Impact of ELN clinical signs and symptoms on the thrombotic risk in Polycythemia Vera patients treated with front-line hydroxyurea

Impact of ELN clinical signs and symptoms on the thrombotic risk in Polycythemia Vera patients treated with front-line hydroxyurea | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Impact of ELN clinical signs and symptoms on the thrombotic risk in Polycythemia Vera patients treated with front-line hydroxyurea Francesca Palandri, Massimo Breccia, Elena Elli, Roberto LATAGLIATA, and 14 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6252512/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 May, 2025 Read the published version in Leukemia → Version 1 posted 11 You are reading this latest preprint version Abstract The European LeukemiaNet recently proposed specific Clinical Signs and Symptoms (CSSs) that should be considered to trigger cytoreduction in patients with polycythemia vera (PV) at low risk (LR) according to conventional criteria (age<60 years and no previous thrombosis). To evaluate the impact of CSSs on the thrombotic risk across different risk categories, including LR, high risk by age only (HR-AGE) or previous thrombosis (HR-THRO), we conducted a multicenter cooperative study (NCT06134102) involving 739 PV patients treated with first-line hydroxyurea. CSSs, including persistent/progressive leukocytosis, extreme thrombocytosis, progressive splenomegaly, inadequate hematocrit control, relevant cardiovascular risk factors (CVRFs), and severe itching, were evaluated for association with thrombosis using incidence rate ratio (IRR) per 100 patient-years (%p-y) and thrombosis-free survival (TFS) adjusted for delayed entry. At hydroxyurea start, 443 patients (60.0%) had at least one CSS. In patients with and without CSSs, the IRR of thrombosis was 2.2 and 0.7 %p-y, respectively (p<0.001), and the TFS at 5 years was 88.7% and 96.1% (p<0.001). The prognostic impact of CSSs was confirmed in all risk categories, with worse TFS in HR-THRO patients with CSSs. In multivariate analysis including each CSS singularly, inadequate hematocrit control (HR: 2.32, 95% CI: 1.45 – 3.72, p<0.001); relevant CVRFs (HR: 2.87, 95% CI: 1.36 – 6.06, p=0.006); progressive splenomegaly (HR: 4.02, 95% CI: 1.18 – 13.65, p=0.03) and previous thrombosis (HR: 3.76, 95% CI: 2.32 – 6.10, p<0.001) remained significantly associated with thrombotic risk. CSSs identify an increased thrombotic risk phenotype in all conventionally defined risk categories, supporting their evaluation in clinical practice. Health sciences/Risk factors Health sciences/Signs and symptoms Health sciences/Diseases/Haematological diseases/Haematological cancer/Myeloproliferative disease Figures Figure 1 Figure 2 Figure 3 Introduction Polycythemia vera (PV) is a Philadelphia chromosome-negative rare hematologic cancer belonging to the family of myeloproliferative neoplasms (MPN) and driven by mutations in the Janus kinase 2 ( JAK2 ) gene, most frequently the JAK2 V617F . The presence of an activating JAK2 mutation drives the aberrant proliferation of hematopoietic cells ( 1 ) leading to erythrocytosis, thrombocytosis, leukocytosis and increased cytokine production resulting in systemic symptoms typical of PV ( 2 , 3 ). Patients with PV face a substantial risk of thrombotic complications, with a 2.7- to 13.1-fold higher likelihood of developing arterial and venous thrombosis, respectively, compared to age- and sex-matched controls ( 4 ). Therefore, the clinical management of PV is focused on reducing the risk of such events, which remain the leading cause of morbidity and mortality. Advanced age and a history of previous thrombotic events are two well-established clinical risk factors for predicting future thromboembolic episodes ( 5 – 9 ). Based on these two risk factors, patients with PV are currently classified as low-risk (LR) (absence of both risk factors) and high-risk (HR) (history of thrombosis and/or age ≥ 60 years) ( 10 , 11 ). However, a growing body of literature suggests that advanced age and prior thrombosis history may rather reflect a limited view of the overall risk profile and are sometimes perceived as suboptimal for proper management of PV. The fact that various biomarkers are currently investigated for risk assessment of PV (including but not limited to allelic ratio ( 12 , 13 ), RDW/neutrophil-lymphocyte ratio ( 14 , 15 ), and others) emphasizes the importance of improved risk stratification. In light of this evidence, the European LeukemiaNet (ELN) has recently indicated the use of cytoreductive therapy also in LR patients presenting specific clinical signs and symptoms (CSSs), including, but not limited to, intolerance to phlebotomy, uncontrolled hematocrit, symptomatic progressive splenomegaly, persistent and/or progressive leukocytosis, extreme thrombocytosis, relevant cardiovascular risk factors ( 16 ). However, the prognostic role of these factors remains so far elusive. Hydroxyurea (HU) is currently the most widely used cytoreductive therapy for PV patients ( 17 , 18 ), offering effective control of the disease and playing a key role in thrombosis prevention with generally acceptable tolerance ( 19 , 20 ). In a large multicenter cooperative study, we assessed the impact of ELN clinical signs and symptoms on the thrombotic risk of PV patients homogeneously treated with first-line HU. Materials and Methods Patients’ collection and study design This is an observational, retrospective cohort study (PV-ARC, NCT06134102) that was promoted by the IRCCS Azienda Ospedaliero-Universitaria S. Orsola-Malpighi, Bologna, Italy. The study now involves 1162 patients with PV diagnosed between January 1985 and December 2023. Among them, 739 patients were treated with first-line HU and had data on CSSs available at the start of HU. Following approval of each IRB, participating centers collectively submitted diagnostic and follow-up information. The totality of medical files from each center was reported via data input into an electronic database that was developed to label all study data with an alphanumeric code after the de-identification of patients to protect personal privacy. The data collected included patient demographics, medications, clinical/laboratory tests at diagnosis and during follow-up, type of PV therapy and thromboses. All information about concomitant diseases, body mass index (BMI), cardiovascular risk factors (CVRFs), thrombosis history, and drug usage was recorded in each case history and, thereafter, used for retrospective evaluation. Any treatment decision, including the use of phlebotomies, HU and antiplatelet/anticoagulant drugs, was at the physician’s discretion and independent from participation in this study. After the first data entry, follow-up information was validated with revision of the clinical data, and specific queries were addressed to the participating centers in cases of inconsistent data. All patients were followed until death or the data cut-off date (March 2024). Ethical Aspects The PV-ARC study was performed in accordance with the guidelines of the IRBs of the participating centers and the standards of the Helsinki Declaration. For patients currently under follow-up with the experimental center, informed consent was obtained as part of one of the visits in their normal care pathway. For deceased patients, Italian regulations authorized the processing of personal data carried out for scientific research purposes (Gazzetta Ufficiale no. 72 dated 26 March 2012). Therefore, the processing of personal data is considered authorized upon approval of the study by the Ethics Committee. The promoter of this study was the IRCCS Azienda Ospedaliero-Universitaria S. Orsola-Malpighi, Bologna, which obtained approval from the Area Vasta Emilia Centro (AVEC) Ethics Committee (approval file number: 483/2018/Oss/AOUBo). This study was also approved by the local ethics committees of participating centers (protocol code: PV-ARC) and had no commercial support. Statistical Analysis Statistical analysis was carried out at the biostatistics laboratory of the MPN Unit, IRCCS Azienda Ospedaliero-Universitaria S. Orsola-Malpighi, Bologna. Continuous variables are expressed as mean ± standard deviation (SD), whereas categorical variables are presented as frequencies and percentages. Comparisons of quantitative variables between two groups of patients were carried out using the Wilcoxon–Mann–Whitney rank-sum test and among three groups using the Kruskal–Wallis equality-of-populations rank test. Associations between categorical variables were tested using the χ2 test. The mean thrombotic risk scores associated with each CVRF were analyzed by a one-way analysis of variance (ANOVA). A Poisson regression model was applied to calculate the incidence rate ratios (IRR) of thrombotic events. The IRR was described as the number of events per 100 patient-years (%p-y), considering the time between HU start and the first thrombotic event or last contact. Variables associated with thrombotic events were identified using univariate and multivariate (MVA) Cox proportional hazards model. Hazard ratio (HR) has been reported with 95% confidence intervals (CI). Thrombosis-free survival (TFS) was assessed from HU start to the first thrombosis or last contact, using Kaplan-Meier analysis, adjusted for delayed entry, considering the time between PV diagnosis and the start of HU. Differences were evaluated with the log-rank test. Tests were two-sided and P values < 0.05 were considered significant. Analyses were performed using STATA/SE software version 18.0 (StataCorp). Definitions PV was diagnosed according to the WHO 2022 classification ( 21 ). In patients diagnosed before 2022, bone marrow biopsies were internally reviewed to adhere the data to current criteria ( 21 ). In patients without a bone marrow histology, PV diagnosis was based on the presence of elevated hemoglobin levels (i.e., > 18.5 and 16.5 g/dL in males and females, respectively), the JAK2 Exon 14 or Exon 12 mutations, and low serum erythropoietin. Conventional criteria were used for the diagnosis of post Polycythemia Vera Myelofibrosis (PPV-MF) ( 22 ); leukemic transformation was defined by blast cells being at least 20% in peripheral blood and/or bone marrow, according to WHO criteria ( 21 ). According to conventional criteria, LR patients were defined by age < 60 years and no previous thrombotic history. HR patients were defined by age ≥ 60 years and/or a history of thromboembolism ( 23 ). In this analysis, HR patients were further stratified in two groups: HR-AGE (patients at high risk only due to age ≥ 60 years) and HR-THRO (patients at high risk due to previous thrombosis, regardless of age). Thromboses were defined according to the International Classification of Diseases (9th revision) ( 24 ) and graded according to the Common Terminology Criteria for Adverse Events (CTCAE) v5.0 ( 25 ). Only grade ≥ 2 thromboses occurring during HU therapy were recorded and analyzed in the present study. At HU start, presence and type of CSSs were initially searched as per the ELN definition.