Ixabepilone-associated peripheral neuropathy: data from across the phase II and III clinical trials
Bibliographic record
Abstract
PURPOSE: Dose-limiting neuropathy is a major adverse event associated with most of the microtubule-stabilizing agent-based chemotherapy regimens. Ixabepilone, a semisynthetic analogue of the natural epothilone B, has activity against a wide range of tumor types. Peripheral neuropathy (PN), associated with ixabepilone treatment, is usually mild to moderate, predominantly sensory and cumulative. Preclinical studies demonstrate that ixabepilone and taxanes produce a similar neurotoxicity profile. METHODS: We searched databases of phase II/III clinical trials involving patients receiving ixabepilone as a monotherapy or in combination with capecitabine for incidences of neuropathy. Potential risk factors for grade 3/4 PN were identified by a Cox regression analysis on a dataset of 1,540 patients with different tumor types across multiple studies. RESULTS: Rates for incidence of ixabepilone-induced severe PN (Common Terminology Criteria for Adverse Events grade 3/4) ranged from 1% in early untreated breast cancer up to 24% in heavily pretreated metastatic breast cancer; grade 4 PN was rare (≤ 1%). Common symptoms included numbness, paresthesias, and sometimes dysesthesias. Cox regression analysis identified only preexisting neuropathy as a risk factor for increased ixabepilone-associated PN. The management of PN has been primarily through dose adjustments (dose delays and/or dose reduction). Patients had resolution of their neuropathy within a median time of 5 to 6 weeks. CONCLUSIONS: PN is a dose-limiting toxicity associated with ixabepilone treatment, is reversible in most patients, and can be managed with dose reduction and delays.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".