mesorectal excision in male patients with mid-low rectal cancer.

Deng-Chao Wang, Xue-Feng Peng, Miao Yu

Abstract read
In one paragraph

Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Deng-Chao WangDepartment of General Surgery, Zigong Fourth People's Hospital, Zigong, Sichuan, China.
Xue-Feng PengDepartment of General Surgery, Zigong Fourth People's Hospital, Zigong, Sichuan, China.
Miao YuDepartment of Basic Medicine, Sichuan Vocational College of Health and Rehabilitation, Zigong, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Neoadjuvant chemoradiotherapy for rectal cancer improves surgical outcomes and reduces recurrence but can cause low anterior resection syndrome (LARS), affecting quality of life. This study aims to predict the risk of LARS in male patients with mid-low rectal cancer after laparoscopic total mesorectal excision (TME). Methods: Clinical data from 203 male patients with mid-low rectal cancer who underwent neoadjuvant therapy and laparoscopic resection were collected. Patients were divided into training (n=143) and validation (n=60) cohorts. LARS risk factors were identified using logistic regression, and a predictive model was constructed and validated using ROC curve, Hosmer-Lemeshow test, calibration curve, and decision curve analysis (DCA). Results: LARS occurred in 53.6% of the patients in this study. Multivariate logistic regression analysis revealed that BMI ≥ 25 kg/m², tumor distance from the anal margin < 5 cm, radiotherapy, and anastomotic leakage were independent risk factors for postoperative LARS in patients (P < 0.05). The areas under the ROC curves for the training cohort and validation cohort were 0.866 (95% CI: 0.807-0.925) and 0.724 (95% CI: 0.595-0.853), respectively, with both groups showing good goodness-of-fit test results (P > 0.05). The DCA curve indicated that the model had a high clinical utility. Conclusions: BMI ≥ 25 kg/m², tumor distance from the anal margin < 5 cm, radiotherapy, and anastomotic leakage are independent risk factors for the occurrence of LARS after neoadjuvant therapy combined with laparoscopic TME in male patients with mid-low rectal cancer. These factors should be emphasized in clinical practice, and corresponding preventive measures should be promptly implemented.

Indexed as

LARSmaleneoadjuvant therapyprediction modelrectal cancer

Identifiers

PMID39735602
PMCPMC11671363

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.