( 16 ) However, three criteria were adapted based on real-life experience. In particular: a platelet (PLT) count > 1500 x10 9 /L was never observed in our cohort, so the threshold has been lowered to a PLT count > 1000 x10 9 /L; for the same reason, the need for at least 6 phlebotomies (PHLs) for at least two years has been modified to at least 6 PHLs and/or a persistently higher hematocrit (HCT) of 50% for at least one year before HU start. This threshold was selected according to the results of the Cyto-PV trial, where patients randomized to maintain HCT 45–50% had poorer outcomes ( 26 ). In absence of a unified definition of “relevant” CVRF( 16 , 27 ), the ANOVA test was used to identify the combination of CVRFs most strongly correlated with the risk of thrombosis. Five predefined CVRFs, namely active smoking, hypertension, overweight (BMI ≥ 25), diabetes, and dyslipidemia, were included in the analysis ( 28 ). In summary, CSSs were defined as follows: 1) persistent/progressive leukocytosis: 100% increase if white blood cells (WBC) 15 before HU start; 2) extreme thrombocytosis: PLT > 1000 x10 9 /L at HU start; 3) progressive splenomegaly: increase by more than 5 cm below costal margin (BCM) in the year before HU start; 4) inadequate HCT control: ≥6 PHLs/year or HCT ≥ 50% at two evaluations within 1 year pre-HU start or PHL intolerance; 5) “relevant” CVRFs: co-occurrence of active smoking, hypertension and overweight (with or without the presence of diabetes and/or dyslipidemia); 6) severe itching. The presence and severity of itching at the start of HU were assessed during clinical visits. In recent years, the 10-item Myeloproliferative Neoplasm Symptom Assessment Form Total Symptom Score (MPN10-TSS) ( 29 ) has been used and “severe” itching was considered with a score ≥ 5 according to ELN definition. Alternatively, the itching score was considered ≥ 5 if refractory to specific medication (e.g., antihistamines). Additional reasons to start hydroxyurea were defined as follows: spleen palpable at 2–5 cm below costal margin, mild leukocytosis or thrombocytosis (WBC > 11 x10 9 /L or PLT > 450 x10 9 /L but not meeting the definition of persistent/progressive or extreme), presence of microvascular disturbances despite appropriate phlebotomies and antiplatelet drug therapy (including vascular headaches, dizziness, visual disturbances, burning pain sensation in the palms of the hands and soles of the feet, distal paresthesia and acrocyanosis) ( 30 ), ≥ 3 PHLs in the 12 months before HU start. Results Patient cohort Overall, 739 patients received treatment with first-line HU and were included in this analysis. At therapy start, 137 (18.5%) patients were categorized as LR and 602 (81.5%) as HR. Among them, 424 (70.4%) were HR-AGE and 178 (29.6%) were HR-THRO, with 46 (25.8%) patients only due to previous thrombosis and 132 (74.2%) due to both older age and previous thrombosis ( Supplemental Fig. 1 ). At least one CVRF was present in 577 (78.1%) patients; specifically, 276 (37.3%), 181 (24.5%), 82 (11.1%) and 38 (5.1%) patients had one, two, three or ≥ 4 CVRFs. The frequency of individual CVRFs and their inter-relationships are shown in Table 1 and in Fig. 1 a. Table 1 Distribution of Clinical Signs and Symptoms and Clinical Characteristics at Hydroxyurea Start LR (n. 137) HR (n. 602) p-value (LR vs. HR) HR-AGE (n. 424) HR-THRO (n. 178) Clinical Signs and Symptoms Presence of at least one Clinical Sign and Symptom, n. (%) 95 (69.3%) 348 (57.8%) 0.02 239 (56.4%) 109 (61.2%) Persistent/Progressive Leukocytosis, n. (%) 26 (19.0%) 63 (10.5%) 0.006 46 (10.9%) 17 (9.6%) Extreme Thrombocytosis, n. (%) 4 (2.9%) 8 (1.3%) 0.18 8 (1.9%) 0 Progressive Splenomegaly, n. (%) 9 (6.6%) 12 (2.0%) 0.004 7 (1.7%) 5 (2.8%) Inadequate Hematocrit Control, n. (%) 57 (41.6%) 224 (37.2%) 0.34 156 (36.8%) 68 (38.2%) Relevant Cardiovascular Risk Factors*, n. (%) 4 (2.9%) 37 (6.2%) 0.14 25 (5.9%) 12 (6.7%) Severe Itching, n. (%) 58 (46.0%) 188 (31.6%) 0.002 125 (29.7%) 63 (36.2%) Clinical Characteristics Age, mean (± SD), years 50.9 (± 6.5) 69.5 (± 9.3) < 0.001 71.1 (± 7.1) 65.6 (± 12.3) Hemoglobin, mean (± SD), g/dL 15.7 (± 2.1) 15.9 (± 1.9) 0.28 15.9 (± 1.9) 16.0 (± 2.0) Hematocrit, mean (± SD), % 50.4 (± 4.8) 50.3 (± 5.4) 0.98 50.3 (± 5.4) 50.3 (± 5.5) Leukocytes count, mean (± SD), x10 9 /L 13.1 (± 10.6) 10.8 (± 5.6) 0.004 10.8 (0.33–77.7) 10.7 (0.31–38.3) Platelets count, mean (± SD), x10 9 /L 622.8 (± 299.1) 519.8 (± 249.9) < 0.001 528.2 (± 250.8) 499.8 (± 247.2) Spleen length, mean (± SD), cm BCM 1.48 (± 2.51) 0.76 (± 1.96) < 0.001 0.66 (± 1.91) 0.98 (± 2.07) Smoke, n. (%) 30 (21.9%) 139 (23.1%) 0.76 86 (20.3%) 53 (29.8%) Hypertension, n. (%) 41 (29.9%) 359 (59.6%) < 0.001 258 (60.9%) 101 (56.7%) Dyslipidemia, n. (%) 22 (16.1%) 151 (25.1%) 0.02 105 (24.8%) 46 (25.8%) Diabetes, n. (%) 7 (5.1%) 69 (11.5%) 0.02 50 (11.8%) 19 (10.7%) Overweight, n. (%) 40 (29.2%) 184 (30.6%) 0.75 126 (29.7%) 58 (32.6%) Treated with antiplatelet/anticoagulants, n. (%) 131 (95.6%) 567 (94.2%) 0.51 396 (93.4%) 171 (96.1%) HU starting dose, mean (± SD), mg 739.2 (± 348.7) 692.4 (± 314.7) 0.18 709.9 (± 313.0) 650.5 (± 315.8) Maximum HU dose ≥ 1g/day, n. (%) 96 (70.1%) 280 (46.5%) 0.006 206 (48.6%) 74 (41.6%) The ANOVA scores for correlation with thrombosis were: 1.21, active smoking (IRR: 2.26%p-y); 1.15, hypertension (IRR: 1.83%p-y); 0.58, overweight (IRR: 1.93%p-y); 0.14, diabetes (IRR: 1.78%p-y) and 0.03, dyslipidemia (IRR: 1.79%p-y). In accordance with the findings of this test, patients with concomitant active smoking, hypertension and overweight were included in the "relevant CVRFs” category (ANOVA score: 4.73; p = 0.03). Overall, "relevant" CVRFs were present in 41 (5.5%) patients; in 15 of these patients, diabetes and/or dyslipidemia were also present. At HU start, CSSs were present in 443 (60.0%) patients, more frequently in LR (n. 95, 69.3%) compared to HR patients (n. 348, 57.8%, p = 0.02), mainly due to higher presence of persistent/progressive leukocytosis (p = 0.006), progressive splenomegaly (p = 0.004) and severe itching (p = 0.002) (Table 1 ). The frequency of CSSs was comparable between HR-AGE (n. 239, 56.4%) and HR-THRO (n. 109, 61.2%) patients (p = 0.27). This was also observed in HR-THRO patients due to both older age and previous thrombosis (62.1%) and HR-THRO patients due to previous thrombosis only (58.7%, p = 0.69). Overall, more than one CSS was present in 155 (out of 443, 35.0%) patients, mainly in low risk (43.2% vs. 32.8% HR, p = 0.05). The frequency of individual CSS and their inter-relationships are shown in Fig. 1 b. At HU start, median leukocytes and platelet counts, and mean spleen length BCM were significantly higher in LR compared to HR patients, with no significant differences between HR-AGE and HR-THRO patients. Median HU starting dose was comparable across the three risk categories, while LR patients more frequently received a maximum dose ≥ 1g (Table 1 ). Anticoagulants were used more frequently in HR patients (12.3% vs. 4.4% LR, p = 0.007). Conversely antiplatelets, excluding patients receiving anticoagulants, were used comparably across risk categories (LR: 95.4% vs. HR: 98.8%, p = 0.21). Additional reasons for starting HU were present in 92.9% of patients without CSSs. Distribution of additional reasons according to conventional risk categories is shown in Supplemental Table 1 . Thrombosis during hydroxyurea therapy The median time on HU was 6.2 years (SD ± 4.3). During HU therapy, 72 patients had a thrombosis, for a total of 92 thrombotic events. Thromboses were equally distributed between arterial (n. 45, 48.9%) and venous (n. 47, 51.1%). Supplemental Table 2 details type and site of thrombotic events. Globally, the IRR of thrombosis during HU was 2.02%p-y and significantly higher (3.0%p-y) in HR-THRO patients (Table 2 ). Among HR-THRO patients, patients older than 60 years had the highest IRR of thrombosis (3.5%p-y). Table 2 Incidence ratio rate (IRR) per 100 patient-years of thromboses during treatment with hydroxyurea Number of events Total cohort LR HR-AGE HR-THRO p-value (LR vs HR-AGE) p-value (LR vs HR-THRO) p-value (HR-AGE vs HR-THRO) CSSs No CSSs CSSs No CSSs CSSs No CSSs CSSs No CSSs Overall thromboses 92 2.02 1.1 1.3 3.0 0.68 0.006 0.002 2.2* 0.7* 1.6* 0* 2.0* 0.5* 4.0* 1.7* Arterial thromboses 45 0.99 0.5 0.6 1.3 0.79 0.05 0.10 1.0* 0.3* 0.8 0 1.0* 0.2* 1.8* 0.3* Venous thromboses 47 1.03 0.6 0.7 1.7 0.85 0.05 0.02 1.2* 0.4* 0.8 0 1.0* 0.3* 2.2 1.4 Impact of clinical signs and symptoms on the incidence of thrombosis during hydroxyurea therapy The IRR of thrombosis was estimated according to the presence of CSSs, without considering the presence of additional reasons for starting HU. In the total cohort, CSSs were associated with a significantly increased IRR of thrombosis (2.2 vs. 0.7%p-y in patients without CSSs, p < 0.001). This was confirmed across all the risk categories (Table 2 ). TFS at 5 years was 88.6% in patients with CSSs compared to 96.2% in those without CSSs (p < 0.001) (Fig. 2 a). Examining the three risk categories separately, the TFS curve of patients with CSSs was always significantly worse than that of patients without CSSs (Fig. 2 b, 2 c, 2 d). Across all risk categories, the best TFS at 5 years was observed in LR and HR-AGE (LR with no CSSs, 100%; HR-AGE with no CSSs: 98.1%). LR and HR-AGE patients with CSSs had comparable TFS than HR-THRO patients without CSSs (89.2%, 92.1% and 88.8%, respectively). HR-THRO patients with CSSs had the most dismal TFS (80.2%) ( Supplemental Fig. 2 ). The prognostic impact of each individual CSS on the thrombotic risk was also explored. In univariate Cox analysis, history of thrombosis (p < 0.001), age ≥ 60 years (p = 0.04), extreme thrombocytosis (p = 0.01), progressive splenomegaly (p = 0.05), inadequate hematocrit control (p = 0.01), relevant CVRFs (p = 0.01) were significantly associated with a higher thrombotic risk. In MVA, four factors maintained significant association with the thrombotic risk: inadequate hematocrit control (HR: 2.32, 95% CI: 1.45–3.72, p < 0.001); relevant CVRFs (HR: 2.87, 95% CI: 1.36–6.06, p = 0.006); progressive splenomegaly (HR: 4.02, 95% CI: 1.18–13.65, p = 0.03) and history of thrombosis (HR: 3.76, 95% CI: 2.32–6.10, p < 0.001) (Fig. 3 ). Discussion HU is the primary cytoreductive agent used in the treatment of PV and plays a crucial role in the overall anti-thrombotic strategy. Its use significantly reduces the incidence of thrombotic events; however, a notable number of events still occur, with an incidence rate of 3.3% p-y, which increases with age ( 31 ). The effectiveness of HU is greater in preventing initial or recurrent arterial events, but it has a higher failure rate in preventing venous events ( 30 , 32 , 33 ). Therefore, it is essential to identify patient groups undergoing cytoreductive therapy who remain at an increased risk for thrombosis. In our cohort, the overall incidence of thrombosis during HU treatment is lower than what was estimated in the aforementioned meta-analysis, likely due to the younger median age of our patients, which includes LR patients. However, the incidence of recurrent thrombosis in the HR-THRO group (3% p-y) is comparable to the rate reported in the meta-analysis (4.5% p-y), indicating that the patients we studied reflect real-world scenarios. It has been more than two years since the publication of the ELN recommendations on the relevance of specific clinical signs and symptoms to consider for earlier therapy in conventionally defined low-risk PV patients ( 16 ). However, the strength of these recommendations remains weak due to a lack of specific data on the prognostic impact of such CSSs on the thrombotic risk. Our results show that CSSs are common and significantly influence thrombotic risk, isolating a cohort of patients at further increased risk within each risk category. Additionally, three CSSs were more significantly associated with thrombosis: inadequate hematocrit control, relevant cardiovascular risk factors and progressive splenomegaly. Elevated hematocrit is one of the major risk factors for thrombosis in patients with PV ( 2 , 11 ). In the CYTO-PV study, patients with hematocrit below 45% had a lower incidence of deaths from cardiovascular causes or major thrombotic events (1.1 %p-y)than those with a target hematocrit of 45–50% (4.4 %p-y)( 34 ). A higher risk of thrombosis has also been observed in the subset of HU-treated patients requiring ≥ 3 phlebotomies per year ( 35 ). There is a significant association between major thromboembolic events and hypertension, diabetes, hyperlipidemia, obesity and smoking ( 5 , 7 – 9 , 13 , 36 – 39 ). Nevertheless, a consensus on which cardiovascular risk factors and/or combinations thereof should be designated as "relevant" in patients with PV remains elusive. As observed in this study, patients frequently exhibit multiple concomitant cardiovascular risk factors. These CVRFs often co-occur