Cancer complicated by thrombosis and thrombocytopenia: still a therapeutic dilemma
Bibliographic record
Abstract
Individuals who have thrombocytopenia and cancer-associated thrombosis (CAT) are difficult to manage because they have a high risk of bleeding and recurrent thrombosis. The International Society on Thrombosis and Haemostasis guidelines for the management of thrombocytopenia in patients with CAT suggest two main approaches: either complete anticoagulation with transfusion support if necessary, or dose-modified anticoagulation while the platelet count is <50×109/L. Nevertheless, rather than being based on information from randomized controlled trials (RCTs), these recommendations were based on expert consensus. Recent research from two different countries has shown how this cohort’s management and results vary widely. While the United Kingdom study, Cancer-Associated Venous Thrombosis and Thrombocytopenia, found no significant differences in bleeding or recurrent thrombosis between full dose and modified dose groups, the North American Thrombocytopenia Related Outcomes with Venous thromboembolism study demonstrated a significantly lower risk of bleeding events in those receiving modified dose anticoagulation compared to full dose, without an increased risk of recurrent VTE. Therefore, an RCT is required to assess the best course of action for patients with CAT and thrombocytopenia. To define the standard of care for the management of patients with CAT and thrombocytopenia, a full-scale trial called the START randomized trial (STrategies for Anticoagulation in patients with thRombocytopenia and cancer-associated Thrombosis) is an international, multi-site pilot study that compares the use of platelet transfusions plus higher dose anticoagulation to modified dose anticoagulation in patients with thrombocytopenia and CAT receiving anticoagulation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.016 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".