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Updated: Jan 25, 2026

Transduction-Transplantation Mouse Model of Myeloproliferative Neoplasm
Published on: December 22, 2016
Diagnostic reassessment in myeloproliferative neoplasms: the value of functional iron parameters and JAK2 allelic
Rita González-Resina1, Sara España-Fernández de Valderrama2, Ángeles Montañés3
1Servicio de Hematología y Hemoterapia, Hospital Universitario Miguel Servet, Zaragoza, Spain. rita.gonzalezresina@gmail.com.
Abstract:
Polycythemia vera (PV) and essential thrombocythemia (ET) are chronic myeloproliferative neoplasms (MPNs), often associated with mutations in JAK2, CALR, and MPL. Differentiating PV from ET can be challenging in borderline cases, particularly when hemoglobin (Hb), hematocrit (Hct) and erythropoietin (EPO) values are inconclusive. Functional iron parameters and JAK2 variant allele frequency (VAF) may provide additional discriminatory value. To assess the diagnostic utility of transferrin saturation index (TSI), serum ferritin, EPO, and JAK2 VAF in distinguishing PV from ET, and to evaluate their association with mutational profiles. We conducted a retrospective, single-center study including 260 adult patients diagnosed with PV or ET between 2009 and 2024. Demographic, clinical, molecular, and laboratory parameters-including ferritin, TSI, EPO, Hb, Hct, and JAK2 VAF-were analyzed. Comparative and correlation analyses were performed using appropriate statistical tests. Compared to ET, patients with PV had significantly lower ferritin (median: 35.65 vs. 95.05 ng/mL), TSI (12.9% vs. 21.64%), and EPO (2.23 vs. 6.11 mIU/mL), but higher Hb (17.7 vs. 14.3 g/dL) and Hct (54.6% vs. 43.0%) (all p < 0.001). TSI discriminated PV from ET better than ferritin (p < 0.001 vs. p = 0.128). Among JAK2-mutated cases, VAF was higher in PV than ET (median: 48% vs. 21%, p = 0.003). VAF correlated inversely with ferritin, TSI, and EPO, and positively with Hct. TSI and JAK2 VAF outperform ferritin as diagnostic markers to differentiate PV from ET. Integrating functional iron parameters with molecular data improves diagnostic accuracy, particularly in clinically ambiguous cases, and supports their inclusion in MPN diagnostic algorithms.
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