Safety profile of FLT3 inhibitors in acute myeloid leukemia: a systematic review and meta-analysis of adverse events
Abstract
Acute myeloid leukemia (AML) is the most common acute leukemia in adults. Approximately 30% of patients present alterations in the FMS-like receptor tyrosine kinase 3 (FLT3) gene, which are associated with poor prognosis. FLT3 inhibitors - midostaurin (first-generation), gilteritinib and quizartinib (second-generation) - have been developed to block FLT3 activation. Given the need of optimizing treatment in FLT3-mutated AML, we conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) to compare the safety profiles of FLT3 inhibitors. Following the PRISMA statement, we searched Embase, MEDLINE and Cochrane Library. The Cochrane Risk of Bias Tool for RCTs was used for quality assessment. Of 2132 references, seven RCTs, involving 2409 adult patients, met inclusion criteria: quizartinib and midostaurin in two trials each and gilteritinib in three. The most frequently reported adverse events (AEs) were classified under the System Organ Class (SOC) Blood and lymphatic system disorders (N = 5474, 58.4% of them related to FLT3 inhibitors). The most frequently observed non-hematological AEs were gastrointestinal disorders, pyrexia, elevated ALT/AST and headache. FLT3 inhibitors are not associated with a significant increase in the risk of AEs compared to standard treatments. No meaningful differences in AE risk were observed among the three drugs. The only exception was an higher risk of ALT increased with gilteritinib (RR = 2.40, 95% CI: 1.16-4.95).…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 5,474 participants or records.
Read the paper
Related studies
- In silico toxicology protocols
- QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules
- Quantum Informed Machine-Learning Potentials for Molecular Dynamics Simulations of CO2's Chemisorption and Diffusion in Mg-MOF-74
- In-silico strategies in nano-drug design: Bridging nanomaterials and pharmacological applications
- mRNA codon optimization with quantum computers
- The computational power of the human brain
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.