BLAST: a globally applicable and molecularly versatile survival model for chronic myelomonocytic leukemia

Abstract

We sought to develop a survival model in chronic myelomonocytic leukemia (CMML) that is primarily based on clinical variables and examine additional impact from mutations and karyotype. A total of 457 molecularly annotated patients were considered. Multivariable analysis identified circulating blasts ≥2% (1 point), leukocytes ≥13 × 109/L (1 point), and severe (2 points) or moderate (1 point) anemia as preferred risk variables in developing a clinical risk stratification tool for overall survival (OS), acronymized to "BLAST": low risk (0 points; median, 63 months); intermediate risk (1 point; median, 28 months; hazard ratio [HR], 2.2; 95% confidence interval [CI], 1.6-3.0), and high risk (2-4 points; median, 13 months; HR, 5.4; 95% CI, 4.1-7.3); the corresponding 3/5-year OS rates were 68%/53%, 43%/18%, and 12%/1%. BLAST model performance (area under the receiver operating characteristic curve [AUC] 0.77/0.85 at 3/5 years) was shown to be comparable to that of the molecular CMML-specific prognostic scoring system (AUC 0.73/0.75) and the international prognostic scoring system-molecular (AUC 0.73/0.74). Multivariable analysis of mutations and karyotype identified PHF6MUT and TET2MUT as being "favorable" and DNMT3AMUT, U2AF1MUT, BCORMUT, SETBP1MUT, ASXL1MUT, NRASMUT, PTPN11MUT, RUNX1MUT, TP53MUT, and adverse karyotype, "unfavorable." Molecular information was subsequently encoded in a combined clinical-molecular risk model (BLAST-mol; AUC 0.80/0.86 at 3/5 years) that included the aforementioned BLAST clinical risk variables and a 3-tiered molecular risk score. BLAST and BLAST-mol were subsequently validated by 2 separate external cohorts. Independent risk factors for blast transformation included DNMT3AMUT, ASXL1MUT, PHF6WT, leukocytes ≥13 × 109/L, and ≥2% circulating or ≥10% bone marrow blasts. The current study proposes an easy-to-implement, globally applicable, and molecularly adaptive risk model for CMML.