Neutrophil-to-Lymphocyte ratio as surrogate for JAK2V617F suppression and event-free survival in polycythemia vera

Abstract

Chronic systemic inflammation is a key driver of polycythemia vera (PV) progression, but the immunomodulatory effects of current treatments remain poorly defined. The neutrophil-to-lymphocyte ratio (NLR) is an accessible biomarker of systemic inflammation proven in other contexts, but its role in monitoring PV disease activity has not been established. Using data from three of the largest PV clinical trials, we evaluated the effects of PV therapies on NLR and its relationship with molecular response and clinical outcomes. In 404 hematocrit-controlled patients from the ECLAP study, hydroxyurea (HU) failed to significantly lower NLR (p = 0.11) due to the parallel declines in ANC and ALC. Neither leukocyte counts nor NLR were significantly reduced by phlebotomy in ECLAP patients treated without cytoreductive therapy. In contrast, the Low-PV study showed that while phlebotomy tended to increase NLR, low-dose ropeginterferon alfa-2b (Ropeg) significantly reduced NLR (-18.2% and -36.3% in patients with low and high baseline NLR, respectively) by suppressing ANC rather than lymphocytes. NLR reduction correlated with the primary Low-PV endpoint (p = 0.021) and reduction of JAK2 variant allele frequency (VAF) [1]. The PROUD-PV/CONTINUATION-PV study confirmed the superior effect of Ropeg over HU, with a significantly greater NLR reduction at 60 months (-56.5% versus -33.6%, respectively, p = 0.019) in patients with high baseline NLR. Moreover, NLR reduction was associated with decreased JAK2^V617F VAF (p < 0.0001) and improved event-free survival (p = 0.010). These findings identify NLR as a dynamic biomarker of treatment response and prognosis in PV and support its incorporation into routine monitoring.

Fig. 1. Longitudinal trend of WBC, NLR, neutrophils and lymphocytes in patients treated with hydroxyurea (HU) or phlebotomy (PHL), including subgroups with elevated baseline values (ECLAP database).

36-months trends of WBC (A), NLR (B), neutrophils (C), and lymphocytes (D) by treatment received in ECLAP database. The trend for the whole cohort and a focus on the subgroup of patients with high baseline values (above the median value) are reported in each panel. Global differences between the two treatments and differences over time were evaluated by a linear mixed-effect model with treatment, time and treatment-time interaction as fixed effects and patient as random intercept. *p-value for the main effect of treatment; **p-values for treatment-time interaction: a significant p-value indicates that the trend of each biomarker over time is different in the two arms, suggesting that the treatment affects how the parameter changes over time.

Fig. 2. Multivariable Cox model for the effect of inflammatory biomarkers on risk of total thrombosis and death (ECLAP database).

Estimates were obtained using a multivariable Cox regression model that included the effect of both WBC and NLR over time as time-dependent variables, adjusting for age, HU treatment, and cardiovascular (CV) risk factors (hypertension, hypercholesterolemia, diabetes, congestive heart failure, and smoking). Hazard ratios (HRs) for thrombosis (blue triangles) and mortality (red diamonds) were plotted with 95% confidence intervals (CIs) (solid lines). In this model, total thromboses were considered, rather than separating arterial and venous thromboses, to ensure adequate statistical power.

Fig. 3. Longitudinal trend of WBC, NLR, neutrophils and lymphocytes in patients treated with Ropeginterferon (Ropeg) or phlebotomy (PHL), including subgroups with elevated baseline values (Low-PV database).

12-months trends of WBC (A), NLR (B), neutrophils (C), and lymphocytes (D) by treatment received in Low-PV database. The trend for the whole cohort and a focus on the subgroup of patients with high baseline values (above the median value) are reported in each panel. Global differences between the two treatments and differences over time were evaluated by a linear mixed-effect model with treatment, time and treatment-time interaction as fixed effects and patient as random intercept. *p-value for the main effect of treatment; **p-values for treatment-time interaction: a significant p-value indicates that the trend of each biomarker over time is different in the two arms, suggesting that the treatment affects how the parameter changes over time.

Fig. 4. Longitudinal trend of WBC, NLR, neutrophils and lymphocytes in patients treated with Ropeginterferon (Ropeg) or hydroxyurea (HU), including subgroups with elevated baseline values (PROUD-PV/CONTINUATION-PV database).

60-months trends of NLR values by treatment received in PROUD-PV/CONTINUATION-PV. The trend for the whole cohort and a focus on the subgroup of patients with high baseline values (above the median value) are reported in each panel. Global differences between the two treatments and differences over time were evaluated by a linear mixed-effect model with treatment, time and treatment-time interaction as fixed effects and patient as random intercept. *p-value for the main effect of treatment; **p-values for treatment-time interaction: a significant p-value indicates that the trend of NLR over time is different in the two arms, suggesting that the treatment affects how the parameter changes over time.

Fig. 5. Median relative changes in JAK2^V617F VAF at 12 months according to categories of NLR reduction in patients treated with Ropeginterferon: PROUD-PV/CONTINUATION-PV database (Panel A) and Low-PV database (Panel B).

This figure illustrates the median relative changes in JAK2^V617F VAF at 12 months in patients treated with Ropeginterferon in the PROUD-PV/CONTINUATION-PV and Low-PV studies, stratified by the extent of NLR reduction.

Fig. 6. Event-free survival by NLR category at last available assessment in PROUD-PV/CONTINUATION-PV.

Association between NLR at last available assessment and the occurrence of risk events (thromboembolic events, disease progression to myelofibrosis or acute myeloid leukemia, or death) shown by time-to-first-risk-event analysis in subgroups based on NLR over or under the threshold of 4.3 (the median level recorded at baseline).

Fig. 7. Percentage of patients with events (thromboembolic events, disease progression to myelofibrosis or acute myeloid leukemia, or death) by NLR at baseline and last available assessment in PROUD-PV/CONTINUATION-PV.

The figure shows the proportion of patients experiencing events based on NLR categories. Patients were categorized based on their baseline and final NLR values into four groups: (i) persistently low NLR (low NLR at baseline and at the final assessment), (ii) increasing NLR (low NLR at baseline but high NLR at the final assessment), (iii) decreasing NLR (high NLR at baseline but low NLR at the final assessment), and (iv) persistently high NLR (high NLR at both baseline and final assessment). The cutoff used to define high and low values corresponds to the median baseline NLR of 4.3.