Evidence map›Paper›PMID 38777891›Full record

ArticleSurgical endoscopy2024

A nomogram of anastomotic stricture after rectal cancer: a retrospective cohort analysis.

Yifan Cheng, Zhen Tian, Shuyang Gao, Shuai Zhao, Ruiqi Li, Jiajie Zhou, Qiannan Sun, Daorong Wang

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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 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Yifan Cheng *Northern Jiangsu People's Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Yangzhou, China.ORCID 0000-0003-3957-9825
Zhen Tian *Northern Jiangsu People's Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Yangzhou, China.
Shuyang GaoNorthern Jiangsu People's Hospital Affiliated to Dalian Medical University, Yangzhou, 225001, China.
Shuai ZhaoNorthern Jiangsu People's Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Yangzhou, China.
Ruiqi LiNorthern Jiangsu People's Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Yangzhou, China.
Jiajie ZhouNorthern Jiangsu People's Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Yangzhou, China.
Qiannan SunNorthern Jiangsu People's Hospital, Yangzhou, 225001, China.
Daorong WangNorthern Jiangsu People's Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Yangzhou, China. wdaorong666@sina.com.ORCID 0000-0003-1245-4002

Funding

National Natural Science Foundation of China 82373014YangZhou Municipal Science and Technology Bureau YZ2020159
6 · The paper itself

Abstract

backgroundAnastomotic stricture significantly impacts patients' quality of life and long-term prognosis. However, current clinical practice lacks accurate tools for predicting anastomotic stricture. This study aimed to develop a nomogram to predict anastomotic stricture in patients with rectal cancer who have undergone anterior resection.

methodsA total of 1542 eligible patients were recruited for the study. Least absolute shrinkage selection operator (Lasso) analysis was used to preliminarily select predictors. A prediction model was constructed using multivariate logistic regression and presented as a nomogram. The performance of the nomogram was evaluated using receiver operating characteristic (ROC) curves, calibration diagrams, and decision curve analysis (DCA). Internal validation was conducted by assessing the model's performance on a validation cohort.

results72 (4.7%) patients were diagnosed with anastomotic stricture. Participants were randomly divided into training (n = 1079) and validation (n = 463) sets. Predictors included in this nomogram were radiotherapy, diverting stoma, anastomotic leakage, and anastomotic distance. The area under the ROC curve (AUC) for the training set was 0.889 [95% confidence interval (CI) 0.840-0.937] and for the validation set, it was 0.930 (95%CI 0.879-0.981). The calibration curve demonstrated a strong correlation between predicted and observed outcomes. DCA results showed that the nomogram had clinical value in predicting anastomotic stricture in patients after anterior resection of rectal cancer.

conclusionWe developed a predictive model for anastomotic stricture following anterior resection of rectal cancer. This nomogram could assist clinicians in predicting the risk of anastomotic stricture, thus improving patients' quality of life and long-term prognosis.

Indexed as

Anastomosis, SurgicalNomogramsPostoperative ComplicationsRectal NeoplasmsAdultAgedAnastomotic LeakConstriction, PathologicFemaleHumansMaleMiddle AgedRectumRetrospective StudiesROC CurveAnastomotic strictureNomogram prediction modelRectal cancerRisk factor

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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.