with other clinical signs and symptoms that correlate with the thrombotic risk, such as inadequate hematocrit control (Fig. 1 b). Furthermore, the impact of individual CVRFs can sometimes be masked by the thrombotic risk associated with PV, complicating the identification of a single CVRF that is associated with a heightened thrombotic risk. We ultimately adopted a composite definition, requiring the concurrent presence of at least three CVRFs, including smoke, hypertension, and overweight. This definition was derived from statistical associations with thrombotic risk and relative incidence rates ratio of thrombosis associated with each factor. From a biological perspective, this composite definition is more likely to reflect the synergistic effects of CVRFs. The potential for cumulative risk actions associated with the concurrent presence of two risk factors cannot be disregarded. However, this definition aligns with previous guidelines and may serve as a practical clinical guidance tool ( 16 , 40 ). Overall, these findings recommend that CVRFs in all PV patients should be adequately controlled and reinforce the necessity of a multidisciplinary approach. We also observed a correlation between progressive splenomegaly and an increased risk of thrombosis. This correlation has been reported by previous groups ( 8 ) but not confirmed in other cohorts ( 41 ). Overall, further investigation into the dynamic evaluation of the spleen may provide valuable insights for the management of PV. Here, we could not confirm the association between thrombocytosis/leukocytosis and thrombosis. The number of platelets in PV outcomes is controversial, with some studies ( 5 , 42 ), but not others ( 30 ), reporting an association between higher platelet count and thrombosis. While in the ECLAP and in the CYTO-PV studies an association between leukocytosis and vascular events was noted ( 5 , 42 ), hyperleukocytosis at diagnosis or during follow-up was not found to correlate with thrombotic risk in other studies ( 43 , 44 ). Neutrophil-to-lymphocyte ratio (NLR) values ≥ 5 was independently associated with an increased risk of venous thrombosis, which suggests that NLR, rather than leukocyte count alone, may be a valuable prognostic biomarker for thrombosis in PV and should be further investigated ( 15 , 45 ). Overall, this analysis shows that multiple phlebotomies and/or persistently elevated hematocrit (> 50%), presence of relevant CVRFs and progressive splenomegaly are major determinants of thrombotic risk and should trigger therapeutic intervention, including multidisciplinary patient management and dynamic clinical-laboratory evaluation. Finally, our study confirmed the pivotal role of thrombotic history, which appeared to be even more relevant than older age ( 5 , 7 – 9 , 36 , 46 ). However, IRRs of thrombosis demonstrated a linear correlation between thrombotic risk and age. It is notable that the IRR for low-risk patients (aged under 60 with no previous history of thrombosis) is 1.1 %p-y, while he IRR for high-risk patients aged 60 or over (but with no previous thrombosis) is higher at 1.3 %p-y. This icidence is comparable to that of patients at high risk for a previous thrombotic history (but aged under 60 years), who have an IRR of 1.9 %p-y. The siultaneous presence of both risk factors identifies the highest risk category, with an IRR of 3.5 %p-y. The reults are comparable to those of the ECLAP study, which found that the IRRs of thrombosis were similar in older age groups without thrombosis (4.9 %p-y) and inyounger age groups with thrombosis (5.0 %p-y) ( 46 ). Intrinsic limitations of the present study are due to its retrospective nature and include uncontrolled patient adherence to HU therapy, consistency in the assessment of CSSs, and reporting of thrombotic events, which may vary and affect the generalizability of the results. However, the study's robust sample size, its focus on real-world adaptations of the ELN recommendations and consistent findings across patient subgroups are its main strengths. In conclusion, CSSs may identify an increased risk phenotype across all thrombotic risk categories and may be actionable markers that can inform more aggressive and personalized management strategies. Furthermore, this study supports further research to investigate the integration of CSSs into existing risk models to improve prognostic accuracy and optimize treatment decisions in PV. Declarations Acknowledgements This work was supported by Ministero della Salute Ricerca corrente and by BolognAIL. Funding The work reported in this publication was funded by Italian Ministry of Health, RC-2024-2790083 project. F.H.H. was supported in part by grants of the German Research Council (DFG): HE6233/15-1 and 16-1, project number 517204983. Authorship Contributions Fr.P. : Conceptualization; Investigation; Funding acquisition; Writing - original draft; Writing - review & editing; Data curation; Resources; and Visualization. F.B. : Conceptualization, Writing - original draft; Writing - review & editing; Data curation; Formal analysis; and Visualization. E.M., A.De., G.Be., M.T., G.A.P., M.Br., E.M.E., R.L., E.R., V.D.S : Conceptualization; Investigation; Visualization; Writing - review & editing; Resources. Fr.C., A.T., M.Fa., A.D., E.A., Fa.C., R.M., A.C., B.M.: Investigation; Writing - review & editing; and Resources. F.H.H : Visualization; Writing - review & editing Competing Interests Francesca Palandri participated in the speakers bureau and advisory board of Novartis, BMS, AOP, Sierra Oncology, Incyte, Telios, Abbvie, Constellation-Morphosys, Sobi and GSK. Giulia Benevolo reports honoraria from Novartis, Janssen, Amgen, Takeda, and BMS. Massimo Breccia reports honoraria from Novartis, BMS, Pfizer, Incyte. Giuseppe A. Palumbo reports consultancy and honoraria from Abbvie, AOP, AstraZeneca, BMS, Incyte, GSK, Morphosys, and Novartis. Mario Tiribelli reports honoraria from and has served on speakers’ bureaus for Novartis, BMS, Pfizer, and Incyte. Valerio De Stefano participated in the speakers bureau and advisory board of Abbvie, AOP Health, Bristol Myers Squibb, Glaxo Smith Kline, Grifols, Novartis, Novo Nordisk, Sanofi, SOBI, Takeda. Florian H. Heidel served as an advisor for Novartis, CTI, Celgene/BMS, Janssen, Abbvie, GSK, Merck and AOP and received research funding from Novartis, Celgene/BMS and CTI. Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request to the corresponding author ( [email protected] ). DOI: 10.5281/zenodo.14017557. Competing Interests Francesca Palandri participated in the speakers bureau and advisory board of Novartis, BMS, AOP, Sierra Oncology, Incyte, Telios, Abbvie, Constellation-Morphosys, Sobi and GSK. Giulia Benevolo reports honoraria from Novartis, Janssen, Amgen, Takeda, and BMS. Massimo Breccia reports honoraria from Novartis, BMS, Pfizer, Incyte. Giuseppe A. Palumbo reports consultancy and honoraria from Abbvie, AOP, AstraZeneca, BMS, Incyte, GSK, Morphosys, and Novartis. Mario Tiribelli reports honoraria from and has served on speakers’ bureaus for Novartis, BMS, Pfizer, and Incyte. Valerio De Stefano participated in the speakers bureau and advisory board of Abbvie, AOP Health, Bristol Myers Squibb, Glaxo Smith Kline, Grifols, Novartis, Novo Nordisk, Sanofi, SOBI, Takeda. Florian H. Heidel served as an advisor for Novartis, CTI, Celgene/BMS, Janssen, Abbvie, GSK, Merck and AOP and received research funding from Novartis, Celgene/BMS and CTI. References Perner F, Perner C, Ernst T, Heidel FH. Roles of JAK2 in Aging, Inflammation, Hematopoiesis and Malignant Transformation. Cells. 2019;8(8). Tefferi A, Barbui T. Polycythemia vera: 2024 update on diagnosis, risk-stratification, and management. Am J Hematol. 2023;98(9):1465–87. Waggoner, MS, PA-C M. Polycythemia Vera: Thinking Beyond the Hematocrit. J Adv Pract Oncol. 2023;14(5):405. 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Additional Declarations Yes there is potential conflict of interest. Supplementary Files LeukemiaSupplementalMaterial.pdf Supplemental Material Cite Share Download PDF Status: Published Journal Publication published 28 May, 2025 Read the published version in Leukemia → Version 1 posted Editorial decision: revise 02 Apr, 2025 Review # 3 received at journal 01 Apr, 2025 Review # 2 received at journal 30 Mar, 2025 Reviewer # 3 agreed at journal 23 Mar, 2025 Review # 1 received at journal 22 Mar, 2025 Reviewer # 2 agreed at journal 20 Mar, 2025 Reviewer # 1 agreed at journal 19 Mar, 2025 Reviewers invited by journal 19 Mar, 2025 Editor assigned by journal 19 Mar, 2025 Submission checks completed at journal 19 Mar, 2025 First submitted to journal 18 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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In the Circos representation, the length of the arc corresponds to the frequency of the CVRF/CSS (color coded) and the width of the ribbon corresponds to the frequency of patients who also had a second CVRF/CSS. The frequency of each individual CVRF/CSS in this cohort is shown on the right side. Specifically, (b) shows the prevalence proportion of individual CSS.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6252512/v1/5d6ec962a5ab7a1e195115d0.png"},{"id":79573750,"identity":"e79119c9-a943-4889-b0e3-606e3c7fac48","added_by":"auto","created_at":"2025-03-31 11:08:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1609244,"visible":true,"origin":"","legend":"\u003cp\u003eThrombosis-free Survival comparison between patients presenting at least one Clinical Sign and Symptom (CSS) (dashed lines) and patients not presenting CSSs (continuous lines)\u003c/p\u003e\n\u003cp\u003eFigure 2: a) Overall Cohort; b) low risk (LR); c) high risk only for age (HR-AGE); d) high risk for previous thrombosis (HR-THRO). HU, hydroxyurea\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6252512/v1/e2843647c6d4d604effdce03.png"},{"id":79573748,"identity":"46de3c75-fce9-48de-8fb2-fd2eee85f646","added_by":"auto","created_at":"2025-03-31 11:08:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":8059110,"visible":true,"origin":"","legend":"\u003cp\u003eMultivariate analysis of clinical signs and symptoms to evaluate the impact on thrombotic risk in the overall patient cohort.\u003c/p\u003e\n\u003cp\u003eFigure 3: CVRFs, Cardiovascular Risk Factors, HU, hydroxyurea, HR, hazard ratio; CI, confidence interval. Red dots identify variable statistically significantly associated with a higher probability of thrombosis during hydroxyurea in both multivariate and univariate analysis; Yellow dots identify variable statistically significantly associated with a higher probability of thrombosis during hydroxyurea only in univariate analysis.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6252512/v1/a2935069b95df9d7e6175b52.png"},{"id":83593747,"identity":"8754de16-ea72-443f-b3f0-8e4841ea1051","added_by":"auto","created_at":"2025-05-29 07:09:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":15485978,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6252512/v1/cf1045e2-0721-4bef-a38c-6f400417009e.pdf"},{"id":79573744,"identity":"6cff60dc-3a42-4028-a825-bcb0753123d6","added_by":"auto","created_at":"2025-03-31 11:08:09","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":409860,"visible":true,"origin":"","legend":"Supplemental Material","description":"","filename":"LeukemiaSupplementalMaterial.