Thromboembolism in Multiple Myeloma: A Single Centre Retrospective Review
Bibliographic record
Abstract
Background: Multiple myeloma (MM) is associated with the highest rates of venous thromboembolism (TE) of all malignancies with an estimated 3-month cumulative incidence of 4-7%. Comparatively, routine thromboprophylaxis is often indicated in hospitalization where 3-month venous TE incidence ranges from 0.6-3%. In contrast, there are no widely adopted guidelines on thromboprophylaxis for MM and current clinical prediction scores are based on US centres, with greatly differing MM standards of practice in other areas globally. This is the first study to explore MM TE in a Canadian population and aims to document the rates and risk factors of TE in this setting. Methods: Patients with a new diagnosis of MM referred to the Tom Baker Cancer Centre from 2018 to 2021 were retrospectively reviewed until April 2024 at all stages of their disease course. Cumulative incidence was calculated using the Kaplan-Meier method. Logistic regression was performed to identify risk factors. Variables were chosen based on a review of the literature of previously reported TE risk factors in MM. Results: 287 patients were included. The median age of our cohort was 65, and 54% the cohort developed relapsed/refractory (R/R) disease (median follow-up of 3.6 years). Half (52%) received autologous stem cell transplants with most commonly VCd (bortezomib, cyclophosphamide, dexamethasone) as the induction regimen. The cumulative incidence of TE was 6% at 3 months, 12.5% at 1 year, and 14.5% at 2 years following the initial myeloma diagnosis. 0.7% experienced arterial events treated as thromboemboli, 3% had superficial vein thrombi, and thirty-seven (13%) developed a combination of deep vein thrombi, pulmonary emboli, or both. Patients previously on an antithrombotic agent (8% on antiplatelets & 8.4% on anticoagulants) for a different indication had lower rates of TE (4% at 1 year, P<0.01) and were excluded from the subsequent regression analysis. Age, body mass index, immunomodulatory drugs (IMiDs), and R/R disease status were not found to be significantly associated with TE risk on univariable analysis (all p>0.05). Factors correlated with increased development of TE were male gender (HR 2.08, 95% CI 1.12-3.83) and International Staging System stage 2-3 disease (HR 2.36, 95% CI 1.11-5.02). Discussion: Data from our institution corroborates the previously reported high rates of TE in the MM population. Concordantly, most events occurred within 1 year of first MM diagnosis or relapse of disease. None of our patients received doxorubicin or high dose dexamethasone (>480mg/mo), and aspirin prophylaxis was routine for those on IMiDs, precluding the use of currently available MM TE prediction scores (SAVED, IMPEDE-VTE). Recently published survey by Frenzel et al. likewise underscores that few myeloma clinicians use these scores despite a majority starting thromboprophylaxis based on clinical context. The two-fold higher TE risk in men may be explained by the age of our cohort as most women were post-menopausal, seen also in the MEGA study. Due to the routine aspirin start with IMiDs, this study's capacity to explore the impact of IMiDs on TE risk was limited; however, the lack of significance and the lower rates of those on antiplatelets for a different indication suggests a possible protective effect that would be better addressed in a prospective study. This aligns well with post-hoc analyses of TE in the Myeloma IX versus Myeloma XI trials demonstrating an inverse relationship between portion on antithrombotics and TE rates. In extensive multi-agent regimen containing IMiDs and steroids, however, TE rates remain high despite antithrombotics (GRIFFIN). Taken altogether, there is an unmet need for further exploration of risk stratification and thromboprophylaxis strategies in MM, such as consideration for the use of direct oral anticoagulants in high risk groups for a year, given the preponderance of TE events early on in the MM disease course.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".