Effect of anticoagulants and antiplatelet agents on the efficacy of intravesical BCG treatment of bladder cancer: A systematic review
Bibliographic record
Abstract
We performed a systematic review of publications describing a correlation between oral anticoagulant medications and intravesical BCG outcome. We collected information on the impact of such medications on tumour recurrence and progression and we excluded papers not reporting outcome correlations. Patients were divided into group 1 and 2 based on whether they were taking or not taking any anticoagulant medications. A total of 7 manuscripts published between 1990 and 2009 were included in this study. Data heterogeneity precluded meta-analysis. In studies combining all anticoagulant medications, 3 out of 5 (60%) publications did not identify any difference in outcome, while 2 (40%) documented significantly more recurrences in group 1 patients. In studies performing multivariate analysis and only examining the intake of 1 medication, warfarin alone seemed to be associated with increased risk of bladder tumour recurrences and progression following intravesical BCG treatment, while ASA alone seemed to be associated with more protective effects. There is no strong evidence to support the allegations of a protective role of ASA and a deleterious role for warfarin. Further, well-designed experimental and clinical studies are needed to clarify the mechanism of action of intravesical BCG along with possible drug interactions.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".