Retrospective Review of Prescribing Patterns in Cancer-Associated Thrombosis: A Single Center Experience in Edmonton, Alberta, Canada
Bibliographic record
Abstract
Low molecular weight heparin (LMWH) is the standard of care for treating cancer-associated thrombosis (CAT), although new evidence for direct oral anticoagulants (DOACs) supports use in specific cancer populations. In this retrospective review at a specialty CAT clinic from 2016 to 2019, we report the use of anticoagulants (LMWH, DOACs, warfarin, anticoagulant class change) in the acute and chronic phases of CAT and compare use before/after publication of the Hokusai-VTE Cancer trial. Death, venous thromboembolism (VTE) recurrence and bleeding was also reported. Of the 221 included, median age was 69 years, with 57.5% having metastatic disease. In the acute phase, 80.1% were prescribed LMWH, 4.1% DOAC, and 14.5% had an anticoagulant class change (LMWH to DOAC; 78.1%). In the chronic phase, 35.8% were prescribed LMWH, 11.3% DOAC, and 42.9% had an anticoagulant class change (LMWH to DOAC; 90.1%). Use of DOACs in the acute and chronic phase prior to the Hokusai-VTE trial was 1.0% and 2.0%, respectively, and following publication was 6.8% and 19.6%. Death occurred for 22.6% patients, recurrent VTE in 7.2%, and bleeding in 5.0%. DOAC use is increasing with time; real-world data may help to guide optimization of the care of complex patients.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.023 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".