ReviewJournal of thrombosis and thrombolysis2026
Tyrosine kinase inhibitors - balancing the haemostatic scales: a review of associated thrombosis and bleeding.
Review in Journal of thrombosis and thrombolysis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Repurposing Tyrosine Kinase Inhibitors for Sickle Cell Disease: Focus on Band 3 Phosphorylation.Biomedicines · 2026Review
- Risks of Retinal Vascular Occlusions with the Systemic Use of Tyrosine Kinase Inhibitors.Ophthalmology. Retina · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tyrosine kinase inhibitors (TKIs) have revolutionised cancer therapy, significantly impacting survival and outcomes by targeting specific signalling pathways that are necessary for tumour survival. Despite their clinical efficacy, TKIs exhibit a complex toxicity profile. Many of the signalling pathways that are targeted by TKIs are shared with normal homeostatic processes, including those responsible for modulating thrombosis and bleeding. The risk profile of thrombosis and bleeding associated with TKIs varies considerably across agents. Multi-kinase inhibitors, particularly those targeting the breakpoint cluster regio-abelson murine leukaemia 1 gene mutation (BCR-ABL) (i.e., nilotinib and ponatinib), significantly elevate arterial thrombotic events. This thrombosis risk is driven by endothelial dysfunction, accelerated atherosclerosis, platelet hyper-reactivity, and impaired fibrinolysis. Similarly, vascular endothelial growth factor (VEGF) pathway inhibition contributes markedly to thrombotic vascular complications by reducing vasodilators like nitric oxide and promoting pro-thrombotic endothelial environments. TKIs targeting the VEGF receptor (VEGFR-TKIs) (i.e., sunitinib and regorafenib) and brutons tyrosine kinase (BTK) inhibitors (i.e., ibrutinib), increase bleeding risk through platelet dysfunction, thrombocytopenia, and interactions affecting coagulation pathways. Optimal management of these medications encompasses careful baseline cardiovascular and bleeding risk assessments, proactive modification of modifiable risk factors, and vigilant patient monitoring. Prophylactic antithrombotic therapy necessitates cautious individualised evaluation and comprehensive patient monitoring strategies. TKIs exemplify the advancements in precision oncology but necessitate nuanced management of their complex vascular toxicities. A multidisciplinary cardio-oncology approach involving detailed patient education, robust risk stratification, and collaborative clinical management is essential. Future research should aim to clarify TKI-specific haemostatic mechanisms and develop predictive biomarkers, enabling tailored therapeutic strategies to optimise clinical outcomes and reduce adverse events..
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.