Risk stratification of EGFR(+) lung cancer diagnosed with panel-based next-generation sequencing

Lung Cancer

Lung Cancer. 2020 Aug 22;148:105-112. doi: 10.1016/j.lungcan.2020.08.007. Online ahead of print.


OBJECTIVE: Panel-based next-generation sequencing (NGS) is increasingly used for the diagnosis of EGFR-mutated non-small-cell lung cancer (NSCLC) and could improve risk assessment in combination with clinical parameters.

MATERIALS AND METHODS: To this end, we retrospectively analyzed the outcome of 400 tyrosine kinase inhibitor (TKI)-treated EGFR+ NSCLC patients with validation of results in an independent cohort (n = 130).

RESULTS: EGFR alterations other than exon 19 deletions (non-del19), TP53 co-mutations, and brain metastases at baseline showed independent associations of similar strengths with progression-free (PFS hazard ratios [HR] 2.1-2.3) and overall survival (OS HR 1.7-2.2), in combination defining patient subgroups with distinct outcome (EGFR+NSCLC risk Score, "ENS", p < 0.001). Co-mutations beyond TP53 were rarely detected by our multigene panel (<5%) and not associated with clinical endpoints. Smoking did not affect outcome independently, but was associated with non-del19 EGFR mutations (p < 0.05) and comorbidities (p < 0.001). Laboratory parameters, like the blood lymphocyte-to-neutrophil ratio and serum LDH, correlated with the metastatic pattern (p < 0.01), but had no independent prognostic value. Reduced ECOG performance status (PS) was associated with comorbidities (p < 0.05) and shorter OS (p < 0.05), but preserved TKI efficacy. Non-adenocarcinoma histology was also associated with shorter OS (p < 0.05), but rare (2-3 %). The ECOG PS and non-adenocarcinoma histology could not be validated in our independent cohort, and did not increase the range of prognostication alongside the ENS.

CONCLUSIONS: EGFR variant, TP53 status and brain metastases predict TKI efficacy and survival in EGFR+ NSCLC irrespective of other currently available parameters ("ENS"). Together, they constitute a practical and reproducible approach for risk stratification of newly diagnosed metastatic EGFR+ NSCLC.