Effect of Switching to Nilotinib in Patients with Imatinib-Related Low-Grade Non-Hematologic Adverse Events
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».