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6252512/v1/1529807d42ecd2564ebddebb.pdf"}],"financialInterests":"\u003cb\u003eYes\u003c/b\u003e there is potential conflict of interest.","formattedTitle":"Impact of ELN clinical signs and symptoms on the thrombotic risk in Polycythemia Vera patients treated with front-line hydroxyurea","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePolycythemia vera (PV) is a Philadelphia chromosome-negative rare hematologic cancer belonging to the family of myeloproliferative neoplasms (MPN) and driven by mutations in the \u003cem\u003eJanus kinase 2\u003c/em\u003e (\u003cem\u003eJAK2\u003c/em\u003e) gene, most frequently the \u003cem\u003eJAK2\u003c/em\u003e\u003csup\u003eV617F\u003c/sup\u003e. The presence of an activating \u003cem\u003eJAK2\u003c/em\u003e mutation drives the aberrant proliferation of hematopoietic cells (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) leading to erythrocytosis, thrombocytosis, leukocytosis and increased cytokine production resulting in systemic symptoms typical of PV (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePatients with PV face a substantial risk of thrombotic complications, with a 2.7- to 13.1-fold higher likelihood of developing arterial and venous thrombosis, respectively, compared to age- and sex-matched controls (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Therefore, the clinical management of PV is focused on reducing the risk of such events, which remain the leading cause of morbidity and mortality.\u003c/p\u003e \u003cp\u003eAdvanced age and a history of previous thrombotic events are two well-established clinical risk factors for predicting future thromboembolic episodes (\u003cspan additionalcitationids=\"CR6 CR7 CR8\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Based on these two risk factors, patients with PV are currently classified as low-risk (LR) (absence of both risk factors) and high-risk (HR) (history of thrombosis and/or age\u0026thinsp;\u0026ge;\u0026thinsp;60 years) (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). However, a growing body of literature suggests that advanced age and prior thrombosis history may rather reflect a limited view of the overall risk profile and are sometimes perceived as suboptimal for proper management of PV. The fact that various biomarkers are currently investigated for risk assessment of PV (including but not limited to allelic ratio (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), RDW/neutrophil-lymphocyte ratio (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), and others) emphasizes the importance of improved risk stratification.\u003c/p\u003e \u003cp\u003eIn light of this evidence, the European LeukemiaNet (ELN) has recently indicated the use of cytoreductive therapy also in LR patients presenting specific clinical signs and symptoms (CSSs), including, but not limited to, intolerance to phlebotomy, uncontrolled hematocrit, symptomatic progressive splenomegaly, persistent and/or progressive leukocytosis, extreme thrombocytosis, relevant cardiovascular risk factors (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). However, the prognostic role of these factors remains so far elusive.\u003c/p\u003e \u003cp\u003eHydroxyurea (HU) is currently the most widely used cytoreductive therapy for PV patients (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), offering effective control of the disease and playing a key role in thrombosis prevention with generally acceptable tolerance (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn a large multicenter cooperative study, we assessed the impact of ELN clinical signs and symptoms on the thrombotic risk of PV patients homogeneously treated with first-line HU.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003ePatients\u0026rsquo; collection and study design\u003c/p\u003e \u003cp\u003eThis is an observational, retrospective cohort study (PV-ARC, NCT06134102) that was promoted by the IRCCS Azienda Ospedaliero-Universitaria S. Orsola-Malpighi, Bologna, Italy.\u003c/p\u003e \u003cp\u003eThe study now involves 1162 patients with PV diagnosed between January 1985 and December 2023. Among them, 739 patients were treated with first-line HU and had data on CSSs available at the start of HU.\u003c/p\u003e \u003cp\u003eFollowing approval of each IRB, participating centers collectively submitted diagnostic and follow-up information. The totality of medical files from each center was reported via data input into an electronic database that was developed to label all study data with an alphanumeric code after the de-identification of patients to protect personal privacy.\u003c/p\u003e \u003cp\u003eThe data collected included patient demographics, medications, clinical/laboratory tests at diagnosis and during follow-up, type of PV therapy and thromboses. All information about concomitant diseases, body mass index (BMI), cardiovascular risk factors (CVRFs), thrombosis history, and drug usage was recorded in each case history and, thereafter, used for retrospective evaluation. Any treatment decision, including the use of phlebotomies, HU and antiplatelet/anticoagulant drugs, was at the physician\u0026rsquo;s discretion and independent from participation in this study.\u003c/p\u003e \u003cp\u003eAfter the first data entry, follow-up information was validated with revision of the clinical data, and specific queries were addressed to the participating centers in cases of inconsistent data. All patients were followed until death or the data cut-off date (March 2024).\u003c/p\u003e \u003cp\u003eEthical Aspects\u003c/p\u003e \u003cp\u003e The PV-ARC study was performed in accordance with the guidelines of the IRBs of the participating centers and the standards of the Helsinki Declaration. For patients currently under follow-up with the experimental center, informed consent was obtained as part of one of the visits in their normal care pathway. For deceased patients, Italian regulations authorized the processing of personal data carried out for scientific research purposes (Gazzetta Ufficiale no. 72 dated 26 March 2012). Therefore, the processing of personal data is considered authorized upon approval of the study by the Ethics Committee. The promoter of this study was the IRCCS Azienda Ospedaliero-Universitaria S. Orsola-Malpighi, Bologna, which obtained approval from the Area Vasta Emilia Centro (AVEC) Ethics Committee (approval file number: 483/2018/Oss/AOUBo). This study was also approved by the local ethics committees of participating centers (protocol code: PV-ARC) and had no commercial support.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was carried out at the biostatistics laboratory of the MPN Unit, IRCCS Azienda Ospedaliero-Universitaria S. Orsola-Malpighi, Bologna.\u003c/p\u003e \u003cp\u003eContinuous variables are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), whereas categorical variables are presented as frequencies and percentages. Comparisons of quantitative variables between two groups of patients were carried out using the Wilcoxon\u0026ndash;Mann\u0026ndash;Whitney rank-sum test and among three groups using the Kruskal\u0026ndash;Wallis equality-of-populations rank test. Associations between categorical variables were tested using the χ2 test.\u003c/p\u003e \u003cp\u003eThe mean thrombotic risk scores associated with each CVRF were analyzed by a one-way analysis of variance (ANOVA).\u003c/p\u003e \u003cp\u003eA Poisson regression model was applied to calculate the incidence rate ratios (IRR) of thrombotic events. The IRR was described as the number of events per 100 patient-years (%p-y), considering the time between HU start and the first thrombotic event or last contact.\u003c/p\u003e \u003cp\u003eVariables associated with thrombotic events were identified using univariate and multivariate (MVA) Cox proportional hazards model. Hazard ratio (HR) has been reported with 95% confidence intervals (CI).\u003c/p\u003e \u003cp\u003eThrombosis-free survival (TFS) was assessed from HU start to the first thrombosis or last contact, using Kaplan-Meier analysis, adjusted for delayed entry, considering the time between PV diagnosis and the start of HU. Differences were evaluated with the log-rank test.\u003c/p\u003e \u003cp\u003eTests were two-sided and P values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered significant. Analyses were performed using STATA/SE software version 18.0 (StataCorp).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDefinitions\u003c/strong\u003e \u003cp\u003ePV was diagnosed according to the WHO 2022 classification (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). In patients diagnosed before 2022, bone marrow biopsies were internally reviewed to adhere the data to current criteria (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). In patients without a bone marrow histology, PV diagnosis was based on the presence of elevated hemoglobin levels (i.e., \u0026gt;\u0026thinsp;18.5 and 16.5 g/dL in males and females, respectively), the \u003cem\u003eJAK2\u003c/em\u003e Exon 14 or Exon 12 mutations, and low serum erythropoietin. Conventional criteria were used for the diagnosis of post Polycythemia Vera Myelofibrosis (PPV-MF) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e); leukemic transformation was defined by blast cells being at least 20% in peripheral blood and/or bone marrow, according to WHO criteria (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003eAccording to conventional criteria, LR patients were defined by age\u0026thinsp;\u0026lt;\u0026thinsp;60 years and no previous thrombotic history. HR patients were defined by age\u0026thinsp;\u0026ge;\u0026thinsp;60 years and/or a history of thromboembolism (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). In this analysis, HR patients were further stratified in two groups: HR-AGE (patients at high risk only due to age\u0026thinsp;\u0026ge;\u0026thinsp;60 years) and HR-THRO (patients at high risk due to previous thrombosis, regardless of age).\u003c/p\u003e \u003cp\u003eThromboses were defined according to the International Classification of Diseases (9th revision) (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) and graded according to the Common Terminology Criteria for Adverse Events (CTCAE) v5.0 (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Only grade\u0026thinsp;\u0026ge;\u0026thinsp;2 thromboses occurring during HU therapy were recorded and analyzed in the present study.\u003c/p\u003e \u003cp\u003eAt HU start, presence and type of CSSs were initially searched as per the ELN definition.(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) However, three criteria were adapted based on real-life experience. In particular: a platelet (PLT) count\u0026thinsp;\u0026gt;\u0026thinsp;1500 x10\u003csup\u003e9\u003c/sup\u003e/L was never observed in our cohort, so the threshold has been lowered to a PLT count\u0026thinsp;\u0026gt;\u0026thinsp;1000 x10\u003csup\u003e9\u003c/sup\u003e/L; for the same reason, the need for at least 6 phlebotomies (PHLs) for at least two years has been modified to at least 6 PHLs and/or a persistently higher hematocrit (HCT) of 50% for at least one year before HU start. This threshold was selected according to the results of the Cyto-PV trial, where patients randomized to maintain HCT 45\u0026ndash;50% had poorer outcomes (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn absence of a unified definition of \u0026ldquo;relevant\u0026rdquo; CVRF(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), the ANOVA test was used to identify the combination of CVRFs most strongly correlated with the risk of thrombosis. Five predefined CVRFs, namely active smoking, hypertension, overweight (BMI\u0026thinsp;\u0026ge;\u0026thinsp;25), diabetes, and dyslipidemia, were included in the analysis (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn summary, CSSs were defined as follows: 1) persistent/progressive leukocytosis: 100% increase if white blood cells (WBC)\u0026thinsp;\u0026lt;\u0026thinsp;10 x10\u003csup\u003e9\u003c/sup\u003e/L or 50% increase if WBC\u0026thinsp;\u0026ge;\u0026thinsp;10, or WBC\u0026thinsp;\u0026gt;\u0026thinsp;15 before HU start; 2) extreme thrombocytosis: PLT\u0026thinsp;\u0026gt;\u0026thinsp;1000 x10\u003csup\u003e9\u003c/sup\u003e/L at HU start; 3) progressive splenomegaly: increase by more than 5 cm below costal margin (BCM) in the year before HU start; 4) inadequate HCT control: \u0026ge;6 PHLs/year or HCT\u0026thinsp;\u0026ge;\u0026thinsp;50% at two evaluations within 1 year pre-HU start or PHL intolerance; 5) \u0026ldquo;relevant\u0026rdquo; CVRFs: co-occurrence of active smoking, hypertension and overweight (with or without the presence of diabetes and/or dyslipidemia); 6) severe itching.