Dong Juanjuan, Tong Sihao, Shi Xianfeng, Wang Chao, Xiao Xin, Ji Wenping, Sun Yimian
Department of Oncology, Anhui Medical University-Affiliated Chaohu Hospital, Hefei 238000, Anhui, People's Republic of China.
Department of Education, Anhui Medical University-Affiliated Chaohu Hospital, Hefei 238000, Anhui, People's Republic of China.
Cancer Manag Res. 2021 Jan 5;12:13607-13616. doi: 10.2147/CMAR.S285121. eCollection 2020.
Lung cancer is the leading cause of cancer-related mortality and non-small-cell lung cancer (NSCLC) accounts for 80-90% of all lung cancers. However, biomarkers to predict the prognosis of NSCLC patients upon treatment with tyrosine kinase inhibitors remain unreliable. Different types of EGFR mutations can help predict the efficacy of tyrosine kinase inhibitor (TKI) treatment among advanced NSCLC patients harboring them. However, survival varies among individuals harboring the same mutation after targeted therapy. This study aimed to investigate the value of serum tumor markers (STMs) and EGFR mutations in the prognostic assessment of progression-free survival (PFS) in advanced-stage EGFR-mutated NSCLC.
A retrospective clinical review was performed on 81 NSCLC patients harboring EGFR mutations and for whom STM data, measured before commencement of first-line treatment with tyrosine kinase inhibitors, were available. Associations among EGFR mutations, STMs, baseline clinical features, and PFS were analyzed. Kaplan-Meier method was used to plot survival curves, and Cox logistic regression models were used to identify independent prognostic factors.
Exon 19 deletion (19-del) in EGFR, negative neuron-specific enolase (NSE), negative pro-gastrin-releasing peptide precursor (ProGRP) value, and "never smoking" status were significantly associated with improved PFS (P=0.007, P=0.001, P<0.001, and P<0.001, respectively). Multivariate Cox analysis revealed that 19-del in EGFR, never smoking, negative ProGRP value, and negative NSE were independent predictors of PFS.
This study demonstrated that 19-del in EGFR may predict longer PFS in advanced-stage EGFR-mutated NSCLC treated with TKIs. Additionally, longer PFS can be predicted by serum tumor markers with negative ProGRP value, negative NSE value before initial treatment, and "never smoking." Therefore, in addition to the EGFR mutation type and smoking status, physicians can also prognosticate the PFS of tyrosine kinase inhibitors treatment according to the values of ProGRP and NSE before treatment.
肺癌是癌症相关死亡的主要原因，非小细胞肺癌（NSCLC）占所有肺癌的80 - 90%。然而，预测NSCLC患者接受酪氨酸激酶抑制剂治疗后预后的生物标志物仍然不可靠。不同类型的表皮生长因子受体（EGFR）突变有助于预测携带这些突变的晚期NSCLC患者接受酪氨酸激酶抑制剂（TKI）治疗的疗效。然而，靶向治疗后，携带相同突变的个体生存期存在差异。本研究旨在探讨血清肿瘤标志物（STMs）和EGFR突变在晚期EGFR突变型NSCLC无进展生存期（PFS）预后评估中的价值。
对81例携带EGFR突变的NSCLC患者进行回顾性临床分析，这些患者在开始一线酪氨酸激酶抑制剂治疗前有可用的STM数据。分析EGFR突变、STMs、基线临床特征和PFS之间的关联。采用Kaplan-Meier法绘制生存曲线，Cox逻辑回归模型用于识别独立预后因素。
EGFR基因第19外显子缺失（19-del）、神经元特异性烯醇化酶（NSE）阴性、胃泌素释放肽前体（ProGRP）值阴性以及“从不吸烟”状态与PFS改善显著相关（P分别为0.007、0.001、<0.001和<0.001）。多因素Cox分析显示，EGFR基因19-del、从不吸烟、ProGRP值阴性和NSE阴性是PFS的独立预测因素。
本研究表明，EGFR基因19-del可能预测晚期EGFR突变型NSCLC患者接受TKI治疗后的PFS更长。此外，ProGRP值阴性、初始治疗前NSE值阴性的血清肿瘤标志物以及“从不吸烟”可预测更长的PFS。因此，除了EGFR突变类型和吸烟状态外，医生还可根据治疗前ProGRP和NSE的值预测酪氨酸激酶抑制剂治疗NSCLC患者的PFS。
