Background: Next-generation anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors (TKIs) (alectinib, brigatinib, and lorlatinib) demonstrate superior progression-free survival (PFS) over chemotherapy or crizotinib as first-line (1L) treatment of ALK-positive advanced non-smallcell lung cancer (NSCLC).
Methods: We conducted network meta-analyses (NMAs) comparing the relative efficacy of lorlatinib with other ALK TKIs in this indication. Evidence identified from a systematic literature review and subsequent updates formed the basis of our evidence. The primary analysis investigated PFS by independent review committee (IRC) in the intent-to-treat (ITT) population. Secondary outcomes included PFS among subgroups, intracranial time to progression (IC TTP), adverse events, and discontinuation due to adverse events. For each of the outcomes, Bayesian proportional hazards NMAs estimated the relative treatment effects. Additionally, we compared the design and results of eight published NMAs conducted for 1L ALK + advanced NSCLC to date.
Results: We formed a network of 10 trials, allowing indirect treatment comparisons. Two trials directly compared alectinib (600 mg twice daily) to crizotinib and one trial directly compared lorlatinib to crizotinib. The results of the NMA show that the hazard ratios (95 % credible interval [CrI]) for ITT PFS IRC were 0.61 (95 % CrI: 0.39, 0.97) when comparing lorlatinib with alectinib (600 mg twice daily) and 0.57 (95 % CrI: 0.35, 0.93) when comparing lorlatinib with brigatinib. In the review of published NMAs, HRs for lorlatinib versus alectinib (600 mg twice daily) and brigatinib were compared. This comparison confirmed that each published NMA yielded similar results.
Conclusions: Our NMA analysis adds to existing findings and supplements data gaps from other published NMAs. Findings from eight published NMAs consistently supported lorlatinib as a clinically effective 1L treatment for ALK + advanced NSCLC patients compared to other TKIs.
Keywords: ALK-positive; First-line; Lorlatinib; NSCLC; Network meta-analysis.
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