Rao Joseph Sushil, Hanumappa Harish Kumar, Joseph Elvis Peter, Chowdappa Raghunandan Gorantlu, Ramesh Rakesh
Department of Surgical Oncology, St. John's National Academy of Health Sciences, Bangalore, India.
Indian J Surg Oncol. 2019 Sep;10(3):454-459. doi: 10.1007/s13193-019-00944-3. Epub 2019 Jun 15.
Neutrophil-Lymphocyte Ratio (NLR) provides an understanding of the systemic inflammatory conditions. NLR plays an important role as a predictor of mortality in breast and other malignancies. The application of NLR to predict prognosis of Locally Advanced Breast Cancer (LABC) has not been well developed. In this retrospective study, we establish a relationship of pre-treatment NLR with the Pathological Complete Response (pCR) in LABC patients to enhance decision-making and treatment protocols. Data of women diagnosed with carcinoma breast between January 2015 and December 2017 was retrieved from hospital records of a tertiary medical centre in Bangalore, India, after obtaining institutional ethical clearance. LABC patients were categorized into pCR(+) and pCR(-). NLR was calculated and divided into quartiles. The cutoff NLR was determined using the Receiver Operating Characteristic (ROC) curve. Statistical analysis was performed on 119 LABC patients, of which 25 (21%) achieved pCR. Oestrogen Receptor (ER) positivity was significantly lower in pCR(+) than in pCR(-) ( = 0.012). NLR of 2.46 (AUC, 0.744; 95% CI [0.201-0.584]; = 0.056) was considered the optimum cutoff for pCR(+). A sensitivity of 54%, specificity of 8%, positive predictive value of 1% and high Negative Predictive Value (NPV) of 84% was achieved in the study. A relationship between pCR and the pre-treatment NLR determined a significantly high NPV. Poor pCR in luminal A/B subtype presents with elevated NLR. Therefore, in luminal type A/B (ER- and PR-positive) with elevated NLR (poor outcome) and low pCR (poor response to NACT), the decision of eliminating NACT could be considered, thereby recommending surgical intervention.
中性粒细胞与淋巴细胞比值(NLR)有助于了解全身炎症状况。NLR作为乳腺癌及其他恶性肿瘤死亡率的预测指标发挥着重要作用。NLR在预测局部晚期乳腺癌(LABC)预后方面的应用尚未得到充分发展。在这项回顾性研究中,我们建立了LABC患者治疗前NLR与病理完全缓解(pCR)之间的关系,以改善决策制定和治疗方案。在获得机构伦理批准后,从印度班加罗尔一家三级医疗中心的医院记录中检索了2015年1月至2017年12月期间被诊断为乳腺癌的女性数据。LABC患者被分为pCR(+)和pCR(-)两组。计算NLR并将其分为四分位数。使用受试者操作特征(ROC)曲线确定NLR的临界值。对119例LABC患者进行了统计分析,其中25例(21%)实现了pCR。pCR(+)组的雌激素受体(ER)阳性率显著低于pCR(-)组(P = 0.012)。NLR为2.46(AUC,0.744;95%CI[0.201 - 0.584];P = 0.056)被认为是pCR(+)的最佳临界值。该研究实现了54%的灵敏度、8%的特异性、1%的阳性预测值和84%的高阴性预测值(NPV)。pCR与治疗前NLR之间的关系确定了显著较高的NPV。管腔A/B亚型中pCR较差表现为NLR升高。因此,对于管腔A型/B型(ER和PR阳性)且NLR升高(预后不良)和pCR较低(对新辅助化疗反应较差)的患者,可以考虑取消新辅助化疗的决定,从而建议进行手术干预。