Integration of multiparameter flow cytometry score improves prognostic stratification provided by standard models in primary myelofibrosis.

Abstract

Prognostic modeling in myelofibrosis (MF) has classically pursued the integration of informative clinical and hematological parameters to separate patients' categories with different outcomes. Modern stratification includes also genetic data from karyotype and mutations. However, some poorly standardized variables, as peripheral blood (PB) blast count by morphology, are still included. In this study, we used multiparameter flow cytometry (MFC) with the aim of improving performance of existing scores. We studied 363 MF patients with available MFC files for PB CD34+ cells count determination at diagnosis. We adapted Ogata score to MF context including 2 parameters: absolute CD34+ cells count (/μL) and granulocytes to lymphocytes SSC ratio. A score of 1 was attributed to above-threshold values of each parameter. Accordingly, patients were categorized as MFClow (score=0, 62.0%), MFCint (score=1, 29.5%), and MFChigh (score=2, 8.5%). MFClow had significantly longer median OS (not reached) compared to MFCint (55 months) and MFChigh (19 months). We integrated MFC into established models as a substitute of morphological PB blasts count. Patients were reclassified according to MFC-enhanced scores, and concordance (C-) indexes were compared. As regards IPSS, C-indexes were 0.67 and 0.74 for standard and MFC-enhanced model, respectively (Z score - 3.82; p=0.0001). MFC-enhanced MIPSS70+ model in PMF patients yielded a C-index of 0.78, outperforming its standard counterpart (C-index 0.73; Z score - 2.88, p=0.004). Our data suggest that the incorporation of MFC-derived parameters, easily attainable from standard assay used for CD34+ cells determination, might help to refine the current prognostic stratification models in myelofibrosis.