Department of Medical Oncology, School of Medicine, Bursa Uludag University, 16059, Gorukle, Nilufer, Bursa, Turkey.
Department of Pathology, School of Medicine, Bursa Uludag University, Bursa, Turkey.
Sci Rep. 2021 Jul 19;11(1):14662. doi: 10.1038/s41598-021-94184-7.
Blood-based biomarkers reflect systemic inflammation status and have prognostic and predictive value in solid malignancies. As a recently defined biomarker, Pan-Immune-Inflammation-Value (PIV) integrates different peripheral blood cell subpopulations. This retrospective study of collected data aimed to assess whether PIV may predict the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in Turkish women with breast cancer. The study consisted of 743 patients with breast cancer who were scheduled to undergo NAC before attempting cytoreductive surgery. A pre-treatment complete blood count was obtained in the two weeks preceding NAC, and blood-based biomarkers were calculated from absolute counts of relevant cell populations. The pCR was defined as the absence of tumor cells in both the mastectomy specimen and lymph nodes. Secondary outcome measures included disease-free survival (DFS) and overall survival (OS). One hundred seven patients (14.4%) had pCR. In receiver operating characteristic analysis, optimal cut-off values for the neutrophile-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte (PLR), PIV, and Ki-67 index were determined as ≥ 2.34, ≥ 0.22, ≥ 131.8, ≥ 306.4, and ≥ 27, respectively. The clinical tumor (T) stage, NLR, MLR, PLR, PIV, estrogen receptor (ER) status, human epidermal growth factor receptor-2 (HER-2) status, and Ki-67 index were significantly associated with NAC response in univariate analyses. However, multivariate analysis revealed that the clinical T stage, PIV, ER status, HER-2 status, and Ki-67 index were independent predictors for pCR. Moreover, the low PIV group patients had significantly better DFS and OS than those in the high PIV group (p = 0.034, p = 0.028, respectively). Based on our results, pre-treatment PIV seems as a predictor for pCR and survival, outperforming NLR, MLR, PLR in predicting pCR in Turkish women with breast cancer who received NAC. However, further studies are needed to confirm our findings.
基于血液的生物标志物反映了全身炎症状态,并且在实体恶性肿瘤中具有预后和预测价值。作为最近定义的生物标志物,全免疫炎症值(PIV)整合了不同的外周血细胞亚群。本研究回顾性收集了数据,旨在评估 PIV 是否可以预测土耳其乳腺癌女性接受新辅助化疗(NAC)后的病理完全缓解(pCR)。该研究纳入了 743 名计划接受 NAC 后再进行细胞减灭术的乳腺癌患者。在 NAC 前两周内获得了预处理的全血细胞计数,并根据相关细胞群的绝对计数计算了基于血液的生物标志物。pCR 定义为乳房切除术标本和淋巴结中均无肿瘤细胞。次要终点包括无病生存期(DFS)和总生存期(OS)。107 名患者(14.4%)达到了 pCR。在接受者操作特征分析中,确定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)、血小板与淋巴细胞比值(PLR)、PIV 和 Ki-67 指数的最佳截断值分别为≥2.34、≥0.22、≥131.8、≥306.4 和≥27。临床肿瘤(T)分期、NLR、MLR、PLR、PIV、雌激素受体(ER)状态、人表皮生长因子受体 2(HER-2)状态和 Ki-67 指数在单因素分析中与 NAC 反应显著相关。然而,多因素分析显示,临床 T 分期、PIV、ER 状态、HER-2 状态和 Ki-67 指数是 pCR 的独立预测因子。此外,低 PIV 组患者的 DFS 和 OS 明显优于高 PIV 组(p=0.034,p=0.028)。根据我们的结果,治疗前 PIV 似乎是 pCR 和生存的预测因子,在预测接受 NAC 的土耳其乳腺癌女性 pCR 方面优于 NLR、MLR 和 PLR。然而,还需要进一步的研究来证实我们的发现。