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Real-world evidence for patients with advanced <i>EGFR</i>-mutated non-small cell lung cancer (NSCLC) in Canada is limited. This study’s objective was to use previously validated DARWEN^TM artificial intelligence (AI) to extract data from electronic heath records of patients with non-squamous NSCLC at University Health Network (UHN) to describe <i>EGFR</i> mutation prevalence, treatment patterns, and outcomes. Of 2154 patients with NSCLC, 613 had advanced disease. Of these, 136 (22%) had common sensitizing <i>EGFR</i> mutations (c<i>EGFR</i>m; ex19del, L858R), 8 (1%) had exon 20 insertions (ex20ins), and 338 (55%) had <i>EGFR</i> wild type. One-year overall survival (OS) (95% CI) for patients with c<i>EGFR</i>m, ex20ins, and <i>EGFR</i> wild type tumours was 88% (83, 94), 100% (100, 100), and 59% (53, 65), respectively. In total, 38% patients with ex20ins received experimental ex20ins targeting treatment as their first-line therapy. A total of 57 patients (36%) with c<i>EGFR</i>m received osimertinib as their first-line treatment, and 61 (39%) received it as their second-line treatment. One-year OS (95% CI) following the discontinuation of osimertinib was 35% (17, 75) post-first-line and 20% (9, 44) post-second-line. In this real-world AI-generated dataset, survival post-osimertinib was poor in patients with c<i>EGFR</i> mutations. Patients with ex20ins in this cohort had improved outcomes, possibly due to ex20ins targeting treatment, highlighting the need for more effective treatments for patients with advanced <i>EGFR</i>m NSCLC.