Clinical and molecular feature-based nomogram model for predicting benefit from bevacizumab combined with first-generation EGFR-tyrosine kinase inhibitor (TKI) in EGFR-mutant advanced NSCLC

• Published in: BMC medicine 2021-10, Vol.19 (1), p.1-245, Article 245
• Main Authors: Zhang, Yongchang, Zeng, Liang, Zhang, Xiangyu, Li, Yizhi, Liu, Lingli, Xu, Qinqin, Yang, Haiyan, Jiang, Wenjuan, Lizaso, Analyn, Qiu, Luting, Hou, Ting, Liu, Jun, Peng, Ling, Yang, Nong
• Format: Article
• Language: English
• Subjects: Advanced NSCLC; Bevacizumab; Bevacizumab combined with EGFR-TKI; Biopsy; Cancer therapies; Clinical features; Drug therapy; Enzyme inhibitors; Epidermal growth factor; Epidermal growth factor receptors; Genes; Genetic aspects; Genomes; Growth factors; Kinases; Lung cancer; Lung cancer, Non-small cell; Medical prognosis; Metastases; Metastasis; Molecular features; Monoclonal antibodies; Mutants; Mutation; Nomograms; Nomography (Mathematics); Non-small cell lung carcinoma; Patient outcomes; Patients; Prediction Model; Small cell lung carcinoma; Survival; Survival analysis; Targeted cancer therapy; Tumor suppressor genes; Tumors; Tyrosine; Tyrosine kinase inhibitors; Vascular endothelial growth factor
• ISSN: 1741-7015; 1741-7015
• DOI: 10.1186/s12916-021-02118-x

Background The combination of bevacizumab and epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) could prolong progression-free survival (PFS) in patients with EGFR-mutant advanced non-small-cell lung cancer (NSCLC). Our study investigated the clinical and molecular factors that affect the efficacy of first-generation EGFR-TKI with or without bevacizumab and identify the subset of patients who can benefit from combination therapy. Methods Our study included 318 patients with EGFR-mutant locally advanced/advanced NSCLC treated with either first-generation EGFR-TKI combined with bevacizumab (A+T; n = 159) or EGFR-TKI monotherapy (T; n = 159). Two nomogram models to predict PFS and overall survival (OS), respectively, were constructed using two factors that impact EGFR-TKI efficacy: metastatic site and presence of concurrent mutations. The study cohort was stratified into 2 cohorts for training (n = 176) and validation (n = 142) of the nomogram model. Using the median score from the nomogram, the patients were stratified into two groups to analyze their survival outcome. Results The A+T group had significantly longer PFS (14.0 vs. 10.5 months; p < 0.001) and OS (37.0 vs. 26.0 months; p = 0.042) than the T group. Among the patients with concurrent mutations in tumor suppressor genes, those in the A+T group had significantly longer PFS and OS than the T group (PFS 14.5 vs. 8.0 months, p < 0.001; OS 39.0 vs. 20.0 months, p = 0.003). The higher scores from the nomograms were associated with the presence of brain/liver/pleural metastasis or concomitant gene mutations, which indicated a higher likelihood of shorter PFS and OS. The validation of the nomogram revealed that patients with lower scores had significantly longer PFS for the T group than those with higher scores (15.0 vs. 9.0 months, p = 0.002), but not for the A+T group (15.9 vs. 13.9 months, p = 0.256). Conclusions Using a nomogram, our study demonstrated that the addition of bevacizumab may enhance the therapeutic effectiveness of EGFR-TKI by overcoming the negative impact of certain clinical and molecular factors on the efficacy of EGFR-TKI. Keywords: Clinical features, Molecular features, Prediction Model, Bevacizumab combined with EGFR-TKI, Advanced NSCLC