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Enregistrement W3097206381 · doi:10.1182/blood-2020-137245

Analyzing Efficacy Outcomes from the Phase 2 Study of Single-Agent Tazemetostat As Third-Line Therapy in Patients with Relapsed or Refractory Follicular Lymphoma to Identify Predictors of Response

2020· article· en· W3097206381 sur OpenAlexaff
Gilles Salles, Hervé Tilly, Aristeidis Chaidos, Pam McKay, Tycel Phillips, Sarit Assouline, Connie Lee Batlevi, Philip Campbell, Vincent Ribrag, Gandhi Damaj, Michael Dickinson, Wojciech Jurczak, Maciej Kaźmierczak, Stephen Opat, John Radford, Anna Schmitt, Jennifer Whalen, Anthony Hamlett, Beth Kamp, Deyaa Adib, Franck Morschhauser

Notice bibliographique

RevueBlood · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensMcGill UniversityJewish General Hospital
Organismes subventionnairesnon disponible
Mots-clésMedicineFollicular lymphomaRefractory (planetary science)Internal medicineOncologyPhases of clinical researchLymphomaPharmacologyClinical trial

Résumé

récupéré en direct d'OpenAlex

Background: Tazemetostat, a first-in-class, oral, enhancer of zeste homolog 2 (EZH2) inhibitor was recently approved by the US Food and Drug Administration in patients with relapsed/refractory (R/R) follicular lymphoma (FL) after demonstrating single-agent, antitumor activity in patients with wild-type (WT) or mutant (MT) EZH2. Progression of disease within 24 months (POD24), exposure to multiple lines of prior therapy, and refractoriness to rituximab therapy have been shown to adversely affect the prognosis of patients receiving second- or third-line regimens for R/R FL, including chemoimmunotherapy. We performed a post hoc exploratory analysis to better understand how these factors impact the outcomes in patients receiving tazemetostat. Methods: This open-label, multicenter study (NCT01897571) evaluated tazemetostat 800 mg administered orally twice daily in patients with MT or WT EZH2 R/R FL. The primary endpoint was objective response rate (ORR; complete response + partial response) as assessed by an independent review committee (IRC); secondary efficacy endpoints included duration of response (DOR) by IRC, progression-free survival (PFS) by IRC, and overall survival (OS) by investigator assessment. Predictive modeling using baseline demographic and disease characteristic variables combined from patients with MT or WT EZH2 R/R FL was performed to identify variables predictive of response (ORR, DOR, PFS, and OS). Models were fitted for variables that were categorical and had no missing observations; they also were fitted with/without Groupe d'Etude des Lymphomes Folliculaires (GELF) criteria and with the number of prior lines of therapy (1, 2, or >2, and 1 or 2 vs >2). Due to incomplete data collection, GELF criteria were analyzed with missing observations (n=28) set to "no." Stepwise logistic and Cox regression was used to determine possible predictors; inclusion at a specified step was based on P≤0.40. Final model inclusion was based on P≤0.20. A final model was run using the possible predictors identified from the previous stepwise regressions. Contingency tables and Kaplan-Meier plots were used to examine significant variables (P≤0.05). Results: In the phase 2 study, the efficacy outcomes by IRC in combined WT and MT EZH2 populations (N=99) were: ORR, 51% (n=50); median DOR, 11 months (95% CI: 7, 19); and median PFS, 12 months (95% CI: 8, 15). Median OS was not reached (95% CI: 38.2, not estimable). Predictive modeling using 17 baseline variables identified possible predictors of efficacy outcome. For ORR, the number (1 or 2 vs >2) of prior lines of therapy was identified as possibly predictive (Table). Patients with 1 line of prior therapy had an ORR of 66% (n=27) vs 40% (n=23) in patients with 2 prior lines of therapy. Disease refractory to rituximab and number (1, 2, or >2) of prior lines of therapy (Table) were identified as possible predictors for DOR. Disease refractory to rituximab, GELF criteria, disease refractory to any treatment, and sex (Table) were possibly predictive for PFS. However, the percentage of subjects that met GELF criteria may be underestimated due to retrospective collection of qualifying data points; therefore, the translation of GELF criteria as a predictive factor for PFS should be interpreted with caution. Other baseline demographic and disease characteristics, including patient age (≤65 y, >65 y), double refractory disease, ECOG performance status, myelosuppression, POD24, disease refractory to last therapy, prior stem cell transplant, and time since last therapy, were not found to be predictive of response, as measured by ORR, DOR, PFS, and OS. Conclusions: In this post hoc exploratory analysis of patients with R/R FL (WT and MT EZH2 cohorts combined), variables associated with heavily pretreated patients (ie, refractory