QRISK3 score is predictive of thrombotic risk in patients with myeloproliferative neoplasms

Thromboembolic events (TE) represent the commonest cause of morbidity and mortality in polycythemia vera (PV) and essential thrombocythaemia (ET). The QRISK3 model is a tool for predicting TE in the general population, with 7.5% recognised as a threshold to identify high-risk patients. We analyzed data of 937 patients (490 ET and 447 PV) with a median follow-up of 85 and 95 months, reporting an occurrence of 52 and 73 TE, respectively. Median QRISK3 scores at diagnosis were higher in conventional high-risk patients in both cohorts (ET; 4.2 in high-risk vs. 2.4 in low-risk, PV; 8.8 vs. 2.8, p < 0.001). During follow-up, a QRISK3 score greater than 7.5%, demonstrated potential to further stratify individuals at high risk of TE, outperforming standard risk assessments in both low and high-risk patients. Using cytoreductive treatment instead of active surveillance in patients with QRISK3 ≥ 7.5% conferred a reduced risk of thrombosis in both cohorts. Of this group, 79.7% with ET and 86.9% with PV, on cytoreductive therapy, remained thrombosis free, compared with 64.1% and 57.1% of those not receiving cytoreductive therapy (p = 0.018/0.034). QRISK3 identifies patients in whom cytoreductive therapies may be indicated, and provides a tool that allows patients to assess, monitor and reduce their cardiovascular risk.

Authors

Institutions

Publication Details

Journal
Leukemia
Published
2025-07-24
DOI
https://doi.org/10.1038/s41375-025-02681-9
Citations
5
Primary Topic
Myeloproliferative Neoplasms: Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
8.13
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

QRISK3 score is predictive of thrombotic risk in patients with myeloproliferative neoplasms

Priya Sriskandarajah, Jennifer O’Sullivan, Deepti H. Radia, Susan Asirvatham et al.
5 citations
Leukemia
Myeloproliferative Neoplasms: Diagnosis and Treatment
8.13
article

QRISK3 score is predictive of thrombotic risk in patients with myeloproliferative neoplasms

Priya Sriskandarajah, Jennifer O’Sullivan, Deepti H. Radia, Susan Asirvatham, Natalia Curto‐García, Claire N. Harrison, Shahram Kordasti, Patrick Harrington, Giuseppe A. Palumbo, Hugues de Lavallade, Claire Woodley, Andrea Duminuco, Raj Vaghela, Sukhraj Virdee
article en
5 citations

Abstract

Thromboembolic events (TE) represent the commonest cause of morbidity and mortality in polycythemia vera (PV) and essential thrombocythaemia (ET). The QRISK3 model is a tool for predicting TE in the general population, with 7.5% recognised as a threshold to identify high-risk patients. We analyzed data of 937 patients (490 ET and 447 PV) with a median follow-up of 85 and 95 months, reporting an occurrence of 52 and 73 TE, respectively. Median QRISK3 scores at diagnosis were higher in conventional high-risk patients in both cohorts (ET; 4.2 in high-risk vs. 2.4 in low-risk, PV; 8.8 vs. 2.8, p < 0.001). During follow-up, a QRISK3 score greater than 7.5%, demonstrated potential to further stratify individuals at high risk of TE, outperforming standard risk assessments in both low and high-risk patients. Using cytoreductive treatment instead of active surveillance in patients with QRISK3 ≥ 7.5% conferred a reduced risk of thrombosis in both cohorts. Of this group, 79.7% with ET and 86.9% with PV, on cytoreductive therapy, remained thrombosis free, compared with 64.1% and 57.1% of those not receiving cytoreductive therapy (p = 0.018/0.034). QRISK3 identifies patients in whom cytoreductive therapies may be indicated, and provides a tool that allows patients to assess, monitor and reduce their cardiovascular risk.

LeukemiaVol. 39(10)
King's College London (GB), Guy's and St Thomas' NHS Foundation Trust (GB), University of Catania (IT)
Good health and well-being
Openalex Percentile: Top 2%
Myeloproliferative Neoplasms: Diagnosis and Treatment
8.13
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.