Switching to Nilotinib Is Associated with Continued Deeper Molecular Responses in CML-CP Patients with Minimal Residual Disease After ≥ 2 Years On Imatinib: Enestcmr 2-Year Follow-up Results
Notice bibliographique
Résumé
Abstract Abstract 694 Background: Superior rates of deeper molecular responses were achieved with nilotinib vs imatinib in patients newly diagnosed with Philadelphia chromosome–positive (Ph+) chronic myeloid leukemia in chronic phase (CML-CP) in the Evaluating Nilotinib Efficacy and Safety in Clinical Trials—newly diagnosed patients (ENESTnd) trial. In addition, the 12-month (mo) analysis of the ENEST—complete molecular response (ENESTcmr) study demonstrated that switching to nilotinib after a minimum of 2 years on imatinib led to increased rates of major molecular response (MMR) and deeper molecular responses vs remaining on imatinib. Results from ENESTcmr are presented here with minimum 24 mo of patient follow-up. Methods: Patients with Ph+ CML-CP who had achieved complete cytogenetic responses but still had persistent BCR-ABL positivity by real-time quantitative polymerase chain reaction (RQ-PCR) after ≥ 2 years on imatinib were eligible. Patients (n = 207) were randomized to switch to nilotinib 400 mg twice daily (BID; n = 104) or to continue on the same dose of imatinib (400 or 600 mg once daily [QD]; n = 103). Rates of MMR, MR4 (BCR-ABL ≤ 0.01% according to the International Scale [IS], corresponding to a 4-log reduction), MR4.5 (BCR-ABL ≤ 0.0032%IS, corresponding to 4.5-log reduction), and undetectable BCR-ABL via RQ-PCR with ≥ 4.5-log sensitivity were measured. Results: Among all randomized patients (intent-to-treat population), significantly more patients treated with nilotinib continued to achieve undetectable BCR-ABL by 24 mo (32.7% on nilotinib vs 16.5% on imatinib; P =.005; Table).The difference between the arms in achievement of this endpoint increased between 1 and 2 years (from 12.4% to 16.2%). The median time to MR4.5 and undetectable BCR-ABL was also significantly faster on nilotinib than on imatinib (P = .005 and .003, respectively). Cumulative rates of MR4.5 and undetectable BCR-ABL continued to be higher with nilotinib in patients without those responses at baseline, and the difference between arms appeared to increase over time. The safety profiles for nilotinib and imatinib were consistent with prior studies. By 24 mo, no patients in either arm progressed to accelerated phase/blast crisis. No patients on nilotinib died since the 12-mo analysis; 1 patient on imatinib died from metastatic prostate cancer in follow-up after discontinuation from the study. Conclusions: Switching to nilotinib led to significantly faster, deeper molecular responses in patients with minimal residual disease on long-term imatinib therapy. Since the 12-mo analysis, rates of deep molecular response (MR4.5 and undetectable BCR-ABL) have remained significantly higher in patients who did not have the response at baseline and were switched to nilotinib (vs those remaining on imatinib). In fact, the difference in favor of nilotinib increased between 1 and 2 years. These results suggest that switching to the more potent, selective tyrosine kinase inhibitor nilotinib is beneficial in patients with minimal residual disease after long-term imatinib therapy. Achievement of these deeper molecular responses (MR4.5 and undetectable BCR-ABL) after switching to nilotinib may enable a greater proportion of CML-CP patients to be eligible for future discontinuation studies. Cumulative rates of confirmed undetectable BCR-ABL by 24 mo will be presented as the confirmation assessments for several responders were not available at the time of this analysis. Disclosures: Hughes: Novartis Pharmaceuticals Corp: Consultancy, Honoraria, Research Funding; Bristol Myers Squibb: Consultancy, Honoraria, Research Funding; Ariad: Consultancy; CSL: Research Funding. Lipton:Novartis: Consultancy, Research Funding, Speakers Bureau. Spector:Novarits: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy. Leber:Novartis: Advisory Board Other, Honoraria, Speakers Bureau. Schwarer:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees. Etienne:Novartis: Consultancy, Speakers Bureau; Pfizer: Consultancy; BMS: Consultancy, Speakers Bureau. Branford:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Honoraria, Research Funding; Ariad: Research Funding. Purkayastha:Novartis Pharmaceuticals Corp: Employment. Collins:Novartis Pharmaceuticals Corp: Employment. Szczudlo:Novartis Pharmaceuticals Corp: Employment. Cervantes:Novartis: Membership on an entity's Board of Directors or advisory committees; Sanofi-Aventis: Membership on an entity's Board of Directors or advisory committees; BMS: Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Teva Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,002 | 0,001 |
| 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 | 0,001 | 0,001 |
| 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 ».