Arterial and venous thrombosis in monoclonal gammopathy of undetermined significance and multiple myeloma: a population-based study
Bibliographic record
Abstract
Patients with multiple myeloma (MM) have an increased risk of venous thrombosis. Interestingly, excess risk of venous thromboembolism has been observed among patients with monoclonal gammopathy of undetermined significance (MGUS). Using population-based data from Sweden, we assessed the risks of venous and arterial thrombosis in 18,627 MM and 5326 MGUS patients diagnosed from 1958 to 2006, compared with 70,991 and 20,161 matched controls, respectively. At 1, 5, and 10 years after MM diagnosis, there was an increased risk of venous thrombosis: hazard ratios (95% confidence intervals) were 7.5 (6.4-8.9), 4.6 (4.1-5.1), and 4.1 (3.8-4.5), respectively. The corresponding results for arterial thrombosis were 1.9 (1.8-2.1), 1.5 (1.4-1.6), and 1.5 (1.4-1.5). At 1, 5, and 10 years after MGUS diagnosis, hazard ratios were 3.4 (2.5-4.6), 2.1 (1.7-2.5), and 2.1 (1.8-2.4) for venous thrombosis. The corresponding risks for arterial thrombosis were 1.7 (1.5-1.9), 1.3 (1.2-1.4), and 1.3 (1.3-1.4). IgG/IgA (but not IgM) MGUS patients had increased risks for venous and arterial thrombosis. Risks for thrombosis did not vary by M-protein concentration (> 10.0 g/L or < 10.0 g/L) at diagnosis. MGUS patients with (vs without) thrombosis had no excess risk of MM or Waldenström macroglobulinemia. Our findings are of relevance for future studies and for improvement of thrombosis prophylaxis strategies.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".