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Combining lymph node ratio to develop prognostic models for postoperative gastric neuroendocrine neoplasm patients.
Liu, Wen; Wu, Hong-Yu; Lin, Jia-Xi; Qu, Shu-Ting; Gu, Yi-Jie; Zhu, Jin-Zhou; Xu, Chun-Fang.
Afiliación
  • Liu W; Department of Gastroenterology, Changzhou Hospital of Traditional Chinese Medicine, Changzhou 213000, Jiangsu Province, China.
  • Wu HY; Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou 215006, Jiangsu Province, China.
  • Lin JX; Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou 215006, Jiangsu Province, China.
  • Qu ST; Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou 215006, Jiangsu Province, China.
  • Gu YJ; Department of Gastroenterology, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou 215200, Jiangsu Province, China.
  • Zhu JZ; Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou 215006, Jiangsu Province, China.
  • Xu CF; Department of Gastroenterology, The First Affiliated Hospital of Soochow University, Suzhou 215006, Jiangsu Province, China. xuchunfang@suda.edu.cn.
World J Gastrointest Oncol ; 16(8): 3507-3520, 2024 Aug 15.
Article en En | MEDLINE | ID: mdl-39171165
ABSTRACT

BACKGROUND:

Lymph node ratio (LNR) was demonstrated to play a crucial role in the prognosis of many tumors. However, research concerning the prognostic value of LNR in postoperative gastric neuroendocrine neoplasm (NEN) patients was limited.

AIM:

To explore the prognostic value of LNR in postoperative gastric NEN patients and to combine LNR to develop prognostic models.

METHODS:

A total of 286 patients from the Surveillance, Epidemiology, and End Results database were divided into the training set and validation set at a ratio of 82. 92 patients from the First Affiliated Hospital of Soochow University in China were designated as a test set. Cox regression analysis was used to explore the relationship between LNR and disease-specific survival (DSS) of gastric NEN patients. Random survival forest (RSF) algorithm and Cox proportional hazards (CoxPH) analysis were applied to develop models to predict DSS respectively, and compared with the 8th edition American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging.

RESULTS:

Multivariate analyses indicated that LNR was an independent prognostic factor for postoperative gastric NEN patients and a higher LNR was accompanied by a higher risk of death. The RSF model exhibited the best performance in predicting DSS, with the C-index in the test set being 0.769 [95% confidence interval (CI) 0.691-0.846] outperforming the CoxPH model (0.744, 95%CI 0.665-0.822) and the 8th edition AJCC TNM staging (0.723, 95%CI 0.613-0.833). The calibration curves and decision curve analysis (DCA) demonstrated the RSF model had good calibration and clinical benefits. Furthermore, the RSF model could perform risk stratification and individual prognosis prediction effectively.

CONCLUSION:

A higher LNR indicated a lower DSS in postoperative gastric NEN patients. The RSF model outperformed the CoxPH model and the 8th edition AJCC TNM staging in the test set, showing potential in clinical practice.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: World J Gastrointest Oncol Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: World J Gastrointest Oncol Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: China