Dalteparin low molecular weight heparin (LMWH) in ovarian cancer: A phase II randomized study
Bibliographic record
Abstract
e16529 Background: Up to 17% of women with ovarian cancer (OC) develop venous thromboembolism (VTE). LMWH reduces the risk of VTE and may have antineoplastic effects because tissue factor on OC cells stimulates tumor growth. A multicentre, open-label phase II randomized trial was undertaken to identify a potentially efficacious and safe dose of dalteparin to investigate its antineoplastic potential in OC. Methods: Women with newly diagnosed epithelial OC were randomized to receive taxane and platinum chemotherapy (CT) and one of 3 doses of dalteparin (50 IU/kg, 100 IU/kg, or 150 IU/kg) subcu daily during the first 3 cycles of CT. With each cycle of CT, patients had a CA125 and were assessed for bleeding or VTE. A response was defined as a ≥50% reduction in CA125 from baseline sustained for at least 28 days (according to GCIG criteria). To select the best LMWH group with a ≥ 80% response rate (RR) {vs. 60% with CT alone} with 90% probability, 39 patients per group were needed. Patients were followed until the end of CT. Results: 77 women were randomized and 72 of them completed follow-up. Compliance with injections was > 80%. There were no major bleeding events and 3 patients in the highest dose group had minor bleeding. There were no VTEs while on or within 7 days of finishing LMWH. There were 2 deaths attributed to the underlying OC. A 50% drop in CA125 by the start of cycle 4 was seen in 87% of the 50 IU/kg group, 92% of the100 IU/kg group, and 84% of the 150 IU/kg group, respectively. The corresponding RRs by the end of cycle 6 were 91%, 92% and 92%. Conclusions: Use of dalteparin is safe and well tolerated in women who are receiving CT for newly diagnosed OC. This therapy was effective in preventing VTE. A dose response effect on CA125 levels was not identified. [Table: see text]
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".