Evidence map›Paper›PMID 42630623›Full record

ArticleFrontiers in oncology2026

Development of an HDL-C combined with AJCC staging system for predicting overall survival after curative resection of intrahepatic cholangiocarcinoma without metabolic comorbidities.

Chengzhi Jiang, Kaijun Long, Qian Ma, Fang Cheng, Ji Tao, Kaiguo Long

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Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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6 authors.

Chengzhi Jiang *Department of Gastrointestinal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China.
Kaijun Long *Department of Breast and Thyroid Surgery, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China.
Qian MaDepartment of Critical Care Medicine, Wenjiang District People's Hospital, Chengdu, China.
Fang ChengDepartment of General Surgery, The Second People's Hospital of Yibin, Yibin, Sichuan, China.
Ji TaoDepartment of Gastrointestinal Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China.
Kaiguo LongDepartment of Breast and Thyroid Surgery, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To develop and validate a prognostic model integrating HDL-C and AJCC staging system for predicting overall survival (OS) in patients with intrahepatic cholangiocarcinoma (ICC) following curative resection without metabolic comorbidities. Patients and methods: A total of 291 with ICC who underwent curative resection between June 2013 and November 2024 were retrospectively enrolled and randomly assigned to a training cohort (n=203) and a validation cohort (n=88). Receiver operating characteristic (ROC) curve analysis was performed to identify the optimal serum lipid biomarkers. Independent prognostic factors for OS were identified using univariate and multivariate Cox proportional hazards regression analyses. A nomogram incorporating clinicopathological characteristics and serum lipid parameters was subsequently developed and internally validated using calibration curves, time-dependent ROC curves, the concordance index (C-index), the Hosmer-Lemeshow goodness-of-fit test, and decision curve analysis (DCA). Results: LDL-C and HDL-C demonstrated favorable predictive performance, with AUC values of 0.9012 and 0.8557, respectively. Multivariate Cox regression analysis identified low body mass index, low HDL-C, smoking, lymphatic invasion, perineural invasion, and AJCC stage as independent adverse prognostic factors for OS. The nomogram demonstrated good predictive performance, with 1-, 2-, and 3-year AUC values of 0.866, 0.801, and 0.721, respectively, and a C-index of 0.701 in the training cohort. Calibration curves showed good agreement between predicted and observed survival probabilities, while DCA confirmed favorable clinical utility. Internal validation further showed good discriminative ability, with an AUC of 0.811. Conclusion: A modified prognostic model integrating HDL-C with the AJCC staging system was successfully developed and validated for predicting overall survival in patients with ICC who underwent curative resection. Low HDL-C was identified as an independent adverse prognostic factor, suggesting that altered lipid metabolism may contribute to ICC progression. This model may provide a practical tool for individualized prognostic assessment and clinical decision-making.

Indexed as

AJCC staging systemHDL-Cintrahepatic cholangiocarcinomalipid metabolismnomogram

Identifiers

PMID42630623
PMCPMC13494928

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