Reversibility of symptomatic peripheral neuropathy with bortezomib in the phase III APEX trial in relapsed multiple myeloma: impact of a dose‐modification guideline
Bibliographic record
Abstract
The frequency, characteristics and reversibility of bortezomib-associated peripheral neuropathy were evaluated in the phase III APEX (Assessment of Proteasome Inhibition for Extending Remissions) trial in patients with relapsed myeloma, and the impact of a dose-modification guideline on peripheral neuropathy severity and reversibility was assessed. Patients received bortezomib 1.3 mg/m(2) (days 1, 4, 8, 11, eight 21-d cycles, then days 1, 8, 15, 22, three 35-d cycles); bortezomib was held, dose-reduced or discontinued depending on peripheral neuropathy severity, according to a protocol-specified dose-modification guideline. Overall, 124/331 patients (37%) had treatment-emergent peripheral neuropathy, including 30 (9%) with grade >or=3; incidence and severity were not affected by age, number/type of prior therapies, baseline glycosylated haemoglobin level, or diabetes history. Grade >or=3 incidence appeared lower versus phase II trials (13%) that did not specifically provide dose-modification guidelines. Of patients with grade >or=2 peripheral neuropathy, 58/91 (64%) experienced improvement or resolution to baseline at a median of 110 d, including 49/72 (68%) who had dose modification versus 9/19 (47%) who did not. Efficacy did not appear adversely affected by dose modification for grade >or=2 peripheral neuropathy. Bortezomib-associated peripheral neuropathy is manageable and reversible in most patients with relapsed myeloma. Dose modification using a specific guideline improves peripheral neuropathy management without adversely affecting outcome.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".