Bibliographic record
Abstract
Advances in myeloma biology and the identification of new anti-myeloma agents have resulted in improved management of younger, transplant-eligible, and older patients. The first novel agents—thalidomide, bortezomib, and lenalidomide—have been integrated into induction therapy before autologous stem cell transplant (ASCT) as well as into first-line therapy in elderly individuals; phase III trials have established the superiority of these approaches in terms of better response rates, progression-free survival (PFS), and, in some studies, overall survival. With more experience, improvements in dosing have decreased the toxicity of these regimens. Before ASCT, four phase III studies have shown that bortezomib-based regimens confer better outcomes than older regimens. Posttransplant consolidation and maintenance strategies with novel agents provide additional benefit, particularly in terms of a longer PFS. In the elderly population, novel agents can be combined with melphalan plus prednisone (MP). MP plus thalidomide and MP plus bortezomib are commonly utilized, and the regimen of MP plus lenalidomide with lenalidomide maintenance (MPR + R) produces superior response rates and longer PFS compared with MP alone. Prolonged maintenance with bortezomib plus thalidomide also appears to extend PFS when given following combinations of MP plus bortezomib. Treatment of very elderly patients, however, remains challenging due to comorbidities and side effects. Lenalidomide plus weekly dexamethasone is also effective in elderly patients, and results of a trial comparing this regimen with MP plus thalidomide should be available soon. Finally, better methods of risk stratification and the availability of even newer drugs will allow future refinements in myeloma treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".