Analysis of imatinib (IM)-related, low-grade (LG), non-hematologic (heme) adverse events (AEs) in patients (pts) with chronic myeloid leukemia (CML) switched to nilotinib (NIL): ENRICH study update.
Bibliographic record
Abstract
6605 Background: This study update assesses change in chronic LG non-heme AEs in adult Ph+ CML-CP pts switched from IM to NIL. Methods: Pts were eligible if treated with IM 400 mg/d for ≥3 mo, and had IM-related grade (G) 1/2 non-heme AEs persisting ≥2 mo or recurring ≥3 times and persisting despite best supportive care. Pts received NIL 300 mg BID. Primary endpoint is change in IM-related LG non-heme AEs at 3 mo. Disease response was monitored by RQ-PCR and pt-reported outcomes measured by 2 quality-of-life (QoL) questions and MD Anderson Symptom Inventory (MDASI)-CML. Results: 47 pts were enrolled as of data cut-off (11/14/2011). There were 168 baseline IM-related non-heme AEs: 121 G1, 47 G2. 37 pts completed 3 mo NIL, by 3 mo 103 of 154 IM-related AEs (67%) improved (92 resolved, 11 improved from G2 to G1), 47 unchanged, 4 increased in severity. 13 pts were dose reduced for NIL-related AEs; 8 pts re-escalated after AEs recovered to G1 or resolved. 34 G3 AEs occurred in 15 pts; investigators reported 19 AEs as suspected NIL-related (increased bilirubin, lipase, or blood glucose; hypokalemia; hypophosphatemia; pruritus; bronchitis; dehydration; rash; arthralgia; pleural effusion). 8 pts discontinued NIL: 6 for AEs, 2 withdrew consent. No G4 AEs were reported. 32 pts had MMR (3-log reduction of Bcr-Abl; ≤0.1% IS) at entry; 16 additional pts achieved MMR on NIL. At entry, 18 pts had 4-log reduction and 10 pts 4.5-log reduction in Bcr-Abl. 16 and 13 additional pts achieved 4- and 4.5-log reduction, respectively, on NIL. At 3 mo (n=34) 62% and 53% pts reported QoL improvement from baseline in the previous 24 h and 7 d, respectively. Reduction in MDASI-CML severity/interference scores indicates symptom improvement. Mean reductions in MDASI-CML from baseline at 3 mo: severity, 1.21 (n=34); interference, 1.55 (n=33). Conclusions: 3 mo after switching to NIL, ~70% baseline chronic LG non-heme IM-related AEs improved and ≥53% of pts reported improvement in QoL. Molecular responses were maintained or improved in all patients. Switch from IM to NIL in majority of pts reduces IM-related toxicities and preserves/induces molecular response in CML-CP.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".