Integrating Genomic and Clinical Data in AML: Real-World Application of the Sanger Multistage Model.

Background

Acute myeloid leukemia (AML) is genomically heterogeneous, and translating baseline molecular data into individualized prognosis remains difficult. We assessed real-world outcomes and externally validated the Sanger Institute AML multistage prognostic model.

Methods

This single-center, retrospective study included 73 AML patients who underwent targeted NGS profiling. In intensively treated patients, the published, validated Sanger AML multistage prognostic model was compared with observed 12- and 36-month clinical outcomes using quadratic-weighted Cohen's kappa.

Results

Median age was 61 years, and median overall survival was 13 months, with the most significant survival differences driven by treatment intensity. TP53 mutations occurred in 7 patients (9.6%) and were linked to primary refractoriness and extremely poor survival. TP53 was the only independent predictor of death (HR 8.07, 95% CI 2.23-29.13; p = 0.0014). Model concordance was moderate at 12 months (29 evaluable cases; weighted κ = 0.52; alive/dead κ = 0.52) and fair-to-moderate at 36 months (23 cases; weighted κ = 0.46). The tool performed best for predicted death without remission, while most discrepancies involved patients expected to remain in first remission who later relapsed and died.

Conclusions

TP53 disruption dominates prognosis in real-world AML. The multistage tool supports early high-risk identification but shows limited long-term calibration, motivating the development of dynamic models integrating contemporary therapies and longitudinal min/serial NGS data.