Overcoming Proteasome Inhibitor-Refractory Multiple Myeloma With Elotuzumab, Bortezomib, Nelfinavir, and Dexamethasone
Bibliographic record
Abstract
Multiple myeloma is a common plasma cell malignancy with a median overall survival of fewer than 10 years. Proteasome inhibitors comprise an important part of the treatment regimen for this disease. The present study reports the case of a 57-year-old man who experienced a second relapse of multiple myeloma 6 years after initial treatment with bortezomib, lenalidomide, dexamethasone (VRD) followed by autologous hematopoietic cell transplant. The first relapse had been successfully treated with VRD, but this approach failed to control his second relapse. Given the lack of response to VRD therapy and relapse while on bortezomib maintenance, the patient was deemed proteasome inhibitor-refractory and received a new treatment of elotuzumab, lenalidomide, and dexamethasone. Four and a half cycles were completed before the treatment was stopped due to grade 4 cytopenias. The patient received a novel combination of elotuzumab, bortezomib, nelfinavir, and dexamethasone. After six cycles, the serum M-protein level was improved to 0.6 g/dL and the kappa light chains dropped from 3.49 to 1.04 mg/dL. A bone marrow biopsy conducted after five treatment cycles demonstrated < 1% plasma cells by immunohistochemistry and achievement of minimal residual disease status. Overall, this case study suggests that proteasome inhibitor-refractory multiple myeloma may be successfully re-treated with proteasome inhibitors when co-administered with nelfinavir.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".