\u003c/p\u003e \u003cp\u003eThe presence and severity of itching at the start of HU were assessed during clinical visits. In recent years, the 10-item Myeloproliferative Neoplasm Symptom Assessment Form Total Symptom Score (MPN10-TSS) (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) has been used and \u0026ldquo;severe\u0026rdquo; itching was considered with a score\u0026thinsp;\u0026ge;\u0026thinsp;5 according to ELN definition. Alternatively, the itching score was considered\u0026thinsp;\u0026ge;\u0026thinsp;5 if refractory to specific medication (e.g., antihistamines).\u003c/p\u003e \u003cp\u003eAdditional reasons to start hydroxyurea were defined as follows: spleen palpable at 2\u0026ndash;5 cm below costal margin, mild leukocytosis or thrombocytosis (WBC\u0026thinsp;\u0026gt;\u0026thinsp;11 x10\u003csup\u003e9\u003c/sup\u003e/L or PLT\u0026thinsp;\u0026gt;\u0026thinsp;450 x10\u003csup\u003e9\u003c/sup\u003e/L but not meeting the definition of persistent/progressive or extreme), presence of microvascular disturbances despite appropriate phlebotomies and antiplatelet drug therapy (including vascular headaches, dizziness, visual disturbances, burning pain sensation in the palms of the hands and soles of the feet, distal paresthesia and acrocyanosis) (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), \u0026ge;\u0026thinsp;3 PHLs in the 12 months before HU start.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003ePatient cohort\u003c/p\u003e \u003cp\u003eOverall, 739 patients received treatment with first-line HU and were included in this analysis. At therapy start, 137 (18.5%) patients were categorized as LR and 602 (81.5%) as HR. Among them, 424 (70.4%) were HR-AGE and 178 (29.6%) were HR-THRO, with 46 (25.8%) patients only due to previous thrombosis and 132 (74.2%) due to both older age and previous thrombosis (\u003cb\u003eSupplemental Fig.\u0026nbsp;1\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eAt least one CVRF was present in 577 (78.1%) patients; specifically, 276 (37.3%), 181 (24.5%), 82 (11.1%) and 38 (5.1%) patients had one, two, three or \u0026ge;\u0026thinsp;4 CVRFs. The frequency of individual CVRFs and their inter-relationships are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003ea.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of Clinical Signs and Symptoms and Clinical Characteristics at Hydroxyurea Start\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLR\u003c/p\u003e \u003cp\u003e(n. 137)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e(n. 602)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003cp\u003e(LR vs. HR)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHR-AGE\u003c/p\u003e \u003cp\u003e(n. 424)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR-THRO\u003c/p\u003e \u003cp\u003e(n. 178)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eClinical Signs and Symptoms\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePresence of at least one Clinical Sign and Symptom, n. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e95 (69.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e348 (57.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e239 (56.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e109 (61.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePersistent/Progressive Leukocytosis, n. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e26 (19.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e63 (10.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (10.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (9.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExtreme Thrombocytosis, n. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e8 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eProgressive Splenomegaly, n. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e9 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e12 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eInadequate Hematocrit Control, n. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e57 (41.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e224 (37.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e156 (36.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68 (38.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRelevant Cardiovascular Risk Factors*, n. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e4 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e37 (6.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSevere Itching, n. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e58 (46.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e188 (31.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125 (29.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63 (36.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical Characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge, mean (\u0026plusmn;\u0026thinsp;SD), years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e50.9 (\u0026plusmn;\u0026thinsp;6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e69.5 (\u0026plusmn;\u0026thinsp;9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.1 (\u0026plusmn;\u0026thinsp;7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.6 (\u0026plusmn;\u0026thinsp;12.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHemoglobin, mean (\u0026plusmn;\u0026thinsp;SD), g/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e15.7 (\u0026plusmn;\u0026thinsp;2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e15.9 (\u0026plusmn;\u0026thinsp;1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.9 (\u0026plusmn;\u0026thinsp;1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.0 (\u0026plusmn;\u0026thinsp;2.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHematocrit, mean (\u0026plusmn;\u0026thinsp;SD), %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e50.4 (\u0026plusmn;\u0026thinsp;4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e50.3 (\u0026plusmn;\u0026thinsp;5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.3 (\u0026plusmn;\u0026thinsp;5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.3 (\u0026plusmn;\u0026thinsp;5.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLeukocytes count, mean (\u0026plusmn;\u0026thinsp;SD), x10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e13.1 (\u0026plusmn;\u0026thinsp;10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e10.8 (\u0026plusmn;\u0026thinsp;5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.8 (0.33\u0026ndash;77.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.7 (0.31\u0026ndash;38.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePlatelets count, mean (\u0026plusmn;\u0026thinsp;SD), x10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e622.8 (\u0026plusmn;\u0026thinsp;299.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e519.8 (\u0026plusmn;\u0026thinsp;249.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e528.2 (\u0026plusmn;\u0026thinsp;250.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e499.8 (\u0026plusmn;\u0026thinsp;247.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSpleen length, mean (\u0026plusmn;\u0026thinsp;SD), cm BCM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.48 (\u0026plusmn;\u0026thinsp;2.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.76 (\u0026plusmn;\u0026thinsp;1.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.66 (\u0026plusmn;\u0026thinsp;1.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.98 (\u0026plusmn;\u0026thinsp;2.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSmoke, n. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e30 (21.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e139 (23.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86 (20.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53 (29.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHypertension, n. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e41 (29.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e359 (59.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e258 (60.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101 (56.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDyslipidemia, n. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e22 (16.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e151 (25.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105 (24.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 (25.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDiabetes, n. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e7 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e69 (11.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (10.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverweight, n. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e40 (29.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e184 (30.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e126 (29.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58 (32.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTreated with antiplatelet/anticoagulants, n. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e131 (95.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e567 (94.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e396 (93.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e171 (96.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHU starting dose, mean (\u0026plusmn;\u0026thinsp;SD), mg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e739.2 (\u0026plusmn;\u0026thinsp;348.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e692.4 (\u0026plusmn;\u0026thinsp;314.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e709.9 (\u0026plusmn;\u0026thinsp;313.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e650.5 (\u0026plusmn;\u0026thinsp;315.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMaximum HU dose\u0026thinsp;\u0026ge;\u0026thinsp;1g/day, n. (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e96 (70.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e280 (46.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e206 (48.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74 (41.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe ANOVA scores for correlation with thrombosis were: 1.21, active smoking (IRR: 2.26%p-y); 1.15, hypertension (IRR: 1.83%p-y); 0.58, overweight (IRR: 1.93%p-y); 0.14, diabetes (IRR: 1.78%p-y) and 0.03, dyslipidemia (IRR: 1.79%p-y). In accordance with the findings of this test, patients with concomitant active smoking, hypertension and overweight were included in the \"relevant CVRFs\u0026rdquo; category (ANOVA score: 4.73; p\u0026thinsp;=\u0026thinsp;0.03). Overall, \"relevant\" CVRFs were present in 41 (5.5%) patients; in 15 of these patients, diabetes and/or dyslipidemia were also present.\u003c/p\u003e \u003cp\u003eAt HU start, CSSs were present in 443 (60.0%) patients, more frequently in LR (n. 95, 69.3%) compared to HR patients (n. 348, 57.8%, p\u0026thinsp;=\u0026thinsp;0.02), mainly due to higher presence of persistent/progressive leukocytosis (p\u0026thinsp;=\u0026thinsp;0.006), progressive splenomegaly (p\u0026thinsp;=\u0026thinsp;0.004) and severe itching (p\u0026thinsp;=\u0026thinsp;0.002) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe frequency of CSSs was comparable between HR-AGE (n. 239, 56.4%) and HR-THRO (n. 109, 61.2%) patients (p\u0026thinsp;=\u0026thinsp;0.27). This was also observed in HR-THRO patients due to both older age and previous thrombosis (62.1%) and HR-THRO patients due to previous thrombosis only (58.7%, p\u0026thinsp;=\u0026thinsp;0.69).\u003c/p\u003e \u003cp\u003eOverall, more than one CSS was present in 155 (out of 443, 35.0%) patients, mainly in low risk (43.2% vs. 32.8% HR, p\u0026thinsp;=\u0026thinsp;0.05). The frequency of individual CSS and their inter-relationships are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eb.