Proposed global prognostic score for systemic mastocytosis: a retrospective prognostic modelling study

Lancet Haematol. 2021 Mar;8(3):e194-e204. doi: 10.1016/S2352-3026(20)30400-2. Epub 2021 Jan 25.


Background: Several risk stratification models have been proposed in recent years for systemic mastocytosis but have not been directly compared. Here we designed and validated a risk stratification model for progression-free survival (PFS) and overall survival (OS) in systemic mastocytosis on the basis of all currently available prognostic factors, and compared its predictive capacity for patient outcome with that of other risk scores.

Methods: We did a retrospective prognostic modelling study based on patients diagnosed with systemic mastocytosis between March 1, 1983, and Oct 11, 2019. In a discovery cohort of 422 patients from centres of the Spanish Network on Mastocytosis (REMA), we evaluated previously identified, independent prognostic features for prognostic effect on PFS and OS by multivariable analysis, and designed a global prognostic score for mastocytosis (GPSM) aimed at predicting PFS (GPSM-PFS) and OS (GPSM-OS) by including only those variables that showed independent prognostic value (p<0·05). The GPSM scores were validated in an independent cohort of 853 patients from centres in Europe and the USA, and compared with pre-existing risk models in the total patient series (n=1275), with use of Harrells' concordance index (C-index) as a readout of the ability of each model to risk-stratify patients according to survival outcomes.

Findings: Our GPSM-PFS and GPSM-OS models were based on unique combinations of independent prognostic factors for PFS (platelet count ≤100 × 109 cells per L, serum β2-microglobulin ≥2·5 μg/mL, and serum baseline tryptase ≥125 μg/L) and OS (haemoglobin ≤110 g/L, serum alkaline phosphatase ≥140 IU/L, and at least one mutation in SRSF2, ASXL1, RUNX1, or DNMT3A). The models showed clear discrimination between low-risk and high-risk patients in terms of worse PFS and OS prognoses in the discovery and validation cohorts, and further discrimination of intermediate-risk patients. The GPSM-PFS score was an accurate predictor of PFS in systemic mastocytosis (C-index 0·90 [95% CI 0·87-0·93], vs values ranging from 0·85 to 0·88 for pre-existing models), particularly in non-advanced systemic mastocytosis (C-index 0·85 [0·76-0·92], within the range for pre-existing models of 0·80 to 0·93). Additionally, the GPSM-OS score was able to accurately predict OS in the entire cohort (C-index 0·92 [0·89-0·94], vs 0·67 to 0·90 for pre-existing models), and showed some capacity to predict OS in advanced systemic mastocytosis (C-index 0·72 [0·66-0·78], vs 0·64 to 0·73 for pre-existing models).

Interpretation: All evaluated risk classifications predicted survival outcomes in systemic mastocytosis. The REMA-PFS and GPSM-PFS models for PFS, and the International Prognostic Scoring System for advanced systemic mastocytosis and GPSM-OS model for OS emerged as the most accurate models, indicating that robust prognostication might be prospectively achieved on the basis of biomarkers that are accessible in diagnostic laboratories worldwide.

Funding: Carlos III Health Institute, European Regional Development Fund, Spanish Association of Mastocytosis and Related Diseases, Rare Diseases Strategy of the Spanish National Health System, Junta of Castile and León, Charles and Ann Johnson Foundation, Stanford Cancer Institute Innovation Fund, Austrian Science Fund.

MeSH terms

  • Adult
  • Aged
  • Alkaline Phosphatase / blood
  • Core Binding Factor Alpha 2 Subunit / genetics
  • Female
  • Hemoglobins / analysis
  • Humans
  • Kaplan-Meier Estimate
  • Male
  • Mastocytosis, Systemic / diagnosis*
  • Mastocytosis, Systemic / mortality
  • Middle Aged
  • Polymorphism, Single Nucleotide
  • Prognosis
  • Progression-Free Survival
  • Repressor Proteins / genetics
  • Retrospective Studies
  • Risk Factors
  • Serine-Arginine Splicing Factors / genetics


  • ASXL1 protein, human
  • Core Binding Factor Alpha 2 Subunit
  • Hemoglobins
  • RUNX1 protein, human
  • Repressor Proteins
  • SRSF2 protein, human
  • Serine-Arginine Splicing Factors
  • Alkaline Phosphatase