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September 10, 2010Blood780 citationsOpen Access

Prediction of venous thromboembolism in cancer patients

CACihan AyCardio-OncologyDDDaniela DunklerMedical University of ViennaCMChristine MarosiGoethe University Frankfurt

Key Points

  • This research aims to enhance the prediction of venous thromboembolism (VTE) in cancer patients by integrating biomarkers into a risk scoring model.
  • Conducted a prospective observational cohort study of newly diagnosed cancer patients or those with disease progression (N=819).

Structured PICO

Does an expanded risk scoring model including soluble P-selectin and D-Dimer improve prediction of venous thromboembolism in cancer patients?

P
Population
819 patients with newly diagnosed cancer or progression of disease after remission
I
Intervention
Expanded risk scoring model incorporating clinical parameters (tumor entity, body mass index), laboratory parameters (hemoglobin level, thrombocyte and leukocyte count), and 2 biomarkers (soluble P-selectin, D-Dimer)
C
Comparator
Previously developed original risk scoring model (clinical and laboratory parameters only)
O
Outcome
Venous thromboembolism (VTE)hard clinical

The addition of soluble P-selectin and D-Dimer to clinical and standard laboratory parameters significantly improves the identification of cancer patients at high risk for venous thromboembolism.

Abstract

The risk of venous thromboembolism (VTE) is increased in cancer patients. To improve prediction of VTE in cancer patients, we performed a prospective and observational cohort study of patients with newly diagnosed cancer or progression of disease after remission. A previously developed risk scoring model for prediction of VTE that included clinical (tumor entity and body mass index) and laboratory (hemoglobin level and thrombocyte and leukocyte count) parameters was expanded by incorporating 2 biomarkers, soluble P-selectin, and D-Dimer. Of 819 patients 61 (7.4%) experienced VTE during a median follow-up of 656 days. The cumulative VTE probability in the original risk model after 6 months was 17.7% in patients with the highest risk score (≥ 3, n = 93), 9.6% in those with score 2 (n = 221), 3.8% in those with score 1 (n = 229), and 1.5% in those with score 0 (n = 276). In the expanded risk model, the cumulative VTE probability after 6 months in patients with the highest score (≥ 5, n = 30) was 35.0% and 10.3% in those with an intermediate score (score 3, n = 130) as opposed to only 1.0% in patients with score 0 (n = 200); the hazard ratio of patients with the highest compared with those with the lowest score was 25.9 (8.0-84.6). Clinical and standard laboratory parameters with addition of biomarkers enable prediction of VTE and allow identification of cancer patients at high or low risk of VTE.

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Cite This Study

Ay et al. (2010) studied this question.

synapsesocial.com/papers/69f933775a4050c311d4b18ahttps://doi.org/10.1182/blood-2010-02-270116
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