Thromboprophylaxis in Multiple Myeloma Patients Treated with Lenalidomide - a Systematic Review
Bibliographic record
Abstract
Abstract Background Lenalidomide in combination to steroid therapy, including high-dose dexamethasone (RD), low-dose dexamethasone (Rd) or triple therapy of melphalan, prednisolone, lenalidomide (MPR), has shown to be an effective and well-tolerated treatment for patients with newly diagnosed multiple myeloma (NDMM) and relapsed refractory multiple myeloma (RRMM). Lenalidomide is associated with an increased risk of venous thromboembolism, and studies have consistently demonstrated the need for venous thromboembolism (VTE) prophylaxis in patients receiving these combinations. However, the optimal approach to thromboprophylaxis has not yet been established. Objective In this systematic review we sought to compare the efficacy of aspirin (ASA) or low molecular weight heparin (LMWH) in the prevention of VTE in patients with myeloma using lenalidomide- based therapy. Methods A systematic literature search strategy was used to identify potential studies on MEDLINE, EMBASE, and CENTRAL using an OVID interface. The methodological quality of the selected cohort studies was assessed according to Newcastle-Ottawa Quality Assessment Scale, and risk of bias of randomised controlled trials (RCTs) was assessed according to risk of bias assessment tool from the Cochrane Handbook. The primary outcome measure was the incidence rate of VTE while using ASA or LMWH. Results Out of 247 studies, 6 met our inclusion criteria with a total of 1126 participants including a total of 5 phase III RCTs, and one retrospective study. Overall, all studies show high quality: In 4 of the 5 RCTs type of randomization was clearly reported, outcome assessment was blinded, and withdrawal rates were reported, and the remaining RCT was an abstract. In 4 RCTs the intervention and comparator arms were related to anti-myeloma treatment regimens. Pooled data of studies of NDMM treated with lenalidomide based regimen with ASA prophylaxis show a VTE rate of 98 of 915 (10.7%) [95% CI: 8.86-12.88] (Table1). In NDMM and RRMM patients treated with lenalidomide, VTE rate on LMWH prophylaxis was 3 of 211 (1.4%) [95% CI: 0.48-4.09] (Table2). The relative risk (RR) of VTE in patients receiving ASA compared to LMWH was 7.5 (95% CI: 2.41-23.53, p =0.0005). Overall, the rate of VTE was 1.4 (95% CI: 1.14 - 1.69) per 100 patient-cycles of anti-myeloma treatment. A subgroup analysis on patient using ASA showed a similar risk of 1.5 (95% CI: 1.24 - 1.84).The incidence of VTE in those using ASA while on RD was 52 of 195 (26.6%) [95% CI: 20.9-33.2], while VTE rate in those receiving Rd was 27 of 262 (10.3%) [95% CI: 7.18-14.58] demonstrating a statistically significant higher risk for patients on RD [RR=2.5 (95% CI: 1.68- 3.96), p <0.0001]. Furthermore, VTE rate with MPR therapy while on ASA was 19 of 458 (4.1%) [95% CI: 2.67-6.38]. Pooled data of studies revealed that patients who received lenalidomide and dexamethasone alone (RD+Rd) had a significantly higher risk of VTE compared to those on MPR while on ASA (RR=6.4 [(95% CI: 4.11- 9.91), p< 0.0001]). Conclusion The study showed that the most frequent thromboprophylaxis of choice for patients with myeloma on lenalidomide-based therapy is ASA. However, ASA may not confer appropriate protection against VTE, especially in patients using high dose dexamethasone. On the other hand, the risk of VTE in patients receiving MPR and ASA was low and ASA may be a safe option for these patients. More studies comparing the safety of ASA to other anticoagulants such as LMWH or direct oral anticoagulants are warranted. Table 1. Rate of VTE using ASA in NDMM with different lenalidomide based regimens. Rx: treatment; 95% CI: 95% confidence interval. Study Design Rx N VTE rate: N (%) 95% CI Zonder, 2010 Rajkumar, 2010 Phase III RCT RD 195 52 (26.6) 20.9-33.2 Larocca, 2011 Rajkumar, 2010 Phase III RCT Rd 262 27 (10.3) 7.18-14.58 Palumbo, 2012 Stewart, 2014 Phase III RCT MPR 458 19 (4.1) 2.67-6.38 Total 915 98 (10.7) 8.86-12.88 Table 2. Rate of VTE using LMWH in myeloma patients (NDMM or RRMM) on lenalidomide-based regimen. 95% CI: 95% confidence interval. Paper Design Induction Setting N VTE rate: N (%) 95% CI Klein, 2008 Retrospective cohort RD RRMM 45 1(2.2) 0.39-11.57 Larocca, 2011 Phase III RCT Rd NDMM 166 2(1.2) 0.33-4.28 Total 211 3(1.4) 0.48-4.09 Disclosures Louzada: pfizer: Consultancy, Other: advisory board and expert opinion; janssen: Consultancy, Other: advisory board and expert opinion; Celegene: Consultancy, Other: advisory board and expert opinion.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".