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Enregistrement W3097681321 · doi:10.1182/blood-2020-136957

Ivosidenib Improves Overall Survival Relative to Standard Therapies in Relapsed or Refractory Mutant <i>IDH1</i> AML: Results from Matched Comparisons to Historical Controls

2020· article· en· W3097681321 sur OpenAlexaff
Peter Paschka, Hervé Dombret, Xavier Thomas, Christian Récher, Sylvain Chantepie, Pau Montesinos Fernández, Evelyn Acuña‐Cruz, Paresh Vyas, Karl‐Anton Kreuzer, Michael Heuser, Klaus H. Metzeler, Michael Dennis, Bruno Quesnel, Mathilde Hunault, Mohamad Mohty, Arnaud Pigneux, Stéphane de Botton, Daniela Weber, Konstanze Döhner, Gary Milkovich, John Reitan, Sarah MacDonald, Deborah Casso, Michael C. Storm, Hua Liu, Stephanie M. Kapsalis, Eyal C. Attar, Thomas Winkler, Hartmut Döhner

Notice bibliographique

RevueBlood · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Myeloid Leukemia Research
Établissements canadiensMerck Canada Inc. (Canada)
Organismes subventionnairesnon disponible
Mots-clésMedicineRegimenInternal medicineRefractory (planetary science)Isocitrate dehydrogenaseOncologyGastroenterologySurgeryBiology

