Hua Xin, Long Zhi-Qing, Huang Xin, Deng Jia-Peng, He Zhen-Yu, Guo Ling, Zhang Wen-Wen, Lin Huan-Xin
Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Department of Radiotherapy, Sun Yat-sen University Cancer Center, Guangzhou, China.
Front Oncol. 2020 Jan 30;9:1562. doi: 10.3389/fonc.2019.01562. eCollection 2019.
To investigate the significance of the prognostic nutrition index (PNI) as a predictor of survival and guide for treating T1-2N1 breast cancer. Patients with T1-2N1 breast cancer ( = 380) who underwent a mastectomy at our center were studied. PNI was calculated as 10 × serum albumin (g/dl) + 0.005 × total lymphocyte count (per mm). The cutoff for the PNI was calculated using the time-dependent receiver operating characteristic (ROC) curve analysis by overall survival (OS) prediction. The associations between the PNI and the clinicopathologic characteristics were analyzed using Pearson's χ test. Survival curves were calculated using the Kaplan-Meier method. Univariate and multivariate analyses were performed using the Cox proportional hazards model. Subgroup analyses of patients with low PNI value (≤52.0) and high PNI value (>52.0) showed that a high PNI was significantly associated with HER2 status, the neutrophil-lymphocyte ratio (NLR), the monocyte-lymphocyte ratio (MLR), and KI 67 status. The OS of patients with a high PNI was significantly better than that of patients with a low PNI. We then conducted subgroup analyses based on PNI and radiotherapy. Among patients who received radiotherapy, the OS of those with a high PNI was significantly better than that of patients with a low PNI. Among patients with a high PNI, the OS of those who received radiotherapy was better than that of the patients who did not receive radiotherapy. However, among the patients with a low PNI, the OS of those who received radiation was worse than that of patients who did not receive radiotherapy. The Kaplan-Meier survival analysis and the multivariate analysis of patients with T1-2N1 breast cancer who received radiotherapy showed PNI independently predicted OS. The preoperative PNI may be a reliable predictor of OS of patients with operable T1-2N1 breast cancer, with the capacity to provide a personalized prognosis and facilitate the development of clinical treatment strategies. However, radiotherapy did not achieve satisfactory outcomes in patients with PNI ≤52.0; thus, further studies on treatment optimization are needed.
为研究预后营养指数(PNI)作为T1-2N1期乳腺癌生存预测指标及治疗指导的意义。对在本中心接受乳房切除术的380例T1-2N1期乳腺癌患者进行了研究。PNI的计算方法为10×血清白蛋白(g/dl)+0.005×总淋巴细胞计数(每立方毫米)。PNI的临界值通过生存时间依赖的受试者工作特征(ROC)曲线分析预测总生存期(OS)来计算。使用Pearson卡方检验分析PNI与临床病理特征之间的关联。采用Kaplan-Meier法计算生存曲线。使用Cox比例风险模型进行单因素和多因素分析。对PNI值低(≤52.0)和PNI值高(>52.0)的患者进行亚组分析,结果显示PNI高与HER2状态、中性粒细胞与淋巴细胞比值(NLR)、单核细胞与淋巴细胞比值(MLR)及Ki-67状态显著相关。PNI高的患者的总生存期明显优于PNI低的患者。然后我们基于PNI和放疗进行了亚组分析。在接受放疗的患者中,PNI高的患者的总生存期明显优于PNI低的患者。在PNI高的患者中,接受放疗的患者的总生存期优于未接受放疗的患者。然而,在PNI低的患者中,接受放疗的患者的总生存期比未接受放疗的患者更差。对接受放疗的T1-2N1期乳腺癌患者进行的Kaplan-Meier生存分析和多因素分析显示,PNI可独立预测总生存期。术前PNI可能是可手术的T1-2N1期乳腺癌患者总生存期的可靠预测指标,具有提供个性化预后及促进临床治疗策略制定的能力。然而,放疗在PNI≤52.0的患者中未取得满意疗效;因此,需要进一步研究优化治疗方案。