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Neutrophil-to-lymphocyte ratio is a novel predictor of venous thrombosis in polycythemia vera.

Alessandra CarobbioAlessandro Maria VannucchiValerio De StefanoArianna MasciulliPaola GuglielmelliGiuseppe Gaetano LoscoccoFrancesco RamundoElena RossiYogendra KanthiAyalew TefferiTiziano Barbui
Published in: Blood cancer journal (2022)
We investigated the neutrophil-to-lymphocyte ratio (NLR) as a predictor of thrombosis in polycythemia vera (PV). After a median follow-up of 2.51 years, of 1508 PV patients enrolled in the ECLAP study, 82 and 84 developed arterial and venous thrombosis, respectively. Absolute counts of total leukocytes, neutrophils, lymphocytes, platelets, and the NLR were tested by generalized additive models (GAM) to evaluate their trend in continuous scale of thrombotic risk. Only for venous thrombosis, we showed that baseline absolute neutrophil and lymphocyte counts were on average respectively higher (median: 6.8 × 10 9 /L, p = 0.002) and lower (median: 1.4 × 10 9 /L, p = 0.001), leading to increased NLR values (median: 5.1, p = 0.002). In multivariate analysis, the risk of venous thrombosis was independently associated with previous venous events (HR = 5.48, p ≤ 0.001) and NLR values ≥5 (HR = 2.13, p = 0.001). Moreover, the relative risk in both low- and high-standard risk groups was almost doubled in the presence of NLR ≥ 5. These findings were validated in two Italian independent external cohorts (Florence, n = 282 and Rome, n = 175) of contemporary PV patients. Our data support recent experimental work that venous thrombosis is controlled by innate immune cells and highlight that NLR is an inexpensive and easily accessible prognostic biomarker of venous thrombosis.
Keyphrases
  • peripheral blood
  • end stage renal disease
  • ejection fraction
  • newly diagnosed
  • prognostic factors
  • patient reported outcomes
  • machine learning
  • mass spectrometry
  • deep learning
  • single molecule