Does androgen-deprivation therapy for prostate cancer increase the risk for thromboembolic disease?
Bibliographic record
Abstract
V enous thromboembolism (VTE) is a common complication of cancer.2][3] However, it is reasonable to believe that the risk for VTE may be higher in PCa patients who are treated with androgen-deprivation therapy (ADT) because it can alter both tumour and host factors that facilitate the development of VTE.In this issue of the journal, Othman et al provide data from a comparative, prospective thromboelastographic analysis of PCa patients initiating ADT, and two control groups -PCa patients on watchful waiting and healthy men.Thromboelastography (TEG) is a laboratory method that assesses the strength and elasticity of a clot and, thus, depends on the global function of different hemostatic processes, including plasma coagulation factors, platelet function, and fibrinolysis.A previous study by the same group suggested that PCa patients, in particular patients with advanced disease who receive ADT, have hypercoagulability that can be identified by TEG. 4 Here, the authors confirmed these findings, but could not demonstrate a consistent effect of ADT on hypercoagulability as defined by TEG over time.The interactions between PCa in general and ADT in particular with VTE development are complex and are obviously not only a reflection of global hypercoagulability laboratory parameters.Factors such as disease burden, advanced age, immobilization, fractures, and cardiovascular disease, which are associated with either the indications for ADT or its associated complications, increase the risk of VTE development in this patient population.Indeed, analyses of different administrative registries suggest an association between ADT use and thromboembolic events. 5,6Using the Surveillance, Epidemiology and End Results (SEER)-Medicare
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".