Thalidomide‐prednisone maintenance following autologous stem cell transplant for <scp>M</scp>ultiple <scp>M</scp>yeloma: effect on thrombin generation and procoagulant markers in <scp>NCIC CTG MY</scp>.10
Bibliographic record
Abstract
Venous thromboembolism (VTE) has an increased incidence in patients with multiple myeloma (MM), especially during chemotherapy. Mechanisms including upregulation of procoagulant factors, such as factor VIII, have been postulated. The National Cancer Institute of Canada Clinical Trials Group MY.10 phase III clinical trial compared thalidomide-prednisone to observation for 332 patients with MM post-autologous stem cell transplantation (ASCT), with a primary endpoint of overall survival and various secondary endpoints including the incidence of VTE. One hundred and fifty-three patients had biomarker data, including D-dimer, factor VIII and thrombin anti-thrombin (TAT) levels collected post-ASCT at baseline and 2 months after intervention investigating in-vivo thrombin generation. Differences between the time-points included a significant reduction over time in D-dimer, factor VIII and TAT levels in the observation group and sustained elevation of D-dimer, significant increase in factor VIII and reduction in TAT levels in the thalidomide-prednisone group. Eight VTE events were reported in this subset of study patients, all in the thalidomide-prednisone arm, with a trend to increase in D-dimer levels over time in those patients with VTE. This study provides physiological and clinical evidence for an increased risk of VTE associated with thalidomide-prednisone maintenance therapy post-ASCT for MM.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".