Naslov
High platelet-to-lymphocyte ratio may differentiate polycythemia vera from secondary polycythemia

Autori
Krečak, Ivan ; Holik, Hrvoje ; Morić Perić, Martina ; Zekanović, Ivan ; Coha, Božena ; Gverić-Krečak, Velka ; Marko, Lucijanić

Izvornik
Wiener klinische Wochenschrift (0043-5325) 134 (2022), 11-12; 483-486

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Neutrophil-to-lymphocyte ratio ; Erythropoietin ; Biomarkers ; Janus Kinase 2

Sažetak
Discriminating polycythemia vera (PV) from secondary polycythemia (SP) is crucial due to the inherent risk of thrombosis in PV and different treatment approaches. The majority of PV patients have subnormal serum erythropoietin levels and harbor Janus kinase 2 (JAK2) mutations ; however, serum erythropoietin levels may be normal in approximately one third of PV patients and mutational analysis is costly and requires access to specialized laboratories. Recently, neutrophil- to-lymphocyte (NLR) and platelet-to-lymphocyte ratios (PLR) emerged as rapidly available biomarkers to identify PV patients under an increased risk of thrombosis and death. This multicenter retrospective study investigated whether these two biomarkers may also be used to differentiate PV from SP. A total of 207 subjects were included (103 PV and 104 SP) with both baseline NLR (median 4.33 vs. 1.89) and PLR (median 259.12 vs. 81.11) being significantly higher in PV than in SP (p < 0.001 for both analyses). According to the receiver operating curve analysis, PLR (area under the curve, AUC 0.936, the optimal cut-off value of > 138.1 had 82.5% sensitivity and 91.67% specificity for the detection of PV) outperformed other tested variables (NLR, total leukocytes, neutrophils, lymphocytes and platelets) and its cut-off values with 100% specificity and sensitivity were able to confirm (PLR > 224.56 ; 31% patients) and to exclude (PLR < 68.8 ; 13% patients) the highest proportions of PV patients. Therefore, PLR may represent a cheap and a rapidly available biomarker with valuable diagnostic and prognostic properties. This information may be particularly useful in resource-limited settings ; however, our results need validation on larger datasets.

Izvorni jezik
Engleski

Znanstvena područja
Kliničke medicinske znanosti

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