Effect of Switching to Nilotinib in Patients with Imatinib-Related Low-Grade Non-Hematologic Adverse Events
Bibliographic record
Abstract
Abstract Abstract 4422 Background: Nilotinib is a potent, highly selective Bcr-Abl kinase inhibitor approved for newly diagnosed adult patients (pts) with Philadelphia chromosome–positive (Ph+) chronic myeloid leukemia in chronic phase (CML-CP) and for adult pts with imatinib-resistant or -intolerant Ph+ CML-CP and CML-AP (accelerated phase). This ongoing study assesses the change in chronic low-grade (LG) non-heme adverse events (AEs) when pts are switched from imatinib (IM) to nilotinib. Methods: Adult CML-CP pts were eligible for the study if they were treated with imatinib 400 mg/d for ≥3 months (mos) and had imatinib-related Grade 1 or 2 non-heme AEs persisting ≥2 mos or recurring ≥3 times and recurring despite best supportive care. Pts are treated with nilotinib 300 mg twice daily on study for up to 1 year. The primary end point is to measure the improvement of imatinib-related LG non-heme AEs at the end of cycle (EOC) 3 after switching to nilotinib therapy. Disease response was monitored and patient-reported outcomes measured by 2 quality-of-life (QoL) questions and the MD Anderson Symptom Inventory (MDASI)-CML. Results: Thirty-eight pts were enrolled as of the data cut-off date (6/27/11) and were included in this analysis. The median time of nilotinib treatment was 7.2 mos. A total of 155 imatinib-related non-heme AEs were reported at baseline; 113 AEs were Grade 1 and 42 AEs were Grade 2. A total of 30 pts completed EOC 3 by the data cut-off date. These pts accounted for 126 of the baseline imatinib-related LG non-heme AEs (Grade 1 = 93, Grade 2 = 33). The median number of IM-related LG non-heme AEs at baseline was 3 per patient. Twenty-one pts reported 1–4 baseline IM-related AEs, 6 pts reported 5–9 IM-related AEs, and 3 pts reported 10–12 IM-related AEs. Of these AEs, 81 (64%) improved (primary end point) by EOC 3; 71 IM-related AEs resolved (51, 15, 5 resolved by mos 1, 2, 3, respectively) and 10 IM-related AEs decreased from Grade 2 to 1. Forty-two AEs were unchanged across 18 pts (20 of which were reported by 3 pts). Three AEs increased in severity by month 3. Overall, 31 (82%) pts had major molecular response (MMR) at entry. MMR is defined as a 3-log reduction of Bcr-Abl from a standardized baseline (Bcr-Abl ≤0.1% IS). All pts maintained MMR after switching to nilotinib on study. The remaining 7 pts achieved MMR during the study. At baseline, 15 pts had a 4-log reduction in Bcr-Abl (Bcr-Abl ≤0.01% IS) and 7 pts with complete molecular response (CMR = Bcr-Abl ≤0.0032% IS). Twelve additional pts achieved a 4-log reduction on study and 9 went on to achieve CMR. Patients completed 2 global QoL questions and the MDASI-CML questionnaire during the study. The MDASI-CML is a patient-reported outcome measure of symptom burden in patients with CML. These were administered at baseline, EOC 1, EOC 3, and then every 3 mos thereafter while on study. Compared to baseline, 68% and 62% of pts (n=34) reported an improvement in global QoL over the last 24 hours and last 7 days, respectively, by EOC 3. The mean reductions from baseline in MDASI-CML severity score and interference score, and therefore improvement in symptoms, were at EOC 1: 1.2 (n=26) and 1.5 (n=25) and at EOC 3: 1.2 (n=24) and 1.6 (n=23), respectively. Thirteen pts were dose reduced for nilotinib-related AEs and subsequently dose re-escalated if the AEs recovered to Grade 1 or resolved. Twenty-seven Grade 3 AEs occurred in 12 pts; of these, 17 AEs were investigator reported and suspected to be nilotinib related (increased bilirubin, hyperglycemia, hypokalemia, hypophosphatemia, increased lipase, pruritus, bronchitis, dehydration, exfoliative rash, rash erythematous, rash, and arthralgia). No pt had a Grade 4 AE. Most AEs were managed by brief dose interruption. A total of 5 pts discontinued, 4 for AEs, and 1 pt withdrew consent. No QTcF prolongation >500 msec occurred. Conclusions: In this analysis, at EOC 3, 64% of the chronic LG non-heme IM-related AEs showed improvement after switching to nilotinib. Twenty-eight of 30 pts who completed 3 mos on study had at least 1 LG non-heme IM-related AE improve after switching to nilotinib. At least 62% of pts improved in QoL. In addition, an overall improvement of symptoms as measured by MDASI-CML was seen by the reduction of severity scores. Disclosures: Lipton: Novartis Canada: Consultancy, Research Funding, Speakers Bureau. Mauro:Novartis Oncology: Consultancy, Research Funding, Speakers Bureau. Ailawadhi:Novartis Pharmaceuticals: Consultancy, Speakers Bureau. Miller:Novartis: Consultancy, Research Funding, Speakers Bureau. Busque:Bristol-Myers Squibb: Consultancy; Novartis Pharmaceuticals: Consultancy, Research Funding, Speakers Bureau. Akard:Eisai: Speakers Bureau; Bristol Myers-Squibb: Speakers Bureau; Novartis: Speakers Bureau; Millenium: Speakers Bureau; Chemgenex: Consultancy. Pinilla-Ibarz:Novartis Pharmaceuticals: Consultancy, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Research Funding, Speakers Bureau. Ericson:Novartis Pharmaceuticals Corporation: Employment, Equity Ownership. Shah:Novartis Pharmaceuticals: Employment, Equity Ownership. Cortes:Bristol-Myers Squibb: Consultancy, Research Funding; Novartis Pharmaceuticals: Consultancy, Research Funding; Ariad Pharmaceuticals: Consultancy, Research Funding; ChemGenex Pharmaceuticals: Consultancy, Research Funding; Pfizer: Research Funding; Deciphera Pharmaceuticals: Research Funding.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".