\u003c/p\u003e \u003cp\u003eAt HU start, median leukocytes and platelet counts, and mean spleen length BCM were significantly higher in LR compared to HR patients, with no significant differences between HR-AGE and HR-THRO patients. Median HU starting dose was comparable across the three risk categories, while LR patients more frequently received a maximum dose\u0026thinsp;\u0026ge;\u0026thinsp;1g (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Anticoagulants were used more frequently in HR patients (12.3% vs. 4.4% LR, p\u0026thinsp;=\u0026thinsp;0.007). Conversely antiplatelets, excluding patients receiving anticoagulants, were used comparably across risk categories (LR: 95.4% vs. HR: 98.8%, p\u0026thinsp;=\u0026thinsp;0.21).\u003c/p\u003e \u003cp\u003eAdditional reasons for starting HU were present in 92.9% of patients without CSSs. Distribution of additional reasons according to conventional risk categories is shown in \u003cb\u003eSupplemental Table\u0026nbsp;1\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eThrombosis during hydroxyurea therapy\u003c/p\u003e \u003cp\u003eThe median time on HU was 6.2 years (SD\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3). During HU therapy, 72 patients had a thrombosis, for a total of 92 thrombotic events. Thromboses were equally distributed between arterial (n. 45, 48.9%) and venous (n. 47, 51.1%). \u003cb\u003eSupplemental Table\u0026nbsp;2\u003c/b\u003e details type and site of thrombotic events.\u003c/p\u003e \u003cp\u003eGlobally, the IRR of thrombosis during HU was 2.02%p-y and significantly higher (3.0%p-y) in HR-THRO patients (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Among HR-THRO patients, patients older than 60 years had the highest IRR of thrombosis (3.5%p-y).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIncidence ratio rate (IRR) per 100 patient-years of thromboses during treatment with hydroxyurea\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNumber of events\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eTotal cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eHR-AGE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eHR-THRO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003cp\u003e\u003cem\u003e(LR vs HR-AGE)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003cp\u003e\u003cem\u003e(LR vs HR-THRO)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003cp\u003e\u003cem\u003e(HR-AGE vs HR-THRO)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCSSs\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eNo CSSs\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eCSSs\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eNo CSSs\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eCSSs\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eNo CSSs\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eCSSs\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eNo CSSs\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eOverall thromboses\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e2.2*\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003e0.7*\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003e1.6*\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0*\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003e2.0*\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003e0.5*\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003e4.0*\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003e1.7*\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eArterial thromboses\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.8*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.3*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eVenous thromboses\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.0*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eImpact of clinical signs and symptoms on the incidence of thrombosis during hydroxyurea therapy\u003c/p\u003e \u003cp\u003eThe IRR of thrombosis was estimated according to the presence of CSSs, without considering the presence of additional reasons for starting HU.\u003c/p\u003e \u003cp\u003eIn the total cohort, CSSs were associated with a significantly increased IRR of thrombosis (2.2 vs. 0.7%p-y in patients without CSSs, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This was confirmed across all the risk categories (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTFS at 5 years was 88.6% in patients with CSSs compared to 96.2% in those without CSSs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Examining the three risk categories separately, the TFS curve of patients with CSSs was always significantly worse than that of patients without CSSs (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003eb, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). Across all risk categories, the best TFS at 5 years was observed in LR and HR-AGE (LR with no CSSs, 100%; HR-AGE with no CSSs: 98.1%). LR and HR-AGE patients with CSSs had comparable TFS than HR-THRO patients without CSSs (89.2%, 92.1% and 88.8%, respectively). HR-THRO patients with CSSs had the most dismal TFS (80.2%) (\u003cb\u003eSupplemental Fig.\u0026nbsp;2\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe prognostic impact of each individual CSS on the thrombotic risk was also explored.\u003c/p\u003e \u003cp\u003eIn univariate Cox analysis, history of thrombosis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), age\u0026thinsp;\u0026ge;\u0026thinsp;60 years (p\u0026thinsp;=\u0026thinsp;0.04), extreme thrombocytosis (p\u0026thinsp;=\u0026thinsp;0.01), progressive splenomegaly (p\u0026thinsp;=\u0026thinsp;0.05), inadequate hematocrit control (p\u0026thinsp;=\u0026thinsp;0.01), relevant CVRFs (p\u0026thinsp;=\u0026thinsp;0.01) were significantly associated with a higher thrombotic risk.\u003c/p\u003e \u003cp\u003eIn MVA, four factors maintained significant association with the thrombotic risk: inadequate hematocrit control (HR: 2.32, 95% CI: 1.45\u0026ndash;3.72, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); relevant CVRFs (HR: 2.87, 95% CI: 1.36\u0026ndash;6.06, p\u0026thinsp;=\u0026thinsp;0.006); progressive splenomegaly (HR: 4.02, 95% CI: 1.18\u0026ndash;13.65, p\u0026thinsp;=\u0026thinsp;0.03) and history of thrombosis (HR: 3.76, 95% CI: 2.32\u0026ndash;6.10, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eHU is the primary cytoreductive agent used in the treatment of PV and plays a crucial role in the overall anti-thrombotic strategy. Its use significantly reduces the incidence of thrombotic events; however, a notable number of events still occur, with an incidence rate of 3.3% p-y, which increases with age (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). The effectiveness of HU is greater in preventing initial or recurrent arterial events, but it has a higher failure rate in preventing venous events (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Therefore, it is essential to identify patient groups undergoing cytoreductive therapy who remain at an increased risk for thrombosis.\u003c/p\u003e \u003cp\u003eIn our cohort, the overall incidence of thrombosis during HU treatment is lower than what was estimated in the aforementioned meta-analysis, likely due to the younger median age of our patients, which includes LR patients. However, the incidence of recurrent thrombosis in the HR-THRO group (3% p-y) is comparable to the rate reported in the meta-analysis (4.5% p-y), indicating that the patients we studied reflect real-world scenarios.\u003c/p\u003e \u003cp\u003eIt has been more than two years since the publication of the ELN recommendations on the relevance of specific clinical signs and symptoms to consider for earlier therapy in conventionally defined low-risk PV patients (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). However, the strength of these recommendations remains weak due to a lack of specific data on the prognostic impact of such CSSs on the thrombotic risk.\u003c/p\u003e \u003cp\u003eOur results show that CSSs are common and significantly influence thrombotic risk, isolating a cohort of patients at further increased risk within each risk category. Additionally, three CSSs were more significantly associated with thrombosis: inadequate hematocrit control, relevant cardiovascular risk factors and progressive splenomegaly.\u003c/p\u003e \u003cp\u003eElevated hematocrit is one of the major risk factors for thrombosis in patients with PV (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). In the CYTO-PV study, patients with hematocrit below 45% had a lower incidence of deaths from cardiovascular causes or major thrombotic events (1.1 %p-y)than those with a target hematocrit of 45\u0026ndash;50% (4.4 %p-y)(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). A higher risk of thrombosis has also been observed in the subset of HU-treated patients requiring\u0026thinsp;\u0026ge;\u0026thinsp;3 phlebotomies per year (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere is a significant association between major thromboembolic events and hypertension, diabetes, hyperlipidemia, obesity and smoking (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan additionalcitationids=\"CR37 CR38\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Nevertheless, a consensus on which cardiovascular risk factors and/or combinations thereof should be designated as \"relevant\" in patients with PV remains elusive. As observed in this study, patients frequently exhibit multiple concomitant cardiovascular risk factors. These CVRFs often co-occur with other clinical signs and symptoms that correlate with the thrombotic risk, such as inadequate hematocrit control (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Furthermore, the impact of individual CVRFs can sometimes be masked by the thrombotic risk associated with PV, complicating the identification of a single CVRF that is associated with a heightened thrombotic risk. We ultimately adopted a composite definition, requiring the concurrent presence of at least three CVRFs, including smoke, hypertension, and overweight. This definition was derived from statistical associations with thrombotic risk and relative incidence rates ratio of thrombosis associated with each factor. From a biological perspective, this composite definition is more likely to reflect the synergistic effects of CVRFs. The potential for cumulative risk actions associated with the concurrent presence of two risk factors cannot be disregarded. However, this definition aligns with previous guidelines and may serve as a practical clinical guidance tool (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Overall, these findings recommend that CVRFs in all PV patients should be adequately controlled and reinforce the necessity of a multidisciplinary approach.\u003c/p\u003e \u003cp\u003eWe also observed a correlation between progressive splenomegaly and an increased risk of thrombosis. This correlation has been reported by previous groups (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) but not confirmed in other cohorts (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Overall, further investigation into the dynamic evaluation of the spleen may provide valuable insights for the management of PV.