Comparative Effectiveness of Generic Imatinib and Brand-Name Imatinib for the Treatment of Chronic Myeloid Leukemia
Notice bibliographique
Résumé
Abstract Background: Generic versions of imatinib (GEN) have been approved for use in Canada for chronic myeloid leukemia, chronic phase (CML-CP) on the basis of bioequivalence studies and were reimbursed in Québec starting from October 2013. Molecular responses with GEN have not yet been examined in detail. This study assesses the risk of diminished molecular response in switchers from brand-name imatinib (BN) to GEN and compares the effectiveness of initiating first-line GEN and first-line BN. Methods: Prospective individual patient data were available from nine hospitals participating in the Québec CML registry. To allow equipoise between GEN and BN, we focused on stable BN users at the time of GEN market entry, of which some were subsequently switched to GEN. We further selected only those who had a 1-log rise in international reporting scale (IS) BCR-ABL1 transcript level and conducted a self-controlled case series study (SCSS).1 Using SCSS, each patient contributed follow-up for BN use, and for GEN use (if a switch occurred). The analysis used pooled BN and GEN person-time and compared the odds ratio (OR) of 1-log rise during GEN and BN treatment using conditional Poisson regression. A second analysis used a cohort of initiators of BN and GEN from 2013 and onwards. Kaplan Meier (KM) analyses were used to estimate the cumulative incidence of early molecular response (EMR) corresponding to < 10% IS. Cox proportional hazards models were used to estimate age-adjusted hazard ratio (HR) with 95% confidence intervals (CI) for EMR with GEN use, when compared with BN use. Results: We identified 184 patients treated with BN, 38 who were switched from BN to GEN, and 5 who used GEN only. For the SCSS analysis we included 23 patients, of which 17 had 1-log rise during BN use and 6 during GEN use. All patients had achieved major molecular response (MMR) prior to cohort entry (Table). Mean follow-up was 1.45±0.43 years. Overall, the use of GEN was associated with an increased incidence of 1- log rise (OR: 3.34, 95% CI: 0.33-33.68), although not reaching statistical significance. Ten of 23 rises in BCR-ABL1 levels were subsequently confirmed (7 in BN and 3 in GEN). Eleven patients lost MMR (IS>0.1%), 9 during BN use and 2 during GEN use. The cohort of first-line imatinib included 11 patients, 4 GEN and 7 BN. GEN users were slightly older (61 vs 53, GEN vs BN), and Sokal scores were comparable (low, 2 vs 4; intermediate, 2 vs 3). There was no clear separation of the EMR curves (Figure). However, the adjusted HR of EMR with GEN was 0.38 (95% CI: 0.07-2.15), compared with BN. Conclusions: While these analyses are preliminary, our results call for an initiative on a larger scale to examine the clinical effectiveness of generic imatinib for CML-CP. 1. Whitaker HJ, Farrington CP, Spiessens B, Musonda P. Tutorial in biostatistics: the self-controlled case series method. Stat Med. 2006;25(10):1768-1797. Table 1. Baseline characteristics of the self-controlled case series cohort (n=23) Characteristic Value Mean age, years (SD) 62.87 (15.4) Female sex (n, %) 9 (39.1) Mean number of concomitant medications (SD) 1.07 (2.2) Mean years of brand-name imatinib use (SD) 6.85 (2.8) Number major molecular response (%) 23 (100.0) Figure 1. Cumulative incidence of EMR (<10% IS) following the initiation of generic or brand-name imatinib. Figure 1. Cumulative incidence of EMR (<10% IS) following the initiation of generic or brand-name imatinib. Disclosures Chamakhi: Pfizer: Consultancy; BMS: Consultancy; Novartis: Consultancy. Delage:Pfizer: Consultancy; BMS: Consultancy; Novartis: Consultancy. Laneuville:Pfizer: Consultancy; BMS: Consultancy; Novartis: Consultancy. Mollica:Pfizer: Consultancy; Novartis: Consultancy; BMS: Consultancy. Olney:Cellgene: Honoraria; Pfizer: Consultancy; BMS: Consultancy; Novartis: Consultancy. Busque:Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau; BMS: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria. Assouline:Pfizer: Consultancy; BMS: Consultancy; Novartis: Consultancy.
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 | 0,003 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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 | 0,000 |
| 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 ».