Citations

AbstractTo develop a genetic risk model for primary myelodysplastic syndromes (MDS), we queried the prognostic significance of next‐generation sequencing (NGS)‐derived mutations, in the context of the Mayo cytogenetic risk stratification, which includes high‐risk (monosomal karyotype; MK), intermediate‐risk (non‐MK, classified as intermediate/poor/very poor, per the revised international prognostic scoring system; IPSS‐R), and low‐risk (classified as good/very good, per IPSS‐R). Univariate analysis in 300 consecutive patients with primary MDS identified TP53, RUNX1, U2AF1, ASXL1, EZH2, and SRSF2 mutations as “unfavorable” and SF3B1 as “favorable” risk factors for survival; for the purposes of the current study, the absence of SF3B1 mutation was accordingly dubbed as an “adverse” mutation. Analysis adjusted for age and MK, based on our previous observation of significant clustering between MK and TP53 mutations, confirmed independent prognostic contribution from RUNX1, ASXL1, and SF3B1 mutations. Multivariable analysis that included age, the Mayo cytogenetics risk model and the number of adverse mutations resulted in HRs (95% CI) of 5.3 (2.5‐10.3) for presence of three adverse mutations, 2.4 (1.6‐3.7) for presence of two adverse mutations, 1.5 (1.02‐2.2) for presence of one adverse mutation, 5.6 (3.4‐9.1) for high‐risk karyotype, 1.5 (1.1‐2.2) for intermediate‐risk karyotype and 2.4 (1.8‐3.3) for age >70 years; HR‐weighted risk point assignment generated a three‐tiered genetic risk model: high (N = 65; 5‐year survival 2%), intermediate (N = 100; 5‐year survival 18%), and low (N = 135; 5‐year survival 56%). The current study provides a practically simple risk model in MDS that is based on age, karyotype, and mutations only.

AbstractThe prognostic importance of genetic information in primary myelofibrosis (PMF) was recently highlighted in a study of over 1000 cytogenetically‐annotated patients; 5‐year survival rates were 8% for very high risk (VHR), 27% “unfavorable” and 45% “favorable” karyotype. The current study addresses the practice‐relevant question of whether or not allogeneic hematopoietic stem cell transplant (HCT) can overcome the detrimental survival effect of VHR or unfavorable karyotype. The study included 67 patients with PMF or secondary MF who received HCT at the Mayo Clinic and in whom pretransplant cytogenetic information was available. Dynamic international prognostic scoring system (DIPSS) risk distribution was 13% high, 66% intermediate‐2 and 21% intermediate‐1. Cytogenetic risk distribution was 11% VHR, 34% unfavorable and 55% favorable. At median post‐HCT follow‐up of 60 months for living patients (range 34‐170), 28 (42%) deaths were recorded. Five‐year survival was 62% and was not affected by VHR or unfavorable karyotype (P = .68). The salutary effect of HCT in patients with VHR or unfavorable karyotype was also apparent during analysis of a combined dataset that included a nontransplant cohort of 383 patients with PMF; multivariable analysis of the combined dataset (n = 450) resulted in HRs (95% CI) of 2.4 (1.6‐3.6) for absence of transplant, 3.3 (2.2‐4.8) for VHR karyotype, 1.6 (1.2‐2.1) for unfavorable karyotype, 2.9 (2.0‐4.2) for DIPSS high and 1.7 (1.4‐2.2) for DIPSS intermediate‐2. These observations were further confirmed by analysis of more stringently matched case‐control subset cohorts and provide the evidence for the therapeutic preference of HCT in cytogenetically high risk patients with MF.

AbstractTherapy related myeloid neoplasms (t‐MN) including therapy related myelodysplastic syndromes (t‐MDS) and acute myeloid leukemia (t‐AML) are associated with aggressive disease biologies and poor outcomes. In this large (n = 497) and informative (inclusive of molecular and cytogenetic information) chronic myelomonocytic leukemia (CMML) patient cohort, we demonstrate key biological insights and an independent prognostic impact for t‐CMML. T‐CMML was diagnosed in 9% of patients and occurred approximately 7 years after exposure to prior chemotherapy and/or radiation therapy. In comparison to de novo CMML, t‐CMML patients had higher LDH levels, higher frequency of karyotypic abnormalities and had higher risk cytogenetic stratification. There were no differences in the distribution of gene mutations and unlike t‐MDS/AML, balanced chromosomal translocations, abnormalities of chromosome 11q23 (1%) and Tp53 mutations (<2%) were uncommon. Molecularly integrated CMML prognostic models were not effective in risk stratifying t‐CMML patients and responses to hypomethylating agents were dismal with no complete responses. Median overall (OS) and leukemia free survival (LFS) was shorter for t‐CMML in comparison to d‐CMML (Median OS 10.9 vs 26 months and median LFS 50 vs 127 months) and t‐CMML independently and adversely impacted OS (P = .0001 HR 2.1 95% CI 1.4‐3.0). This prognostic impact was retained in the context of the Mayo Molecular Model (P = .001, HR 2.4, 95% CI 1.5‐3.7) and the GFM prognostic model (P < .0001, HR 2.15, 95% CI 1.5‐3.7). In summary, we highlight the unique genetics and independent prognostic impact of t‐CMML, warranting its inclusion as a separate entity in the classification schema for both CMML and t‐MN.