Predicting survival rates: the power of prognostic nomograms in distal cholangiocarcinoma.

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Tác giả: Jingnan Chen, Jinsuo Chen, Yuwei Dong, Bensong Duan, Jiangfeng Hu, Yang Jiang, Lihua Jin, Yuping Shi, Dadong Wan, Weixin Ye, Suhong Yi, Yajing Zhang

Ngôn ngữ: eng

Ký hiệu phân loại: 613.69 Survival

Thông tin xuất bản: Switzerland : Frontiers in oncology , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 51398

OBJECTIVE: The purpose of this research is to establish a prognostic nomogram for patients with distal cholangiocarcinoma (dCCA). METHODS: We obtained clinical data from 2401 patients diagnosed with distal cholangiocarcinoma (dCCA) between 2010 and 2020 from the Surveillance, Epidemiology, and End Results database. These patients were randomly assigned to either the training or validation group in a ratio of 6:4. 228 patients were enrolled from 9 hospitals in China as the external validation cohort. Univariate and multifactorial Cox regression analyses were conducted to ascertain prognostic factors and prognostic nomograms were developed utilizing LASSO logistic regression analysis. We used the calibration curve, and area under the curve to validate the nomograms. Decision curve analysis was used to evaluate the model and its clinical applicability. RESULTS: The findings demonstrated that Grade, M stages, Surgery, and Chemotherapy emerged as autonomous prognostic factors for the survival of individuals with dCCA. The developed nomograms exhibited satisfactory accuracy in forecasting 1-year, 3-year, and 5-year survival probabilities. Furthermore, the calibration curves indicated a strong concordance between the anticipated and observed outcomes. The AUC of the nomogram for 1-year, 3-year, 5 year overall survival (OS) predication were 0.809 (95%CI 78.5-83.3), 0.79 (95%CI 75.8-82.2) and 0.761 ((95%CI 72.3-80.0) in the training cohort, 0.79 (95%CI 75.9-82.0), 0.73 (95%CI 68.5-77.5), and 0.732(95%CI 68.0-78.3) in internal test cohort, 0.862 (95%CI 81.7-90.7),0.83 (95%CI 76.4-89.6),and 0.819(95%CI 74.6-89.2) in external test cohort. CONCLUSION: The nomograms that have been suggested demonstrate strong predictive capability. These tools can assist medical professionals in assessing the prognosis of patients with dCCA and in devising more accurate treatment strategies for them.
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