Venous thromboembolism is associated with graft-<i>versus</i>-host disease and increased non-relapse mortality after allogeneic hematopoietic stem cell transplantation
Bibliographic record
Abstract
Although venous thromboembolism rates and risk factors are well described in patients with cancer, there are limited data on the incidence, risk factors and outcomes of thrombosis after allogeneic stem cell transplantation, a curative therapy for patients with hematologic malignancies. We aimed to determine the incidence and risks associated with venous thrombosis in allogeneic stem cell transplants. We studied 2276 recipients of first transplant between 2002–2013 at our institution with a median follow up of 50 months (range 4–146). Using pharmacy records and subsequent chart reviews, 190 patients who received systemic anticoagulation for venous thrombosis were identified. The 1-and 2-year cumulative incidence of all venous thrombotic events were 5.5% (95% confidence interval (CI) 4.6–6.5%) and 7.1% (95% CI 6.1–8.2%), respectively. There was no difference in age, sex, body mass index, diagnosis, disease risk index, conditioning intensity, donor type or graft source between transplant recipients with and without subsequent thrombosis. In multivariable models, both acute and chronic graft-versus-host disease were independently associated with thrombosis occurrence (Hazard ratio (HR)=2.05, 95% CI 1.52–2.76; HR=1.71, 95% CI 1.19–2.46, respectively). Upper extremity thrombosis differed from all other thromboses in terms of timing, risk factors and clinical impact, and was not associated with non-relapse mortality (HR=1.15; 95% CI 0.69–1.90), unlike all other thromboses which did increase non-relapse mortality (HR=1.71; 95% CI 1.17–2.49). In subgroup analysis evaluating conventional thrombosis predictors by comparing patients with and without thrombosis, a history of prior venous thrombosis was the only significant predictor. Venous thromboembolism has a high incidence after allogeneic stem cell transplant and is associated with graft-versus-host disease and non-relapse mortality.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".