Résumé

récupéré en direct d'OpenAlex

Background: A European Marketing Authorization Application for ivosidenib (IVO) is currently under review for the indication of mutant isocitrate dehydrogenase 1 (mIDH1) R132 relapsed/refractory (R/R) acute myeloid leukemia (AML) in adult patients (pts) who have received ≥ 2 prior regimens, including ≥ 1 standard intensive chemotherapy (IC) regimen, or are not candidates for IC and have received ≥ 1 prior non-intensive regimen. IVO is an oral, potent, targeted inhibitor of mIDH1 and was approved by the FDA for the treatment of mIDH1 R/R AML in 2018, and in newly diagnosed AML in adults ≥ 75 years of age or pts ineligible for IC in 2019, based on the results of the open-label AG120-C-001 (NCT02074839) study. Aims: To evaluate the comparative benefit of IVO within the proposed EU indication, matched pt analyses were conducted using data on mIDH1 R/R AML pts from the AML Study Group (AMLSG) registry (NCT01252485) and a real-world chart review study (RWD) from France, Germany, UK, and Spain. Methods: Individual pt data from Arm 1+ of the AG120-C-001 study (n = 159) was compared to a historical control (HC), combining individual pt data from the AMLSG registry (n = 127) and the RWD (n = 148). A medical review was conducted to identify Arm 1+ IVO pts in the AG120-C-001 study and HC pts who fell within the proposed EU indication. Treatment with IVO was compared with the most recent therapy received by HC pts. HC pts treated with IC as their most recent therapy were excluded, as IVO pts, based on the AG120-C-001 study's eligibility criteria, were not considered candidates for IC. Propensity score-based matching/weighting methods were used to adjust for imbalances in baseline prognostic factors between the 2 cohorts (optimal full matching and inverse probability of treatment weighting [IPTW]). A literature review and data availability led to the inclusion of 6 baseline prognostic factors for estimation of propensity scores (age, history of hematopoietic stem cell transplantation, number of prior regimens for AML, nature of AML, cytogenetic risk, and primary refractory status). Balance between populations was assessed pre- and post-match via comparison of (weighted) standardized differences (SDs) for each covariate. Time-to-event data were summarized via Kaplan-Meier (KM) estimators with 2-sided 95% confidence intervals (CI). Cox regression analysis, using the key prognostic factors as covariates, was applied to estimate hazard ratios (HR) of overall survival (OS), and the corresponding 95% CI was estimated using the sandwich estimator. Complete remission (CR) rates were also compared between IVO pts and RWD non-IC HC pts (AMLSG pts were excluded as the response data did not allow for identification of CRs distinct from other response types). Results: One hundred and nine IVO pts and 60 HC pts fell within the proposed EU indication. The IPTW-matched dataset was selected for analysis, as it more strongly minimized the absolute weighted SDs between cohorts as compared with optimal full matching, with all SDs < 0.05. Median OS was 8.1 months (mo) (95% CI: 5.7, 9.8) with IVO compared with 2.9 mo (95% CI: 1.9, 4.5) in the HC pts. The HR for OS was 0.396 (95% CI: 0.279, 0.562), strongly in favor of IVO (p < 0.0001). There was clear and early separation of the IVO and HC KM curves, reflecting the early and sustained benefit of IVO treatment in this setting (Fig). Six- and 12-mo survival rates in the IVO cohort were 57.7% (95% CI: 48.2, 67.2) and 35.0% (95% CI: 25.7, 44.3), respectively, representing improvements versus 6- and 12-mo survival rates in the HC cohort of 29.1% (95% CI: 17.4, 40.8) and 10.8% (95% CI: 2.7, 18.9), respectively. The IVO cohort also demonstrated higher rates of CR than the HC cohort, with an observed CR rate of 18.3% (95% CI: 11.6, 26.9), compared with 7.0% (95% CI: 1.5, 19.1). Conclusion: IVO monotherapy demonstrated prolonged OS and the potential to increase CR rates vs standard of care therapies in a HC population. Disclosures Paschka: Amgen: Other; AbbVie: Other: Travel, accommodation or expenses, Speakers Bureau; Astellas Pharma: Consultancy, Speakers Bureau; Celgene: Consultancy, Other: Travel, accommodations or expenses; Sunesis Pharmaceuticals: Consultancy; Pfizer: Consultancy, Speakers Bureau; Novartis: Consultancy, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Speakers Bureau; Otsuka: Consultancy; Janssen Oncology: Other; Astex Pharmaceuticals: Consultancy; Agios Pharmaceuticals: Consultancy, Speakers Bureau; BerGenBio ASA: Research Funding. Dombret:Novartis: Consultancy; Cellectis: Consultancy; Sunesis: Consultancy; Abbvie: Consultancy; Immunogen: Consultancy; Celgene: Honoraria; Amgen: Consultancy, Honoraria; Jazz Pharma: Consultancy, Honoraria; Astellas: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Shire: Honoraria; Otsuka: Consultancy, Honoraria; Menarini: Honoraria; Daiichi Sankyo: Consultancy, Other: travel, accommodation expenses; Incyte: Consultancy, Other: travel, accommodation expenses; Celyad: Consultancy. Montesinos Fernandez:Abbvie: Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Daiichi Sankyo: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Incyte: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Research Funding, Speakers Bureau; Karyopharm: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Teva: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Vyas:Astellas: Speakers Bureau; Daiichi Sankyo: Speakers Bureau; Celgene: Research Funding, Speakers Bureau; Forty Seven: Research Funding; Pfizer: Speakers Bureau; Novartis: Research Funding, Speakers Bureau; AbbVie: Speakers Bureau. Kreuzer:Daiichi Sankyo: Consultancy, Honoraria, Other, Research Funding, Speakers Bureau; Chugai: Consultancy, Honoraria, Other, Research Funding, Speakers Bureau; Gilead: Consultancy, Honoraria, Other, Research Funding, Speakers Bureau; Grifols: Consultancy, Honoraria, Other, Research Funding, Speakers Bureau; Hexal: Consultancy, Honoraria, Other, Research Funding, Speakers Bureau; Janssen-Cilag: Consultancy, Honoraria, Other, Research Funding, Speakers Bureau; Jazz: Consultancy, Honoraria, Other, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Other, Research Funding, Speakers Bureau; Otsuka: Consultancy, Honoraria, Other, Research Funding, Speakers Bureau; Pfizer: Consultancy, Honoraria, Other, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Other: Personal fees, Research Funding, Speakers Bureau; BMS: Consultancy, Honoraria, Other: Personal fees, Research Funding, Speakers Bureau; Roche: Consultancy, Honoraria, Other: Personal fees, Research Funding, Speakers Bureau; AbbVie: Consultancy, Honoraria, Other: Personal fees, Research Funding, Speakers Bureau; Alexion: Consultancy, Honoraria, Other: Personal fees, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Other: Personal fees, Research Funding, Speakers Bureau; Ariad: Consultancy, Honoraria, Other: Personal fees, Research Funding, Speakers Bureau; Baxalta: Consultancy, Honoraria, Other: Personal fees, Research Funding, Speakers Bureau; Bayer: Consultancy, Honoraria, Other: Personal fees, Research Funding, Speakers Bureau; Biotest: Consultancy, Honoraria, Other: Personal fees, Research Funding, Speakers Bureau. Heuser:Karyopharm: Research Funding; Janssen: Consultancy; Amgen: Research Funding; Novartis: Consultancy, Honoraria, Research Funding; Roche: Research Funding; Abbvie: Consultancy; Stemline Therapeutics: Consultancy; Astellas: Research Funding; Pfizer: Consultancy, Honoraria, Research Funding; Daiichi Sankyo: Consultancy, Research Funding; BerGenBio ASA: Research Funding; Bayer: Consultancy, Research Funding; PriME Oncology: Honoraria. Metzeler:Daiichi Sankyo: Honoraria; Otsuka Pharma: Consultancy; Celgene: Consultancy, Honoraria, Research Funding; Novartis: Consultancy; Jazz Pharmaceuticals: Consultancy; Pfizer: Consultancy; Astellas: Honoraria. Quesnel:Abbvie: Other: travel expenses; Daichii Sankyo: Other: travel expenses, Research Funding. Mohty:Stemline: Consultancy, Honoraria, Research Funding, Speakers Bureau; BMS: Consultancy, Honoraria, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Jazz Pharmaceuticals: Consultancy, Honoraria, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Research Funding, Speakers Bureau; GSK: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Sanofi: Consultancy, Honoraria, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau. De Botton:Pierre Fabre: Consultancy; Novartis: Consultancy; Pfizer: Consultancy; Servier: Consultancy; Celgene: Consultancy, Honoraria, Speakers Bureau; Agios: Consultancy, Honoraria, Research Funding; Forma Therapeutics: Honoraria, Research Funding; Astellas: Consultancy, Honoraria; Daiichi Sankyo: Consultancy, Honoraria; Syros: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Bayer: Consultan

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai non randomisé · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,008

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,042
Tête enseignante GPT0,299
Écart entre enseignants0,257 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeEssai non randomisé
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2020
Routes d'admission1
Résumé présentoui

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