Wang Li, Zhang Yu-Ling, Jiang Chang, Duan Fang-Fang, Yuan Zhong-Yu, Huang Jia-Jia, Bi Xi-Wen
Department 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.
Department of Endocrinology, Jiangxi Provincial People's Hospital, Nanchang, People's Republic of China.
J Inflamm Res. 2022 Jul 13;15:3957-3974. doi: 10.2147/JIR.S364284. eCollection 2022.
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.
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.
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 ( < 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.
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.
淋巴细胞与C反应蛋白（CRP）比值（LCR）在早期乳腺癌（BC）中的价值尚不清楚。我们探讨了LCR与早期BC患者生存率之间的相关性，并建立了基于LCR的有效预后特征以预测预后。
在这项回顾性研究中，我们将2010年12月至2012年10月在中山大学肿瘤防治中心确诊的623例早期BC患者随机分为训练集和验证集。所有患者的中位随访时间为109个月。采用Kaplan-Meier法和Log rank检验计算生存差异。对于总生存期（OS）和无病生存期（DFS），使用单因素和多因素Cox分析确定训练集中的独立因素，其中双尾P值<0.05被认为具有统计学意义。在此基础上，我们分别构建了生存预测的新特征，并通过两个数据集中的一致性指数（C指数）、校准和受试者工作特征（ROC）曲线验证了特征的有效性。
LCR、淋巴管浸润（LVI）、孕激素受体（PR）状态和Ki67指数是OS的独立预后因素。LCR和LVI也与DFS相关。高LCR与更好的OS和DFS相关。我们基于这些独立预后因素构建了预测特征并计算了风险评分。训练集中风险评分较高的患者预后明显较差（<0.001）。该特征具有出色的区分能力，训练集和验证集中OS的C指数分别为0.785 [95%置信区间（CI）：0.713 - 0.857]和0.750（95% CI：0.669 - 0.832）。时间ROC曲线也表明该特征预测准确。
LCR是早期BC中OS和DFS 的重要预后预测指标。基于LCR的预后特征可能是个体化治疗指导的有用工具。
