Direct oral anticoagulant (DOAC) versus low-molecular-weight heparin (LMWH) for treatment of cancer associated thrombosis (CAT): A systematic review and meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: It is unclear if direct oral anticoagulants (DOACs) are effective and safe alternatives to low-molecular-weight heparin (LMWHs) for the treatment of cancer-associated venous thromboembolism (VTE). We aim to synthesize existing literature that compared DOACs versus LMWHs in this high-risk population. MATERIALS AND METHODS: We conducted a systematic review using EMBASE, MEDLINE and CENTRAL for all observational studies and randomized controlled trials (RCTs) (PROSPERO: CRD42017080898). Two authors independently reviewed study eligibility, extracted data, and assessed bias. Primary outcomes included 6-month recurrent VTE and major bleeding. Secondary outcomes included clinically relevant non-major bleeding (CRNMB) and mortality. RESULTS: We screened 426 articles, reviewed 25 in full-text, and selected 13 and 2 for qualitative and quantitative synthesis, respectively. Based on a meta-analysis of the 2 RCTs, DOACs had lower 6-month recurrent VTE (42/725) when compared to LMWH (64/727) (RR: 0.65 (0.42-1.01)). However, DOACs had higher major bleeding (40/725) when compared to LMWH (23/727) (RR 1.74 (1.05-2.88)). Similarly, CRNMB was higher (RR 2.31 (0.85-6.28)) for patients receiving DOACs. There was no difference in mortality (RR 1.03 (0.85-1.26)). Observational studies were heterogeneous with high risks of bias but showed recurrent VTE rates consistent with the meta-analysis. CONCLUSIONS: DOACs were more effective than LMWHs to prevent recurrent VTE but were associated with a significantly increased risk of major bleeding as well as a trend toward more CRNMB. The absolute risk differences were small (2-3%) for both primary outcomes and may reflect better compliance with DOACs than LMWHs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.028 | 0.007 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it