MAPS-R: International consensus classification-guided revision of the mayo alliance prognostic system for systemic mastocytosis

A Ayalew Tefferi (4Mayo Clinic, Scottsdale, United States) F Fnu Aperna (2Advent Health, Orlando, United States) M Mahesh Kumar M Maymona Abdelmagid (4Mayo Clinic, Scottsdale, United States) J Joseph Butterfield (1Mayo Clinic, Rochester, United States) T Thanai Pongdee (24Division of Allergic Diseases, Mayo Clinic, Rochester, United States) C Cecilia Arana Yi (2Mayo Clinic, Phoenix, United States) D Daniel Arber (8University of Chicago, Chicago, United States) A Attilio Orazi (9Texas Tech University Health Sciences Center, El Paso, TX, United States) D Dong Chen K Kaaren Reichard (4Mayo Clinic, Department of Laboratory Medicine and Pathology, Rochester, United States) N Naseema Gangat (4Mayo Clinic, Scottsdale, United States) A Animesh Pardanani (4Mayo Clinic, Scottsdale, United States)

Abstract

Abstract Background: The International Consensus Classification (ICC) for systemic mastocytosis (SM) recognizes mast cell leukemia (MCL) and SM with associated myeloid neoplasm (SM-AMN) as distinct categories of advanced SM (SM-Adv; Arber et al. Blood 2022;140:1200). Contemporary risk models in SM, including the Mayo Alliance Prognostic System (MAPS), do not account for the prognostic heterogeneity among ICC-defined SM-Adv subcategories. Methods: Mayo Clinic databases were utilized to access patient information. Diagnoses of SM and its morphological subcategories were confirmed through clinical evaluations and review of BM pathology. Diagnostic criteria were retrospectively fitted to be consistent with those of the ICC (Arber et al. Blood 2022;140:1200); diagnosis of MCL required the presence of immature cytomorphology of mast cells and only myeloid neoplasms were listed under the category of SM-AMN.Next-generation sequencing and cytogenetic studies was performed in a subset of the study patients according to previously described methodologies. Statistical analyses were conducted on clinical and laboratory data collected at the time of initial diagnosis while survival analysis was censored at the time of allogeneic stem cell transplant (ASCT). Results: A total of 910 Mayo Clinic patients with SM (median age 56 years, range 12-89; males 50%) were accessed in order to conduct a series of multivariable analyses (MVA) in search of independent risk factors for transplant-censored overall survival (OS). All patients were evaluable for assignment to specific ICC categories of SM: indolent (ISM; N=553), aggressive (ASM; N=114), SM-AMN (N=235), and MCL (N=8); the AMN components in SM-AMN included acute myeloid leukemia (N=18), chronic myelomonocytic leukemia (N=70), myelodysplastic syndromes (N=32), MDS/myeloproliferative overlap (N=81), myelofibrosis (N=7), polycythemia vera or essential thrombocythemia (PV/ET; N=19), and others (N=8). In addition, subsets of patients were evaluable for hemoglobin level (N= 865), white blood cell count (WBC; N=858), platelet count (N= 859), serum alkaline phosphatase (ALP; N=761), serum tryptase level (N=706), karyotype (N=574), and mutations (N=240). Median follow-up for living patients was 70 months (range, 0-520); during this time 346 (38%) deaths, 16 leukemic transformations, and 20 ASCTs were documented. ROC analysis-determined optimal cutoff levels for predicting OS included age at ≥60 years, platelet count <150 x 109/L, tryptase level ≥100 ng/mL, WBC ≥10 x 109/L, hemoglobin below sex-adjusted lower limit of normal (anemia), and ALP >210 U/L in women or >170 U/L in men (increased). All except WBC ≥10 x 109/L retained significance during MVA that included ICC-specified SM categories: MCL (HR 74.8, 26.0-215.3; p<0.01); SM-AMN (HR 3.9, 2.5-6.0; p<0.01); ASM (HR 2.2, 1.4-3.5; p<0.01); age ≥60 years (HR 3.3, 2.2-4.7; p<0.01); platelets <150 x 109/L (HR 2.8, 2.0-3.9; p<0.01); tryptase ≥100 ng/mL (HR 2.1, 1.5-2.9; p<0.01); anemia (HR 1.7, 1.1-2.4; p<0.01); and increased ALP (HR1.5, 1.1-2.0; p=0.01). A subsequent HR-weighted risk model effectively delineated 5 risk levels ranging in median survivals from 11 months to 372 months (Figure 1). Figure 2 outlines complementary subtype-specific risk models; to that end, risk factors for ISM included age ≥60 years (HR 4.5, 2.5-7.9), tryptase ≥100 ng/mL (HR 3.5, 2.1-6.0); platelets <150 x 109/L (HR 3.4, 1.5-7.9), and anemia (HR 2.4, 1.2-4.8); for ASM age ≥60 years (HR 2.3, 1.3-4.3), platelets <150 x 109/L (HR 2.4, 1.4-4.0), and anemia (HR 2.0, 1.2-3.4); and for SM-AMN age ≥60 years (HR 2.9, 1.6-5.2), platelets <150 x 109/L (HR 2.5, 1.6-3.9), and tryptase ≥100 ng/mL (HR 2.5, 1.6-3.9) [Figure 2]. In SM-AMN, additional prognostic relevance from subcategorization into PV/ET vs. all other types of AMN was appreciated (Figure 3; HR 4.0, 1.6-3.9) and incorporated into the risk model for SM-AMN (Figure 2). Abnormal karyotype (AK) and high risk mutations(HRM; ASXL1, SRSF2, RUNX1, NRAS)clustered withSM-AMN with AK and ASXL1MUT displaying independent prognostic relevance that was most apparent in SM-AMN. Conclusions : MAPS-R relies on the prognostic eminence of ICC-defined morphologic subcategories and allows for additional SM subtype-specific risk stratification. SM associated with ET or PV is a prognostically unique subcategory of SM-AMN and should be recognized as such in future classification schemes. SM-AMN must be thoroughly ruled out in the presence of AK or HRM.

Article Details

Journal Blood
Volume / Issue Vol. 146, Issue Supplement 1
Published November 03, 2025
Pages 2017-2017
ISSN 0006-4971
Publisher Elsevier BV

Journal Info

Blood

Elsevier BV

ISSN: 0006-4971 Health Sciences

Authors (13)

A

Ayalew Tefferi

4Mayo Clinic, Scottsdale, United States

F

Fnu Aperna

2Advent Health, Orlando, United States

M

Mahesh Kumar

M

Maymona Abdelmagid

4Mayo Clinic, Scottsdale, United States

J

Joseph Butterfield

1Mayo Clinic, Rochester, United States

T

Thanai Pongdee

24Division of Allergic Diseases, Mayo Clinic, Rochester, United States

C

Cecilia Arana Yi

2Mayo Clinic, Phoenix, United States

D

Daniel Arber

8University of Chicago, Chicago, United States

A

Attilio Orazi

9Texas Tech University Health Sciences Center, El Paso, TX, United States

D

Dong Chen

K

Kaaren Reichard

4Mayo Clinic, Department of Laboratory Medicine and Pathology, Rochester, United States

N

Naseema Gangat

4Mayo Clinic, Scottsdale, United States

A

Animesh Pardanani

4Mayo Clinic, Scottsdale, United States