Mariean Claudia Raluca, Tiucă Oana Mirela, Mariean Alexandru, Szekely Tiberiu-Bogdan, Niculescu Raluca, Sabau Adrian Horatiu, Al-Akel Cristina Flavia, Cotoi Ovidiu Simion
Doctoral School of Medicine and Pharmacy, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, 540142 Targu Mures, Romania.
Pathophysiology Department, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, 540142 Targu Mures, Romania.
J Clin Med. 2025 Apr 28;14(9):3038. doi: 10.3390/jcm14093038.
: The analysis of the complete blood count (CBC)-derived inflammatory indexes across different histological subtypes of lung cancer supports the early detection of tumor-induced inflammation and has a good predictive value for severity in cancer patients. The main objective of this article was to assess the variations in CBC-derived inflammatory markers across different histologic subtypes of lung cancer, with the final goal of identifying specific predictors of severity for each histologic subtype of lung cancer. : We conducted a retrospective descriptive study that included 202 patients diagnosed with lung carcinoma at the Clinical County Hospital Mureș. The analyzed parameters were as follows: the histological type, the stage of the tumor, patients' general data, and associated comorbidities. In addition, nine CBC-derived inflammatory indexes, like the neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (d-NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), eosinophil-to-neutrophil ratio (ENR), eosinophil-to-monocyte ratio (EMR), systemic inflammatory index (SII), systemic inflammatory response index (SIRI), and aggregate index of systemic inflammation (AISI), were analyzed as predictors of severity and correlated with histologic findings. : The predictors of severity differed across the histologic subtypes. SIRI, d-NLR, and age were predictors of severity in adenocarcinoma patients, while the d-NLR, ENR, leukocyte, and neutrophil count predicted severity in squamous cell carcinoma. For SCLC patients, AISI, SIRI, SII, d-NLR, EMR, ENR, MLR, leukocyte count, lymphocyte count, neutrophil count, platelets count, COPD, smoking, and male gender were predictors for severity. Understanding the complexity and variations in the inflammatory response across different histologic types of lung cancer can personalize treatment regimens and target specific abnormal cellular lines, thus improving the outcome of this highly deadly condition.
对不同组织学亚型肺癌患者全血细胞计数（CBC）衍生的炎症指标进行分析，有助于早期发现肿瘤诱导的炎症，对癌症患者的病情严重程度具有良好的预测价值。本文的主要目的是评估不同组织学亚型肺癌患者CBC衍生炎症标志物的变化，最终目标是确定每种组织学亚型肺癌严重程度的特定预测指标。我们进行了一项回顾性描述性研究，纳入了202例在穆列什县临床医院被诊断为肺癌的患者。分析的参数如下：组织学类型、肿瘤分期、患者的一般资料以及相关合并症。此外，还分析了9个CBC衍生的炎症指标，如中性粒细胞与淋巴细胞比值（NLR）、衍生中性粒细胞与淋巴细胞比值（d-NLR）、单核细胞与淋巴细胞比值（MLR）、血小板与淋巴细胞比值（PLR）、嗜酸性粒细胞与中性粒细胞比值（ENR）、嗜酸性粒细胞与单核细胞比值（EMR）、全身炎症指数（SII）、全身炎症反应指数（SIRI）和全身炎症聚集指数（AISI），作为病情严重程度的预测指标，并与组织学结果进行关联分析。不同组织学亚型的病情严重程度预测指标有所不同。SIRI、d-NLR和年龄是腺癌患者病情严重程度的预测指标，而d-NLR、ENR、白细胞计数和中性粒细胞计数可预测鳞状细胞癌的严重程度。对于小细胞肺癌患者，AISI、SIRI、SII、d-NLR、EMR、ENR、MLR、白细胞计数、淋巴细胞计数、中性粒细胞计数、血小板计数、慢性阻塞性肺疾病（COPD）、吸烟和男性性别是病情严重程度的预测指标。了解不同组织学类型肺癌炎症反应的复杂性和变异性，可为制定个性化治疗方案提供依据，并针对特定异常细胞系进行治疗，从而改善这种高致死性疾病的治疗效果。
