Uncommon_Mutations_Database

On March 16, 2020 Boehringer Ingelheim reported the launch of a patient outcomes database which will provide clinicians with important information when considering optimal treatment for non-small cell lung cancer (NSCLC) patients harboring specific uncommon epidermal growth factor receptor (EGFR) mutations (Press release, Boehringer Ingelheim, MAR 16, 2020, View Source [SID1234555568]). The real-world database includes all available data from such patients treated with afatinib.

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The data from 693 NSCLC patients published in the Journal of Thoracic Oncology (JTO) support the use of afatinib against the most prevalent uncommon EGFR mutations. In patients who had not previously received any form of EGFR tyrosine kinase inhibitor (TKI), treatment with afatinib demonstrated activity against major uncommon mutations (median time-to-treatment-failure (TTF): 10.8 months; 95% CI: 8.1–16.6; overall response rate (ORR): 60.0%), compound mutations (14.7 months; 95% CI: 6.8–18.5; 77.1%), other uncommon mutations (4.5 months; 95% CI: 2.9–9.7; 65.2%). Median duration of response (DoR) was 17.1, 16.6, and 9.0 months, respectively. Outcome in patients with exon 20 insertions was heterogeneous with a TTF of 4.2 months (95% CI: 2.8 – 5.3) with 3% having complete remissions and 5% being on treatment for more than 3 years.i

The pooled analysis was based on global clinical outcome data from 693 patients with NSCLC driven by uncommon EGFR mutations, who received afatinib as part of clinical trials, compassionate use or expanded access programs, phase IIIb trials, non-interventional trials and case series/studies in more than 40 countries. The mutations included: (29% major uncommon EGFR mutations [G719X, L861Q and S768I], 25% T790M, 21% exon 20 insertion, 13% other uncommon EGFR mutation, 12% compound mutation) which had been available via the new searchable database www.uncommonEGFRmutations.com.

This new data supports previous findings from a post-hoc analysis of the LUX-Lung trials, which demonstrated significant clinical activity of afatinib against the most prevalent uncommon mutations.ii Of the EGFR TKI prospective randomized trials to date, only IPASS (gefitinib),iii NEJ002 (gefitinib),iv and LUX-Lung 2, 3 and 6 (afatinib),v, vi included patients with uncommon EGFR mutations, meaning clinical data for other EGFR TKIs against uncommon mutations is lacking. While other TKIs have shown efficacy in a first-line setting in patients with NSCLC and common mutations (Del19, L858R), their clinical activity against uncommon mutations remains largely unknown.

Lead author Dr James Chih-Hsin Yang from the Department of Oncology at the National Taiwan University Hospital said, "The relative scarcity of prospective clinical data concerning the up to 23% of NSCLC EGFR M+ cases that fall into the ‘uncommon mutation’ category can compromise effective treatment decisions. The results from this pooled analysis, alongside the post-hoc LUX-Lung results, should support afatinib as the first-choice treatment for NSCLC patients with uncommon EGFR mutations. Additionally, the uncommon mutation database, which is going to be continuously updated as new data becomes available, will be an invaluable clinical decision-making tool for the treatment of this patient sub-population moving forward."

"The value and the richness of these new combined data establishes afatinib as the meaningful treatment option for patients with uncommon EGFR mutation in addition to its recognized role as first-line therapy for common EGFR mutations," said Dr Victoria Zazulina, Global Head of Oncology, Medicine, at Boehringer Ingelheim. "We hope that this new searchable database will inform clinical decisions and therapeutic choices for patients with various types of uncommon EGFR mutations."

The uncommon mutation data summarized within the paper are available in a searchable online database at www.uncommonEGFRmutations.com. The database can be accessed globally by clinicians and non-clinicians alike and will be regularly updated as new data becomes available.

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