GIPSS: genetically inspired prognostic scoring system for primary myelofibrosis

Leukemia. 2018 Jul;32(7):1631-1642. doi: 10.1038/s41375-018-0107-z. Epub 2018 Mar 23.

Abstract

International collaborations over the years have produced a series of prognostic models for primary myelofibrosis (PMF), including the recently unveiled mutation-enhanced international prognostic scoring systems for transplant-age patients (MIPSS70 and MIPSS70-plus). In the current study, we considered the feasibility of a genetically inspired prognostic scoring system (GIPSS) that is exclusively based on genetic markers. Among 641 cytogenetically annotated patients with PMF and informative for previously recognized adverse mutations, multivariable analysis identified "VHR" karyotype, "unfavorable" karyotype, absence of type 1/like CALR mutation and presence of ASXL1, SRSF2, or U2AF1Q157 mutation, as inter-independent predictors of inferior survival; the respective HRs (95% CI) were 3.1 (2.1-4.3), 2.1 (1.6-2.7), 2.1 (1.6-2.9), 1.8 (1.5-2.3), 2.4 (1.9-3.2), and 2.4 (1.7-3.3). Based on HR-weighted risk points, a four-tiered GIPSS model was devised: low (zero points; n = 58), intermediate-1 (1 point; n = 260), intermediate-2 (2 points; n = 192), and high (≥3 points; n = 131); the respective median (5-year) survivals were 26.4 (94%), 8.0 (73%), 4.2 (40%), and 2 (14%) years; the model was internally validated by bootstrapping and its predictive accuracy was shown to be comparable to that of MIPSS70-plus. GIPPS offers a low-complexity prognostic tool for PMF that is solely dependent on genetic risk factors and, thus, forward-looking in its essence.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Biomarkers
  • Cell Transformation, Neoplastic / genetics
  • Epistasis, Genetic
  • Female
  • Genetic Association Studies*
  • Genetic Predisposition to Disease*
  • Humans
  • Male
  • Middle Aged
  • Primary Myelofibrosis / diagnosis*
  • Primary Myelofibrosis / genetics*
  • Primary Myelofibrosis / mortality
  • Prognosis
  • Risk Assessment
  • Risk Factors
  • Survival Analysis

Substances

  • Biomarkers