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

Area of Science:

• Hematology
• Oncology
• Genomics

Background:

• Acute myeloid leukemia (AML) presents significant genomic heterogeneity, complicating individualized prognosis.
• Translating baseline molecular data into actionable prognostic insights remains a clinical challenge.

Purpose of the Study:

• To assess real-world outcomes in AML patients.
• To externally validate the Sanger Institute AML multistage prognostic model using targeted next-generation sequencing (NGS) data.

Main Methods:

• Retrospective analysis of 73 AML patients undergoing targeted NGS.
• Comparison of the Sanger AML model with observed 12- and 36-month outcomes using quadratic-weighted Cohen's kappa.

Main Results:

• TP53 mutations (9.6%) were strongly associated with primary refractoriness and poor survival, identified as the sole independent predictor of death.
• The prognostic model demonstrated moderate concordance at 12 months (κ=0.52) and fair-to-moderate at 36 months (κ=0.46).
• Model discrepancies were noted in patients predicted for remission but who relapsed and died.

Conclusions:

• TP53 gene disruption is a dominant prognostic factor in real-world AML.
• The multistage prognostic tool aids early high-risk identification but requires improvement for long-term calibration.
• Development of dynamic models incorporating contemporary therapies and longitudinal NGS data is warranted.