Xing Li1, Hailin Tang2, Jin Wang3, Xinhua Xie4, Peng Liu5, Yanan Kong6, Feng Ye7, Zeyu Shuang8, Zeming Xie9, Xiaoming Xie10. 1. Department of Breast Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, PR China. Electronic address: lixing@sysucc.org.cn. 2. Department of Breast Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, PR China. Electronic address: tanghl@sysucc.org.cn. 3. Department of Breast Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, PR China. Electronic address: wangjin@sysucc.org.cn. 4. Department of Breast Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, PR China. Electronic address: xiexh@sysucc.org.cn. 5. Department of Breast Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, PR China. Electronic address: liupeng@sysucc.org.cn. 6. Department of Breast Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, PR China. Electronic address: kongyn@sysucc.org.cn. 7. Department of Breast Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, PR China. Electronic address: yefeng@sysucc.org.cn. 8. Department of Breast Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, PR China. Electronic address: shuangzy@sysucc.org.cn. 9. Department of Breast Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, PR China. Electronic address: xiezm@sysucc.org.cn. 10. Department of Breast Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, 510060, PR China. Electronic address: xiexm@sysucc.org.cn.
Abstract
OBJECTIVES: Although dyslipidemia has been documented to be associated with several types of cancer including breast cancer, it remains uncertainty the prognostic value of serum lipid in breast cancer. The purpose of this study is to evaluate the association between the preoperative plasma lipid profile and the prognostic of breast cancer patients. METHODS: The levels of preoperative serum lipid profile (including cholesterol [CHO], Triglycerides [TG], high-density lipoprotein-cholesterol [HDL-C], low-density lipoprotein-cholesterol [LDL-C], apolipoprotein A-I [ApoAI], and apolipoprotein B [ApoB]) and the clinical data were retrospectively collected and reviewed in 1044 breast cancer patients undergoing operation. Kaplan-Meier method and the Cox proportional hazards regression model were used in analyzing the overall survival [OS] and disease-free survival [DFS]. RESULTS: Combining the receiver-operating characteristic and Kaplan-Meier analysis, we found that preoperative lower TG and HDL-C level were risk factors of breast cancer patients. In multivariate analyses, a decreased HDL-C level showed significant association with worse OS (HR: 0.528; 95% CI: 0.302-0.923; P = 0.025), whereas a decreased TG level showed significant association with worse DFS (HR: 0.569; 95% CI: 0.370-0.873; P = 0.010). CONCLUSIONS: Preoperative serum levels of TG and HDL-C may be independent factor to predict outcome in breast cancer patient.
OBJECTIVES: Although dyslipidemia has been documented to be associated with several types of cancer including breast cancer, it remains uncertainty the prognostic value of serum lipid in breast cancer. The purpose of this study is to evaluate the association between the preoperative plasma lipid profile and the prognostic of breast cancerpatients. METHODS: The levels of preoperative serum lipid profile (including cholesterol [CHO], Triglycerides [TG], high-density lipoprotein-cholesterol [HDL-C], low-density lipoprotein-cholesterol [LDL-C], apolipoprotein A-I [ApoAI], and apolipoprotein B [ApoB]) and the clinical data were retrospectively collected and reviewed in 1044 breast cancerpatients undergoing operation. Kaplan-Meier method and the Cox proportional hazards regression model were used in analyzing the overall survival [OS] and disease-free survival [DFS]. RESULTS: Combining the receiver-operating characteristic and Kaplan-Meier analysis, we found that preoperative lower TG and HDL-C level were risk factors of breast cancerpatients. In multivariate analyses, a decreased HDL-C level showed significant association with worse OS (HR: 0.528; 95% CI: 0.302-0.923; P = 0.025), whereas a decreased TG level showed significant association with worse DFS (HR: 0.569; 95% CI: 0.370-0.873; P = 0.010). CONCLUSIONS: Preoperative serum levels of TG and HDL-C may be independent factor to predict outcome in breast cancerpatient.
Authors: Bing Dong; Xiaoxing Yin; Han Xu; Kun Zhou; Longzhi Li; Baoxing Tian; Rongrong Cui Journal: Am J Transl Res Date: 2022-04-15 Impact factor: 3.940