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A new clinical model for predicting lymph node metastasis in T1 colorectal cancer.
Wang, Kai; He, Hui; Lin, Yanyun; Zhang, Yanhong; Chen, Junguo; Hu, Jiancong; He, Xiaosheng.
Afiliación
  • Wang K; Department of Anaesthesia, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • He H; Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Lin Y; Department of General Surgery (Colorectal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Zhang Y; Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Chen J; Department of General Surgery (Colorectal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Hu J; Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • He X; Department of General Surgery (Colorectal Surgery), The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
Int J Colorectal Dis ; 39(1): 46, 2024 Apr 03.
Article en En | MEDLINE | ID: mdl-38565736
ABSTRACT

PURPOSE:

Lymph node metastasis (LNM) is a crucial factor that determines the prognosis of T1 colorectal cancer (CRC) patients. We aimed to develop a practical prediction model for LNM in T1 CRC.

METHODS:

We conducted a retrospective analysis of data from 825 patients with T1 CRC who underwent radical resection at a single center in China. All enrolled patients were randomly divided into a training set and a validation set at a ratio of 73 using R software. Risk factors for LNM were identified through multivariate logistic regression analyses. Subsequently, a prediction model was developed using the selected variables.

RESULTS:

The lymph node metastasis (LNM) rate was 10.1% in the training cohort and 9.3% in the validation cohort. In the training set, risk factors for LNM in T1 CRC were identified, including depressed endoscopic gross appearance, sex, submucosal invasion combined with tumor grade (DSI-TG), lymphovascular invasion (LVI), and tumor budding. LVI emerged as the most potent predictor for LNM. The prediction model based on these factors exhibited good discrimination ability in the validation sets (AUC 79.3%). Compared to current guidelines, the model could potentially reduce over-surgery by 48.9%. Interestingly, we observed that sex had a differential impact on LNM between early-onset and late-onset CRC patients.

CONCLUSIONS:

We developed a clinical prediction model for LNM in T1 CRC using five factors that are easily accessible in clinical practice. The model has better predictive performance and practicality than the current guidelines and can assist clinicians in making treatment decisions for T1 CRC patients.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias Colorrectales / Modelos Estadísticos Límite: Humans País/Región como asunto: Asia Idioma: En Revista: Int J Colorectal Dis Asunto de la revista: GASTROENTEROLOGIA Año: 2024 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias Colorrectales / Modelos Estadísticos Límite: Humans País/Región como asunto: Asia Idioma: En Revista: Int J Colorectal Dis Asunto de la revista: GASTROENTEROLOGIA Año: 2024 Tipo del documento: Article País de afiliación: China