Remnant cholesterol is an effective biomarker for predicting survival in patients with breast cancer

Author:

Shi Jinyu,Liu Tong,Liu Chenan,Zhang Heyang,Ruan Guotian,Xie Hailun,Lin Shiqi,Zheng Xin,Chen Yue,Zhang Qi,Zhang Xiaowei,Li Xiangrui,Liu Xiaoyue,Deng Li,Shi Han-Ping

Abstract

Abstract Background Breast cancer is the most common malignancy in women worldwide. The relationship between remnant cholesterol (RC) and the prognosis of patients with breast cancer has not been clearly reported. This study investigated the prognostic value of RC in predicting mortality in patients with breast cancer. Methods This study prospectively analysed 709 women patients with breast cancer from the Investigation on Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) project. Restricted cubic splines were used to analyse the dose-response relationship between RC and breast cancer mortality. The Kaplan–Meier method was used to evaluate the overall survival of patients with breast cancer. A Cox regression analyses was performed to assess the independent association between RC and breast cancer mortality. Inverse probability of treatment weighting (IPTW) using the propensity score was used to reduce confounding. Sensitivity analysis was performed after excluding patients with underlying diseases and survival times shorter than one year. Results A linear dose-response relationship was identified between RC and the risk of all-cause mortality in patients with breast cancer (p = 0.036). Kaplan–Meier survival analysis and log-rank test showed that patients with high RC levels had poorer survival than those with low RC levels (p = 0.007). Univariate and multivariate Cox regression analyses showed that RC was an independent risk factor for mortality in women patients with breast cancer. IPTW-adjusted analyses and sensitivity analyses showed that CR remained a prognostic factor. Conclusions RC is an independent risk factor for the prognosis of patients with breast cancer, and patients with higher RC levels have poorer survival.

Funder

National Key Research and Development Program of China

Beijing Municipal Science and Technology Commission

Publisher

Springer Science and Business Media LLC

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