Subgroup-Specific Nomogram for Refined Risk Stratification in Hepatocellular Carcinoma Patients with Low LDL-C.

IF 3.9 3区 医学 Q2 ONCOLOGY
Journal of Hepatocellular Carcinoma Pub Date : 2026-06-15 eCollection Date: 2026-01-01 DOI:10.2147/JHC.S616354
Bojun Liu, Zhixia Gu, Ling Li, Lei Li, Ronghua Jin, Caixia Hu
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引用次数: 0

Abstract

Background: Hepatocellular carcinoma (HCC) exhibits high mortality and clinical heterogeneity. While low low-density lipoprotein cholesterol (LDL-C) is a recognized risk factor for HCC, its continuous dose-response relationship with overall survival (OS) remains unclear. Furthermore, existing prognostic models lack precision for this specific high-risk population, highlighting an urgent need for individualized risk stratification.

Methods: A retrospective cohort of 486 HCC patients treated at Beijing You'an Hospital (January 1, 2015-January 1, 2021) was analyzed. Restricted cubic splines (RCS) and Cox regression evaluated the LDL-C and OS dose-response relationship. Following quartile stratification (Q1-Q4), the cohort was dichotomized into low (Q1+Q2, n=245) and high (Q3+Q4, n=241) LDL-C groups. Within the high-risk low LDL-C subgroup, least absolute shrinkage and selection operator (LASSO) regression identified core features to construct a specific nomogram, validated via concordance index (C-index), receiver operating characteristic (ROC) curves, calibration, decision curve analysis (DCA), and Kaplan-Meier (KM) curves for risk stratification.

Results: RCS analysis revealed a non-linear relationship: mortality risk increased as baseline LDL-C decreased below 2.2 mmol/L. Multivariable Cox regression confirmed LDL-C as an independent protective factor for OS (HR=0.714, 95% CI: 0.539-0.947, P=0.019). KM analysis demonstrated significantly inferior OS in the low LDL-C cohort compared to the high LDL-C group (P=0.013). The subgroup-specific nomogram, integrating drinking history, Barcelona Clinic Liver Cancer stage, tumor number, and thrombin time, exhibited good discrimination (C-index=0.686; 3- and 5-year AUCs=0.752 and 0.696, respectively), accurate calibration, and positive clinical benefit. Furthermore, the model achieved secondary risk stratification within this subgroup (P<0.0001).

Conclusion: Lower baseline LDL-C is an independent predictor of worse OS. The developed subgroup-specific nomogram provides an objective tool for secondary risk stratification, aiding personalized therapeutic management for this high-risk population.

低LDL-C肝细胞癌患者精细风险分层的亚组特异性Nomogram。
背景:肝细胞癌(HCC)具有高死亡率和临床异质性。虽然低密度脂蛋白胆固醇(LDL-C)是HCC的公认危险因素,但其与总生存期(OS)的持续剂量-反应关系尚不清楚。此外,现有的预后模型对这一特定的高危人群缺乏精确性,因此迫切需要进行个体化的风险分层。方法:对2015年1月1日至2021年1月1日在北京佑安医院治疗的486例HCC患者进行回顾性队列分析。限制性三次样条(RCS)和Cox回归评估LDL-C和OS的剂量-反应关系。按照四分位数分层(Q1-Q4),将该队列分为低(Q1+Q2, n=245)和高(Q3+Q4, n=241) LDL-C组。在高风险低LDL-C亚组中,最小绝对收缩和选择算子(LASSO)回归识别核心特征以构建特定的nomogram,并通过一致性指数(C-index)、受试者工作特征(ROC)曲线、校准、决策曲线分析(DCA)和Kaplan-Meier (KM)曲线进行风险分层验证。结果:RCS分析显示出非线性关系:当基线LDL-C低于2.2 mmol/L时,死亡风险增加。多变量Cox回归证实LDL-C是OS的独立保护因素(HR=0.714, 95% CI: 0.539 ~ 0.947, P=0.019)。KM分析显示低LDL-C组的OS明显低于高LDL-C组(P=0.013)。结合饮酒史、巴塞罗那临床肝癌分期、肿瘤数目和凝血酶时间的亚组特异性nomogram鉴别性好(C-index=0.686, 3年和5年aus分别=0.752和0.696),校正准确,临床获益积极。此外,该模型在该亚组中实现了二级风险分层(结论:较低的基线LDL-C是较差的OS的独立预测因子。发展的亚组特异性nomogram为二级风险分层提供了客观的工具,有助于对这一高危人群进行个性化的治疗管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
0.50
自引率
2.40%
发文量
108
审稿时长
16 weeks
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