\u003c/p\u003e \u003cp\u003eHere, we could not confirm the association between thrombocytosis/leukocytosis and thrombosis. The number of platelets in PV outcomes is controversial, with some studies (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e), but not others (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e), reporting an association between higher platelet count and thrombosis. While in the ECLAP and in the CYTO-PV studies an association between leukocytosis and vascular events was noted (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e), hyperleukocytosis at diagnosis or during follow-up was not found to correlate with thrombotic risk in other studies (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). Neutrophil-to-lymphocyte ratio (NLR) values\u0026thinsp;\u0026ge;\u0026thinsp;5 was independently associated with an increased risk of venous thrombosis, which suggests that NLR, rather than leukocyte count alone, may be a valuable prognostic biomarker for thrombosis in PV and should be further investigated (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOverall, this analysis shows that multiple phlebotomies and/or persistently elevated hematocrit (\u0026gt;\u0026thinsp;50%), presence of relevant CVRFs and progressive splenomegaly are major determinants of thrombotic risk and should trigger therapeutic intervention, including multidisciplinary patient management and dynamic clinical-laboratory evaluation.\u003c/p\u003e \u003cp\u003eFinally, our study confirmed the pivotal role of thrombotic history, which appeared to be even more relevant than older age (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e). However, IRRs of thrombosis demonstrated a linear correlation between thrombotic risk and age. It is notable that the IRR for low-risk patients (aged under 60 with no previous history of thrombosis) is 1.1 %p-y, while he IRR for high-risk patients aged 60 or over (but with no previous thrombosis) is higher at 1.3 %p-y. This icidence is comparable to that of patients at high risk for a previous thrombotic history (but aged under 60 years), who have an IRR of 1.9 %p-y. The siultaneous presence of both risk factors identifies the highest risk category, with an IRR of 3.5 %p-y. The reults are comparable to those of the ECLAP study, which found that the IRRs of thrombosis were similar in older age groups without thrombosis (4.9 %p-y) and inyounger age groups with thrombosis (5.0 %p-y) (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIntrinsic limitations of the present study are due to its retrospective nature and include uncontrolled patient adherence to HU therapy, consistency in the assessment of CSSs, and reporting of thrombotic events, which may vary and affect the generalizability of the results. However, the study's robust sample size, its focus on real-world adaptations of the ELN recommendations and consistent findings across patient subgroups are its main strengths.\u003c/p\u003e \u003cp\u003eIn conclusion, CSSs may identify an increased risk phenotype across all thrombotic risk categories and may be actionable markers that can inform more aggressive and personalized management strategies. Furthermore, this study supports further research to investigate the integration of CSSs into existing risk models to improve prognostic accuracy and optimize treatment decisions in PV.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eThis work was supported by Ministero della Salute Ricerca corrente and by BolognAIL. \u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThe work reported in this publication was funded by Italian Ministry of Health, RC-2024-2790083 project.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eF.H.H.\u003c/strong\u003e was supported in part by grants of the German Research Council (DFG): HE6233/15-1 and 16-1, project number 517204983.\u003c/p\u003e\n\u003ch2\u003eAuthorship Contributions\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eFr.P.\u003c/strong\u003e: Conceptualization; Investigation; Funding acquisition; Writing - original draft; Writing - review \u0026amp; editing; Data curation; Resources; and Visualization. \u003cstrong\u003eF.B.\u003c/strong\u003e: Conceptualization, Writing - original draft; Writing - review \u0026amp; editing; Data curation; Formal analysis; and Visualization. \u003cstrong\u003eE.M., A.De., G.Be., M.T., G.A.P., M.Br., E.M.E., R.L., E.R., V.D.S\u003c/strong\u003e: Conceptualization; Investigation; Visualization; Writing - review \u0026amp; editing; Resources. \u003cstrong\u003eFr.C., A.T., M.Fa., A.D., E.A., Fa.C., R.M., A.C., B.M.:\u0026nbsp;\u003c/strong\u003eInvestigation; Writing - review \u0026amp; editing; and Resources. \u003cstrong\u003eF.H.H\u003c/strong\u003e: Visualization; Writing - review \u0026amp; editing\u003c/p\u003e\n\u003ch2\u003eCompeting Interests\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eFrancesca Palandri\u003c/strong\u003e participated in the speakers bureau and advisory board of Novartis, BMS, AOP, Sierra Oncology, Incyte, Telios, Abbvie, Constellation-Morphosys, Sobi and GSK. \u003cstrong\u003eGiulia Benevolo\u003c/strong\u003e reports honoraria from Novartis, Janssen, Amgen, Takeda, and BMS. \u003cstrong\u003eMassimo Breccia\u003c/strong\u003e reports honoraria from Novartis, BMS, Pfizer, Incyte. \u003cstrong\u003eGiuseppe A. Palumbo\u003c/strong\u003e reports consultancy and honoraria from Abbvie, AOP, AstraZeneca, BMS, Incyte, GSK, Morphosys, and Novartis. \u003cstrong\u003eMario Tiribelli\u003c/strong\u003e reports honoraria from and has served on speakers\u0026rsquo; bureaus for Novartis, BMS, Pfizer, and Incyte. \u003cstrong\u003eValerio De Stefano\u003c/strong\u003e participated in the speakers bureau and advisory board\u0026nbsp;of Abbvie,\u0026nbsp;AOP Health, Bristol Myers Squibb, Glaxo Smith Kline, Grifols, Novartis, Novo Nordisk, Sanofi, SOBI, Takeda. \u003cstrong\u003eFlorian H. Heidel\u003c/strong\u003e served as an advisor for Novartis, CTI, Celgene/BMS, Janssen, Abbvie, GSK, Merck and AOP and received research funding from Novartis, Celgene/BMS and CTI.\u003c/p\u003e\n\u003ch2\u003eData Availability Statement\u003c/h2\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request to the corresponding author ([email protected]).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDOI:\u0026nbsp;10.5281/zenodo.14017557.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFrancesca Palandri\u003c/strong\u003e participated in the speakers bureau and advisory board of Novartis, BMS, AOP, Sierra Oncology, Incyte, Telios, Abbvie, Constellation-Morphosys, Sobi and GSK. \u003cstrong\u003eGiulia Benevolo\u003c/strong\u003e reports honoraria from Novartis, Janssen, Amgen, Takeda, and BMS. \u003cstrong\u003eMassimo Breccia\u003c/strong\u003e reports honoraria from Novartis, BMS, Pfizer, Incyte. \u003cstrong\u003eGiuseppe A. Palumbo\u003c/strong\u003e reports consultancy and honoraria from Abbvie, AOP, AstraZeneca, BMS, Incyte, GSK, Morphosys, and Novartis. \u003cstrong\u003eMario Tiribelli\u003c/strong\u003e reports honoraria from and has served on speakers\u0026rsquo; bureaus for Novartis, BMS, Pfizer, and Incyte. \u003cstrong\u003eValerio De Stefano\u003c/strong\u003e participated in the speakers bureau and advisory board\u0026nbsp;of Abbvie,\u0026nbsp;AOP Health, Bristol Myers Squibb, Glaxo Smith Kline, Grifols, Novartis, Novo Nordisk, Sanofi, SOBI, Takeda. \u003cstrong\u003eFlorian H. Heidel\u003c/strong\u003e served as an advisor for Novartis, CTI, Celgene/BMS, Janssen, Abbvie, GSK, Merck and AOP and received research funding from Novartis, Celgene/BMS and CTI.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePerner F, Perner C, Ernst T, Heidel FH. Roles of JAK2 in Aging, Inflammation, Hematopoiesis and Malignant Transformation. Cells. 2019;8(8).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTefferi A, Barbui T. Polycythemia vera: 2024 update on diagnosis, risk-stratification, and management. Am J Hematol. 2023;98(9):1465\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWaggoner, MS, PA-C M. Polycythemia Vera: Thinking Beyond the Hematocrit. J Adv Pract Oncol. 2023;14(5):405.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHultcrantz M, Bj\u0026ouml;rkholm M, Dickman PW, Landgren O, Derolf \u0026Aring;R, Kristinsson SY, et al. Risk for Arterial and Venous Thrombosis in Patients With Myeloproliferative Neoplasms: A Population-Based Cohort Study. Ann Intern Med. 2018;168(5):317\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLandolfi R, Di Gennaro L, Barbui T, De Stefano V, Finazzi G, Marfisi R, et al. Leukocytosis as a major thrombotic risk factor in patients with polycythemia vera. Blood. 2007;109(6):2446\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFinazzi G. A prospective analysis of thrombotic events in the European collaboration study on low-dose aspirin in polycythemia (ECLAP). Pathologie Biologie. 2004;52(5):285\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEnblom-Larsson A, Renlund H, Andr\u0026eacute;asson B, Holmberg H, Liljeholm M, Sj\u0026auml;lander A. Thromboembolic events, major bleeding and mortality in essential thrombocythaemia and polycythaemia vera-A matched nationwide population-based study. Br J Haematol. 2024;204(5):1740\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCerquozzi S, Barraco D, Lasho T, Finke C, Hanson CA, Ketterling RP, et al. Risk factors for arterial versus venous thrombosis in polycythemia vera: a single center experience in 587 patients. Blood Cancer Journal 2017 7:12. 2017;7(12):1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarbui T, Carobbio A, Rumi E, Finazzi G, Gisslinger H, Rodeghiero F, et al. In contemporary patients with polycythemia vera, rates of thrombosis and risk factors delineate a new clinical epidemiology. Blood. 2014;124(19):3021\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMasarova L, Chifotides HT. SOHO State of the Art Update and Next Questions: Novel Therapies for Polycythemia Vera. Clin Lymphoma Myeloma Leuk. 2024;24(3):141\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarbui T, Tefferi A, Vannucchi AM, Passamonti F, Silver RT, Hoffman R, et al. Philadelphia chromosome-negative classical myeloproliferative neoplasms: revised management recommendations from European LeukemiaNet. Leukemia. 2018;32(5):1057\u0026ndash;69.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuglielmelli P, Mora B, Gesullo F, Mannelli F, Loscocco GG, Signori L, et al. Clinical impact of mutated JAK2 allele burden reduction in polycythemia vera and essential thrombocythemia. Am J Hematol. 2024;99(8):1550\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuglielmelli P, Loscocco GG, Mannarelli C, Rossi E, Mannelli F, Ramundo F, et al. JAK2V617F variant allele frequency\u0026thinsp;\u0026gt;\u0026thinsp;50% identifies patients with polycythemia vera at high risk for venous thrombosis. Blood Cancer J. 2021;11(12).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarbui T, Carobbio A, Guglielmelli P, Ghirardi A, Fenili F, Loscocco GG, et al. Neutrophil/lymphocyte ratio identifies low-risk polycythaemia vera patients for early Ropeginterferon alfa-2b therapy. Br J Haematol. 2024;205(6).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerstovsek S, Krečak I, Heidel FH, De Stefano V, Bryan K, Zuurman MW, et al. Identifying Patients with Polycythemia Vera at Risk of Thrombosis after Hydroxyurea Initiation: The Polycythemia Vera-Advanced Integrated Models (PV-AIM) Project. Biomedicines. 2023;11(7)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarchetti M, Vannucchi AM, Griesshammer M, Harrison C, Koschmieder S, Gisslinger H, et al. Appropriate management of polycythaemia vera with cytoreductive drug therapy: European LeukemiaNet 2021 recommendations. Lancet Haematol. 2022;9(4):e301\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCrodel CC, Jentsch-Ullrich K, Reiser M, Jacobasch L, Sauer A, Tesch H, et al. Cytoreductive treatment in real life: a chart review analysis on 1440 patients with polycythemia vera. J Cancer Res Clin Oncol. 2022;148(10):2693\u0026ndash;705.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJentsch-Ullrich K, Eberhardt J, Zeremski V, Koehler M, Wolleschak D, Heidel FH. Characteristics and treatment of polycythemia vera patients in clinical practice: a multicenter chart review on 1476 individuals in Germany. J Cancer Res Clin Oncol. 2016;142(9):2041\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePodoltsev NA, Zhu M, Zeidan AM, Wang R, Wang X, Davidoff AJ, et al. The impact of phlebotomy and hydroxyurea on survival and risk of thrombosis among older patients with polycythemia vera. Blood Adv. 2018;2(20):2681.