Prognostic Value of Neurotrophic Tyrosine Receptor Kinase Gene Fusions in Solid Tumors for Overall Survival: A Systematic Review and Meta-Analysis

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Abstract
PURPOSE: Evidence suggests that neurotrophic tyrosine receptor kinase ( NTRK) gene fusions in solid tumors are predictive biomarkers for targeted inhibition across a number of adult and pediatric tumor types. However, despite robust clinical response to tyrosine receptor kinase (TRK) inhibitors, the natural history and prognostic implications of NTRK fusions in solid tumors are poorly understood. It is important to evaluate their prognostic significance on survival to provide some context to the clinical effectiveness observed in clinical trials of TRK-targeted therapies. METHODS: A systematic literature review was conducted in Medline, Embase, Cochrane, and PubMed to identify studies comparing the overall survival (OS) of patients with NTRK fusion–positive ( NTRK+) versus NTRK fusion–negative ( NTRK–) tumors. Five retrospective matched case-control studies published before 11 August 2022 were assessed for inclusion, and three were selected for the meta-analysis (sample size: 69 NTRK+, 444 NTRK–). Risk of bias was assessed using the Risk of Bias Assessment tool for Non-randomized Studies tool. The pooled hazard ratio (HR) was estimated using a Bayesian random-effects model. RESULTS: In the meta-analysis, the median follow-up ranged from 2 to 14 years and the median OS was between 10.1 and 12.7 months (where reported). Comparing patients with tumors NTRK+ and NTRK–, the pooled HR estimate for OS was 1.51 (95% credible interval, 1.01 to 2.29). The patients analyzed had no previous or current exposure to TRK inhibitors. CONCLUSION: In patients not treated with TRK inhibitor therapies, those with NTRK+ solid tumors have a 50% increased risk of mortality within 10 years from diagnosis or the start of standard therapy compared with those with NTRK– status. Although this is the most robust estimate of the comparative survival rate to date, further studies are required to reduce uncertainty.

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