8 research outputs found

    Expected individual benefit of prophylactic platelet transfusions in hemato-oncology patients based on bleeding risks

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    Background: Prophylactic platelet transfusions prevent bleeding in hematooncology patients, but it is unclear how any benefit varies between patients. Our aim was to assess if patients with different baseline risks for bleeding benefit differently from a prophylactic platelet transfusion strategy. Study design and methods: Using the data from the randomized controlled TOPPS trial (Trial of Platelet Prophylaxis), we developed a prediction model for World Health Organization grades 2, 3, and 4 bleeding risk (defined as at least one bleeding episode in a 30 days period) and grouped patients in four risk-quartiles based on this predicted baseline risk. Predictors in the model were baseline platelet count, age, diagnosis, disease modifying treatment, disease status, previous stem cell transplantation, and the randomization arm. Results: The model had a c-statistic of 0.58 (95% confidence interval [CI] 0.54– 0.64). There was little variation in predicted risks (quartiles 46%, 47%, and 51%), but prophylactic platelet transfusions gave a risk reduction in all risk quartiles. The absolute risk difference (ARD) was 3.4% (CI 12.2 to 18.9) in the lowest risk quartile (quartile 1), 7.4% (95% CI 8.4 to 23.3) in quartile 2, 6.8% (95% CI 9.1 to 22.9) in quartile 3, and 12.8% (CI 3.1 to 28.7) in the highest risk quartile (quartile 4). Conclusion: In our study, generally accepted bleeding risk predictors had limited predictive power (expressed by the low c-statistic), and, given the wide confidence intervals of predicted ARD, could not aid in identifying subgroups of patients who might benefit more (or less) from prophylactic platelet transfusionClinical epidemiolog

    Prophylactic platelet transfusions: why less is more

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    In short, given the current evidence base, we recommend the use of restrictive platelet transfusion thresholds while awaiting the results of new/ongoing studies and large-scale epidemiologic studies. Future trialists will have an opportunity to address the identified challenges and additionally improve the efficiency and design of these trials using electronic patient data and advanced trial designs. There clearly is a need for new biomarkers and models to better predict bleeding risk for more tailored platelet transfusion decisions, implementation strategies to support evidence-based transfusion practices, and fundamental research to better understand the mechanisms of transfusion-related harm.Developmen
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