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGilbert HS. Current management in polycythemia vera. Semin Hematol. 2001;38(1 Suppl 2):25\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArber DA, Orazi A, Hasserjian RP, Borowitz MJ, Calvo KR, Kvasnicka HM, et al. International Consensus Classification of Myeloid Neoplasms and Acute Leukemias: integrating morphologic, clinical, and genomic data. Blood. 2022;140(11):1200\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarosi G, Mesa RA, Thiele J, Cervantes F, Campbell PJ, Verstovsek S, et al. Proposed criteria for the diagnosis of post-polycythemia vera and post-essential thrombocythemia myelofibrosis: a consensus statement from the International Working Group for Myelofibrosis Research and Treatment. Leukemia. 2008;22(2):437\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMora B, Passamonti F. SOHO State of the Art Updates and Next Questions | Polycythemia Vera: Is It Time to Rethink Treatment? Clin Lymphoma Myeloma Leuk. 2023;23(2):79\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSlee VN. The International Classification of Diseases: ninth revision (ICD-9). Ann Intern Med. 1978;88(3):424\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCancer Institute N. Common Terminology Criteria for Adverse Events (CTCAE) Common Terminology Criteria for Adverse Events (CTCAE) v5.0. 2017\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarchioli R, Finazzi G, Specchia G, Masciulli A, Mennitto MR, Barbui T. The CYTO-PV: A Large-Scale Trial Testing the Intensity of CYTOreductive Therapy to Prevent Cardiovascular Events in Patients with Polycythemia Vera. Thrombosis. 2011;2011:1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreenlund KJ, Zheng ZJ, Keenan NL, Giles WH, Casper ML, Mensah GA, et al. Trends in self-reported multiple cardiovascular disease risk factors among adults in the United States, 1991\u0026ndash;1999. Arch Intern Med. 2004;164(2):181\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsao CW, Vasan RS. Cohort Profile: The Framingham Heart Study (FHS): overview of milestones in cardiovascular epidemiology. Int J Epidemiol. 2015;44(6):1800\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEmanuel RM, Dueck AC, Geyer HL, Kiladjian JJ, Slot S, Zweegman S, et al. Myeloproliferative neoplasm (MPN) symptom assessment form total symptom score: prospective international assessment of an abbreviated symptom burden scoring system among patients with MPNs. J Clin Oncol. 2012;30(33):4098\u0026ndash;103.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Stefano V, Za T, Rossi E, Vannucchi AM, Ruggeri M, Elli E, et al. Recurrent thrombosis in patients with polycythemia vera and essential thrombocythemia: incidence, risk factors, and effect of treatments. Haematologica. 2008;93(3):372\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerrari A, Carobbio A, Masciulli A, Ghirardi A, Finazzi G, de Stefano V, et al. Clinical outcomes under hydroxyurea treatment in polycythemia vera: a systematic review and meta-analysis. Haematologica. 2019;104(12):2391\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Stefano V, Rossi E, Carobbio A, Ghirardi A, Betti S, Finazzi G, et al. Hydroxyurea prevents arterial and late venous thrombotic recurrences in patients with myeloproliferative neoplasms but fails in the splanchnic venous district. Pooled analysis of 1500 cases. Blood Cancer Journal. 2018;8(11):1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarbui T, De Stefano V, Ghirardi A, Masciulli A, Finazzi G, Vannucchi AM. Different effect of hydroxyurea and phlebotomy on prevention of arterial and venous thrombosis in Polycythemia Vera. Blood Cancer J. 2018;8(12).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarchioli R, Finazzi G, Specchia G, Cacciola R, Cavazzina R, Cilloni D, et al. Cardiovascular events and intensity of treatment in polycythemia vera. N Engl J Med. 2013;368(1):22\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlvarez-Larr\u0026aacute;n A, P\u0026eacute;rez-Encinas M, Ferrer-Mar\u0026iacute;n F, Hern\u0026aacute;ndez-Boluda JC, Jos\u0026eacute; Ram\u0026iacute;rez M, Mart\u0026iacute;nez-L\u0026oacute;pez J, et al. Risk of thrombosis according to need of phlebotomies in patients with polycythemia vera treated with hydroxyurea. Haematologica. 2017;102(1):103\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenevolo G, Elli EM, Bartoletti D, Latagliata R, Tiribelli M, Heidel FH, et al. Impact of comorbidities and body mass index on the outcome of polycythemia vera patients. Hematol Oncol. 2021;39(3):409\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarbui T, Vannucchi AM, Carobbio A, Rumi E, Finazzi G, Gisslinger H, et al. The effect of arterial hypertension on thrombosis in low-risk polycythemia vera. Am J Hematol. 2017;92(1):E5\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHorvat I, Boban A, Zadro R, Antolic MR, Serventi-Seiwerth R, Roncevic P, et al. Influence of Blood Count, Cardiovascular Risks, Inherited Thrombophilia, and JAK2 V617F Burden Allele on Type of Thrombosis in Patients With Philadelphia Chromosome Negative Myeloproliferative Neoplasms. Clin Lymphoma Myeloma Leuk. 2019;19(1):53\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKomatsu N, Jun GJ, Yonezu T, Ohashi Y. Real-world, retrospective study evaluating thromboembolic events, associated risk factors, and health-care resource utilization in Japanese patients with polycythemia vera. Int J Hematol. 2020;112(2):176\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCosentino F, Grant PJ, Aboyans V, Bailey CJ, Ceriello A, Delgado V, et al. 2019 ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD. Eur Heart J. 2020;41(2):255\u0026ndash;323.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee MW, Yeon SH, Ryu H, Song IC, Lee HJ, Yun HJ, et al. Volumetric Splenomegaly in Patients With Polycythemia Vera. J Korean Med Sci. 2022;37(11):e87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarbui T, Masciulli A, Marfisi MR, Tognoni G, Finazzi G, Rambaldi A, et al. White blood cell counts and thrombosis in polycythemia vera: a subanalysis of the CYTO-PV study. Blood. 2015;126(4):560\u0026ndash;1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Stefano V, Za T, Rossi E, Vannucchi AM, Ruggeri M, Elli E, et al. Leukocytosis is a risk factor for recurrent arterial thrombosis in young patients with polycythemia vera and essential thrombocythemia. Am J Hematol. 2010;85(2):97\u0026ndash;100.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRonner L, Podoltsev N, Gotlib J, Heaney ML, Kuykendall AT, O\u0026rsquo;Connell C, et al. Persistent leukocytosis in polycythemia vera is associated with disease evolution but not thrombosis. Blood. 2020;135(19):1696\u0026ndash;703.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarobbio A, Vannucchi AM, De Stefano V, Masciulli A, Guglielmelli P, Loscocco GG, et al. Neutrophil-to-lymphocyte ratio is a novel predictor of venous thrombosis in polycythemia vera. Blood Cancer J. 2022;12(2):28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarchioli R, Finazzi G, Landolfi R, Kutti J, Gisslinger H, Patrono C, et al. Vascular and neoplastic risk in a large cohort of patients with polycythemia vera. J Clin Oncol. 2005;23(10):2224\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"leukemia","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"leu","sideBox":"Learn more about [Leukemia](http://www.nature.com/leu/)","snPcode":"41375","submissionUrl":"https://mts-leu.nature.com/cgi-bin/main.plex","title":"Leukemia","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6252512/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6252512/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe European LeukemiaNet recently proposed specific Clinical Signs and Symptoms (CSSs) that should be considered to trigger cytoreduction in patients with polycythemia vera (PV) at low risk (LR) according to conventional criteria (age\u0026lt;60 years and no previous thrombosis).\u003c/p\u003e\n\u003cp\u003eTo evaluate the impact of CSSs on the thrombotic risk across different risk categories, including LR, high risk by age only (HR-AGE) or previous thrombosis (HR-THRO), we conducted a multicenter cooperative study (NCT06134102) involving 739 PV patients treated with first-line hydroxyurea. CSSs, including persistent/progressive leukocytosis, extreme thrombocytosis, progressive splenomegaly, inadequate hematocrit control, relevant cardiovascular risk factors (CVRFs), and severe itching, were evaluated for association with thrombosis using incidence rate ratio (IRR) per 100 patient-years (%p-y) and thrombosis-free survival (TFS) adjusted for delayed entry.\u003c/p\u003e\n\u003cp\u003eAt hydroxyurea start, 443 patients (60.0%) had at least one CSS. In patients with and without CSSs, the IRR of thrombosis was 2.2 and 0.7 %p-y, respectively (p\u0026lt;0.001), and the TFS at 5 years was 88.7% and 96.1% (p\u0026lt;0.001). The prognostic impact of CSSs was confirmed in all risk categories, with worse TFS in HR-THRO patients with CSSs.\u003c/p\u003e\n\u003cp\u003eIn multivariate analysis including each CSS singularly, inadequate hematocrit control (HR: 2.32, 95% CI: 1.45 – 3.72, p\u0026lt;0.001); relevant CVRFs (HR: 2.87, 95% CI: 1.36 – 6.06, p=0.006); progressive splenomegaly (HR: 4.02, 95% CI: 1.18 – 13.65, p=0.03) and previous thrombosis (HR: 3.76, 95% CI: 2.32 – 6.10, p\u0026lt;0.001) remained significantly associated with thrombotic risk.\u003c/p\u003e\n\u003cp\u003eCSSs identify an increased thrombotic risk phenotype in all conventionally defined risk categories, supporting their evaluation in clinical practice.\u003c/p\u003e","manuscriptTitle":"Impact of ELN clinical signs and symptoms on the thrombotic risk in Polycythemia Vera patients treated with front-line hydroxyurea","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-31 11:08:04","doi":"10.21203/rs.3.rs-6252512/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2025-04-02T12:47:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-04-01T14:09:29+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-03-30T16:23:59+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-03-24T02:12:21+00:00","index":3,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2025-03-22T16:49:55+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-03-20T06:59:48+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2025-03-19T15:20:18+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2025-03-19T15:18:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-19T11:24:26+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-19T11:24:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"Leukemia","date":"2025-03-18T11:08:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"leukemia","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"leu","sideBox":"Learn more about [Leukemia](http://www.nature.com/leu/)","snPcode":"41375","submissionUrl":"https://mts-leu.nature.com/cgi-bin/main.plex","title":"Leukemia","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b00db037-6c8d-4fed-a335-5fee8cfa2707","owner":[],"postedDate":"March 31st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":45920686,"name":"Health sciences/Risk factors"},{"id":45920687,"name":"Health sciences/Signs and symptoms"},{"id":45920688,"name":"Health sciences/Diseases/Haematological diseases/Haematological cancer/Myeloproliferative disease"}],"tags":[],"updatedAt":"2025-05-29T07:09:00+00:00","versionOfRecord":{"articleIdentity":"rs-6252512","link":"https://doi.org/10.1038/s41375-025-02646-y","journal":{"identity":"leukemia","isVorOnly":false,"title":"Leukemia"},"publishedOn":"2025-05-28 04:00:00","publishedOnDateReadable":"May 28th, 2025"},"versionCreatedAt":"2025-03-31 11:08:04","video":"","vorDoi":"10.1038/s41375-025-02646-y","vorDoiUrl":"https://doi.org/10.1038/s41375-025-02646-y","workflowStages":[]},"version":"v1","identity":"rs-6252512","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6252512","identity":"rs-6252512","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}