Jun 2026· Journal of Gastrointestinal Oncology· Vol 17, pp. 256-256· 0 citations· 38 references
Medicine
TL;DR
This prognostic model provides accurate individualized survival prediction for ECC and facilitates objective risk stratification and facilitates objective risk stratification in palliative settings.
Abstract
Background Extrahepatic cholangiocarcinoma (ECC) is a highly aggressive malignancy. This study aimed to develop and validate a comprehensive prognostic nomogram incorporating treatment data to enable individualized risk stratification and refine patient selection for palliative interventions. Methods Data were extracted from the Surveillance, Epidemiology, and End Results (SEER) program (for the period from 2018 to 2022). There were 2,254 patients identified and randomly divided into model development (n=1,577) and validation (n=677) cohorts. Prognostic factors were selected through multivariate Cox regression using backward elimination based on the Akaike Information Criterion (AIC). A nomogram was developed to estimate 6-month, 1-year, and 3-year survival probabilities. Model performance was evaluated using the consistency index (C-index), calibration curves, and decision curve analysis (DCA). Finally, risk stratification cutoffs were determined to facilitate individualized prognostic assessment in palliative settings. Results The final nomogram incorporated age, N stage, M stage, surgery, and chemotherapy status. The model demonstrated good discrimination, with C-indices of 0.770 [95% confidence interval (CI): 0.750–0.790] in the training cohort and 0.789 (95% CI: 0.768–0.802) in the validation cohort. Calibration curves indicated good agreement between predicted and observed probabilities. DCA revealed good net benefit across clinically relevant threshold probabilities. Risk stratification identified high-risk (<3 months, score ≥70), intermediate-risk (3–12 months, score 59–69), and low-risk (>1 year, score ≤58) groups, potentially guiding the selection between plastic and metal stents in palliative settings. Conclusions This prognostic model provides accurate individualized survival prediction for ECC and facilitates objective risk stratification.
A prognostic nomogram is constructed for mRCC patients, providing a proof-of-concept framework for post-treatment risk stratification, prognostic counseling, and individualized follow-up planning and indicates that surgical intervention is significantly associated with superior survival outcomes in selected patients.
Zhi-Hui Li, Xi-Hao Wang, Yi Zhang et al.· Scientific Reports· 0 citations
The nomogram model incorporating clinicopathological and demographic variables showed higher predictive accuracy than conventional TNM staging for CSS in CRC patients and indicated that the nomogram provided higher net benefit for prognostic risk classification than the traditional TNM staging system across a wide rang...
Yi Liu, Xiao-Jun Tang, Zhi Liu et al.· Cancer Investigation· 0 citations
OBJECTIVES
To develop an individualized nomogram for predicting disease progression risk in systemic anaplastic large cell lymphoma (sALCL).
METHODS
Independent predictors of progression-free survival (PFS) were identified using Cox regression in a multicenter retrospective cohort of 109 sALCL patients (2010-2022). T...
Mei Zhou, Cui-zhen Liu, Zhong Wei et al.· Hematology· 0 citations
PURPOSE
This study aimed to develop an individualized nomogram incorporating clinical and imaging features for predicting recurrence in hepatocellular carcinoma (HCC) patients with microvascular invasion (MVI) after hepatectomy.
METHODS
A total of 317 pathologically confirmed MVI-positive HCC patients who underwent c...
Shi-Yuan Huang, Bin Chen, Yun-Yun Wei et al.· Journal of Gastrointestinal...· 0 citations
Background This study aimed to develop and validate a risk stratification model incorporating the log odds of positive lymph nodes (LODDS) and the prognostic nutritional index (PNI) to predict outcomes in patients with locally advanced gastric cancer (LAGC) undergoing neoadjuvant chemotherapy (NAC). Methods A retrospec...
Zheng-Zhao Wang, Wen-Zhi Wu, Zong-Sheng Sun et al.· Frontiers in Nutrition· 0 citations
The nomogram based on tumor diameter, perineural invasion, and pN stage effectively predicts the risk of LVI in AGC patients, demonstrating high accuracy and clinical applicability.