AUTHORS
Meenakkshy Manoharan, MD, Rebecca Irlmeier, MS2, Erica N Lamkin, M.Sc.3, Matthew H. Wayne4, Sangeetha Venugopal, MD, MS5, Fnu Alnoor, MD6, Jill Lykon, PharmD7, Ellen Madarang, PharmD8, Justin M Watts, MD9, Fei Ye, PhD, MSPH, FASA10, Justin Taylor, MD11
AFFILIATIONS
1 University of Miami Miller School of Medicine, Miami, Florida, United States
2 University of Miami Miller School of Medicine, Miami, Florida, United States, University of Miami Miller School of Medicine, Miami, Florida, United States
3 University of Miami Miller School of Medicine, Miami, Florida, United States
4 Medical Impact Ventures, Austin, Texas, United States
5 University of Miami Miller School of Medicine, Miami, Florida, United States, University of Miami Miller School of Medicine, Miami, Florida, United States
6 University of Miami Miller School of Medicine, Miami, Florida, United States
7 University of Miami Miller School of Medicine, Miami, Florida, United States
8 University of Miami Miller School of Medicine, Miami, Florida, United States
9 University of Miami Miller School of Medicine, Miami, Florida, United States
10 University of Miami Miller School of Medicine, Miami, Florida, United States, University of Miami Miller School of Medicine, Miami, Florida, United States
11 University of Miami Miller School of Medicine, Miami, Florida, United States, University of Miami Miller School of Medicine, Miami, Florida, United States
ABSTRACT
Background
FLT3 mutations are among the most clinically actionable genomic alterations in acute myeloid leukemia (AML), and rapid molecular identification is essential for timely incorporation of FLT3 inhibitors into frontline therapy. Despite guideline recommendations supporting molecularly informed treatment selection, real-world implementation of FLT3 testing workflows, turnaround times (TAT), and targeted therapy delivery varies across practice settings. Delays in molecular testing or treatment initiation may compromise optimal care. We evaluated real-world FLT3 testing practices, TAT, treatment patterns, and clinical outcomes among patients with newly diagnosed AML treated within an integrated academic-community health system.
Methods
We performed a retrospective analysis of 100 adults with newly diagnosed AML treated at a tertiary academic cancer center and affiliated community oncology practices from 2020-2026. Clinical characteristics, FLT3 testing practices, molecular turnaround times, FLT3 mutation status, treatment regimens, FLT3 inhibitor utilization, and clinical outcomes were collected. Overall survival (OS), relapse-free survival (RFS), and event-free survival (EFS) were estimated using Kaplan-Meier methods. Outcomes were compared by practice location, FLT3 testing TAT (≤7 days vs >7 days), and time from FLT3 result availability to initiation of FLT3-targeted therapy using log-rank tests. Multivariable Cox proportional hazards regression models evaluated factors associated with OS, RFS, and EFS, adjusting for FLT3 testing TAT, time from AML diagnosis to FLT3 result availability, practice location, age, and ECOG performance status. Interrupted time-series analysis evaluated the impact of implementing an in-house NGS panel.
Results
Among 100 patients, 77 were treated at the academic center and 23 at affiliated community practices. The median (IQR) age was 65 (52.8, 73.0) years. FLT3 testing was performed in 97% of patients at diagnosis, indicating broad incorporation of molecular testing into routine AML evaluation (100% academic vs 87% community). Median (IQR) turnaround time from FLT3 testing to result availability was 10 (6.2, 14.0) days, with a median (IQR) of 11 (7.0, 17.0) days from AML diagnosis to FLT3 result availability. Before implementation of the in-house NGS panel, quarterly median FLT3 TAT increased by an estimated 1.8% per quarter. Following implementation, quarterly median FLT3 TAT decreased immediately by 60.3% (P=0.016).
A total of seven patients with documented FLT3 mutations did not receive an inhibitor, highlighting potential gaps between molecular identification and delivery of guideline-directed therapy. Among patients receiving FLT3-directed treatment, the median interval from FLT3 result availability to inhibitor initiation was 8 days, with substantial variability across patients and practice locations.
Patients with FLT3 testing turnaround times ≤7 days demonstrated numerically longer OS, RFS, and EFS than those with turnaround times >7 days, although differences were not statistically significant (OS P=0.09; RFS P=0.26; EFS P=0.22). Among patients who received FLT3-targeted therapy, time from FLT3 result availability to inhibitor initiation was not significantly associated with OS, RFS, or EFS. Patients treated at the academic center demonstrated improved OS (P=0.045), RFS (P=0.018), and EFS (P=0.054) compared with community practices. After multivariable Cox regression, only treatment location and ECOG status remained significantly associated with OS (P=0.015 and P=0.014) and RFS (P=0.044 and P=0.041), respectively.
Conclusion
In this real-world AML cohort, FLT3 molecular testing was successfully incorporated into routine practice, with nearly all patients undergoing diagnostic testing and most patients with FLT3 alterations receiving targeted therapy. However, variability in molecular turnaround times and treatment delivery persisted, including patients with confirmed FLT3 mutations who did not receive FLT3-directed therapy. Although shorter FLT3 testing turnaround times were associated with favorable trends in OS, RFS, and EFS, these findings were not statistically significant and require validation in larger cohorts. The observed variation in testing timelines and treatment delivery highlights opportunities to optimize molecular diagnostic workflows, strengthen coordination between pathology and oncology teams, and expand in-house NGS testing, which was associated with faster TAT.
DISCLOSURES
Meenakkshy Manoharan, MD: No relevant conflicts of interest to declare.