Novel Signatures Based on the Lymphocyte-to-C-Reactive Protein Ratio Predict the Prognosis of Patients with Early Breast Cancer: A Retrospective Study

Abstract

Li Wang,1,* Yu-Ling Zhang,2,* Chang Jiang,1,* Fang-Fang Duan,1 Zhong-Yu Yuan,1 Jia-Jia Huang,1 Xi-Wen Bi1 1Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, People’s Republic of China; 2Department of Endocrinology, Jiangxi Provincial People’s Hospital, Nanchang, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xi-Wen Bi; Jia-Jia Huang, Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, People’s Republic of China, Email [email protected]; [email protected]: The value of the lymphocyte-to-C-reactive protein (CRP) ratio (LCR) in early breast cancer (BC) is unclear. We explored the correlation between the LCR and survival of patients with early BC and established effective LCR-based prognostic signatures for predicting prognosis.Methods: In this retrospective study, we randomized 623 patients with early-stage BC diagnosed in December 2010 to October 2012 at the Sun Yat-sen University Cancer Center to training and verification datasets. The median follow-up of all patients was 109 months. The survival differences were calculated by Kaplan–Meier method using the Log rank test. For overall survival (OS) and disease-free survival (DFS), the independent factors in the training dataset were identified using univariate and multivariate Cox analyses, in which two-tailed P-values < 0.05 were considered statistically significant. Based on this, we respectively constructed novel signatures for survival prediction and validated the efficiency of signatures through the concordance index (C-index), calibration and receiver operating characteristic (ROC) curves in both datasets.Results: The LCR, lymphatic vessel invasion (LVI), progesterone receptor (PR) status, and Ki67 index were independent prognostic factors of OS. And the LCR and LVI are associated to DFS too. High LCR was associated with better OS and DFS. We constructed the prediction signatures based on those independent prognostic factors and calculated the risk scores. Patients in the training dataset with higher risk scores had significantly worse prognosis (P < 0.001). The signature had excellent discrimination capacity, with an OS C-index of 0.785 [95% confidence interval (CI): 0.713– 0.857] and 0.750 (95% CI: 0.669– 0.832) in the training and verification datasets, respectively. The time–ROC curves also suggest accurate prediction by the signature.Conclusion: The LCR was a significant prognostic predictor of OS and DFS in early BC. The LCR-based prognostic signatures could be a useful tool for individualized therapeutic guidance.Keywords: survival, nomogram, early breast cancer, LCR

Keywords

• survival
• nomogram
• early breast cancer
• lcr