Effect of age and frailty on the efficacy and tolerability of once‐weekly selinexor, bortezomib, and dexamethasone in previously treated multiple myeloma
Bibliographic record
Abstract
Elderly and frail patients with multiple myeloma (MM) are more vulnerable to the toxicity of combination therapies, often resulting in treatment modifications and suboptimal outcomes. The phase 3 BOSTON study showed that once-weekly selinexor and bortezomib with low-dose dexamethasone (XVd) improved PFS and ORR compared with standard twice-weekly bortezomib and moderate-dose dexamethasone (Vd) in patients with previously treated MM. This is a retrospective subgroup analysis of the multicenter, prospective, randomized BOSTON trial. Post hoc analyses were performed to compare XVd versus Vd safety and efficacy according to age and frailty status (<65 and ≥65 years, nonfrail and frail). Patients ≥65 years with XVd had higher ORR (OR 1.77, p = .024), ≥VGPR (OR, 1.68, p = .027), PFS (HR 0.55, p = .002), and improved OS (HR 0.63, p = .030), compared with Vd. In frail patients, XVd was associated with a trend towards better PFS (HR 0.69, p = .08) and OS (HR 0.62, p = .062). Significant improvements were also observed in patients <65 (ORR and TTNT) and nonfrail patients (PFS, ORR, ≥VGPR, and TTNT). Patients treated with XVd had a lower incidence of grade ≥ 2 peripheral neuropathy in ≥65 year-old (22% vs. 37%; p = .0060) and frail patients (15% vs. 44%; p = .0002). Grade ≥3 TEAEs were not observed more often in older compared to younger patients, nor in frail compared to nonfrail patients. XVd is safe and effective in patients <65 and ≥65 and in nonfrail and frail patients with previously treated MM.
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 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".