ArticleCancer control : journal of the Moffitt Cancer Center
Nomogram for Predicting Survival Post-Immune Therapy in Cholangiocarcinoma Based on Inflammatory Biomarkers.
Article in Cancer control : journal of the Moffitt Cancer Center. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Correlated expression of MYBL2 and CCL5 defines an immunosuppressive microenvironment and predicts poor prognosis in intrahepatic cholangiocarcinoma.BMC cancer · 2026Article
- Colorectal cancer liver metastasis: immunosuppressive microenvironment, signaling pathways, and emerging therapeutic strategies.Frontiers in immunology · 2026Review
- From PD-1/PD-L1 to tertiary lymphoid structures: Paving the way for precision immunotherapy in cholangiocarcinoma treatment.Human vaccines & immunotherapeutics · 2025Article
- Construction of a predictive model for gemcitabine combined with cisplatin resistance in intrahepatic cholangiocarcinoma based on multidimensional inflammatory indices.Journal of gastrointestinal oncology · 2025Article
- Applications of artificial intelligence in cancer immunotherapy: a frontier review on enhancing treatment efficacy and safety.Frontiers in immunology · 2025Review
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Authors and funding
4 authors.
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Abstract
backgroundImmune therapy, especially involving PD-1/PD-L1 inhibitors, has shown promise as a therapeutic option for cholangiocarcinoma. However, limited studies have evaluated survival outcomes in cholangiocarcinoma patients treated with immune therapy. This study aims to develop a predictive model to evaluate the survival benefits of immune therapy in patients with cholangiocarcinoma.
methodsThis retrospective analysis included 120 cholangiocarcinoma patients from Shulan (Hangzhou) Hospital. Univariate and multivariate Cox regression analyses were conducted to identify factors associated with survival following immune therapy. A predictive model was constructed and validated using calibration curves (CC), decision curve analysis (DCA), concordance index (C-index), and receiver operating characteristic (ROC) curves.
resultsCox regression analysis identified several factors as potential predictors of survival post-immune therapy in cholangiocarcinoma: treatment cycle (<6 vs ≥ 6 months, 95% CI: 0.119-0.586,
conclusionThe nomogram model, incorporating key risk factors for cholangiocarcinoma patients post-immune therapy, demonstrates robust predictive accuracy for survival outcomes, offering the potential for improved clinical decision-making.
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