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Establishment and Verification of Scoring System for Colorectal Adenoma Recurrence

OBJECTIVE: The purpose of this study was to establish and verify a risk-scoring system for colorectal adenoma recurrence. METHODS: A total of 359 patients with colorectal adenoma who underwent polypectomy from October 2017 to December 2018 were included in this retrospective study. Information inclu...

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Detalles Bibliográficos
Autores principales: Xi, Xujie, Fu, Zhaoli, Liu, Tianwen, Lin, Yanfeng, Wu, Wenbin, Li, Jianmin, Luo, Ming, Zhang, Beiping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8590838/
https://www.ncbi.nlm.nih.gov/pubmed/34785963
http://dx.doi.org/10.2147/RMHP.S316408
Descripción
Sumario:OBJECTIVE: The purpose of this study was to establish and verify a risk-scoring system for colorectal adenoma recurrence. METHODS: A total of 359 patients with colorectal adenoma who underwent polypectomy from October 2017 to December 2018 were included in this retrospective study. Information including taking traditional Chinese medicine, demographic characteristics, adenoma characteristics were collected. The patients will review the colonoscopy one year after surgery. The patients were divided into a modeling cohort (216 cases) and a model validation cohort (143 cases) according to the ratio of 6:4. Modeling and model verification were performed by logistic regression, ROC curve, nomogram (calibration chart) and other methods. RESULTS: After adjusting for confounding factors by logistic regression, it was found that taking Chinese medicine, the number, size, site, pathological type and morphology of adenoma were independent influencing factors for the recurrence of colorectal adenoma. The area under the ROC curve (AUC) in the model validation cohort of established risk scoring system was 0.771 (95% CI: 0.694–0.847), indicating that there was good consistency. CONCLUSION: The established risk prediction model of colorectal adenoma recurrence and its risk scoring system performed well and had high predictive value.