to rituximab, treatment-refractory disease, and number of prior treatments) were identified as possible predictors of response. However, in these analyses other high-risk disease characteristics, such as POD24, were not predictive, although the results may be confounded by the small number of patients in some of the groups. In addition to reinforcing the efficacy of tazemetostat in heavily pretreated patients, these data also suggest that ORR is greater in patient populations who receive treatment as an earlier line of therapy. Prospective confirmatory studies are warranted to confirm these post hoc observations. Disclosures Salles: Kite: Consultancy, Honoraria, Other; Gilead: Consultancy, Honoraria, Other: Participation in educational events; Bristol Myers Squibb: Consultancy, Other; F. Hoffman-La Roche Ltd: Consultancy, Honoraria, Other; Takeda: Consultancy, Honoraria, Other; Janssen: Consultancy, Honoraria, Other: Participation in educational events; Amgen: Honoraria, Other: Participation in educational events; Celgene: Consultancy, Honoraria, Other: Participation in educational events; Autolus: Consultancy; Abbvie: Consultancy, Honoraria, Other: Participation in educational events; Genmab: Consultancy; Epizyme: Consultancy; Debiopharm: Consultancy; MorphoSys: Consultancy, Honoraria, Other; Karyopharm: Consultancy; Novartis: Consultancy, Honoraria, Other. Tilly:BMS: Honoraria. McKay:Greater Glasgow and Clyde Health Board: Current Employment; Roche, Gilead, Takeda, Janssen: Other: For lectures etc; TAKEDA: Membership on an entity's Board of Directors or advisory committees, Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company), Speakers Bureau; Janssen: Other: TRAVEL, ACCOMMODATIONS, EXPENSES (paid by any for-profit health care company), Speakers Bureau; BeiGene: Membership on an entity's Board of Directors or advisory committees; Gilead: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees. Phillips:Beigene: Consultancy; Karyopharm: Consultancy; AstraZeneca: Consultancy; Incyte: Consultancy, Other: travel expenses; Seattle Genetics: Consultancy; BMS: Consultancy; Bayer: Consultancy, Research Funding; Abbvie: Consultancy, Research Funding; Pharmacyclics: Consultancy; Cardinal Health: Consultancy. Assouline:Pfizer: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Speakers Bureau; BeiGene: Consultancy, Honoraria, Research Funding; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Research Funding; Takeda: Research Funding; AbbVie: Consultancy, Honoraria, Speakers Bureau; AstraZeneca: Consultancy, Honoraria, Speakers Bureau. Batlevi:Janssen, Novartis, Epizyme, Xynomics, Bayer, Autolus, Roche/Genentech: Research Funding; Life Sci, GLG, Juno/Celgene, Seattle Genetics, Kite: Consultancy. Campbell:Amgen, Novartis, Roche, Janssen, Celgene (BMS): Research Funding; AstraZeneca, Janssen, Roche, Amgen, CSL Behring, Novartis: Consultancy. Ribrag:BAY1000394 studies on MCL: Patents & Royalties; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees; Epizyme: Consultancy, Current equity holder in publicly-traded company, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; argenX: Current equity holder in publicly-traded company, Research Funding; Institut Gustave Roussy: Current Employment; Immune Design: Consultancy, Membership on an entity's Board of Directors or advisory committees; F. Hoffmann-La Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Expenses; arGEN-X-BVBA: Research Funding; Nanostring: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees; Incyte: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Eisai: Honoraria; Servier: Consultancy, Honoraria; Pharmamar: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; AZD: Honoraria, Other; MSD: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Expenses; Infinity: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Damaj:Roche, Takeda, Accord: Honoraria; Roche, Takeda, Iqone, Accord: Consultancy; Abbevie, Pfizer, Takeda, Roche: Other: Travel. Dickinson:Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Merck Sharp & Dohme: Consultancy; Novartis: Consultancy, Honoraria, Research Funding, Speakers Bureau. Jurczak:BeiGene: Consultancy, Research Funding; Celgene: Research Funding; Epizyme: Consultancy; Gilead Sciences: Research Funding; MorphoSys: Research Funding; Nordic Nanovector: Research Funding; Servier: Research Funding; Maria Sklodowska-Curie National Research Institute of Oncology, Krakow, Poland: Current Employment; Jagiellonian University, Krakow, Poland: Ended employment in the past 24 months; Sandoz-Novartis: Consultancy; European Medicines Agency,: Consultancy; AstraZeneca: Consultancy; Takeda: Research Funding; Roche: Research Funding; Pharmacyclics: Research Funding; Merck: Research Funding; Afimed: Res

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)0,006
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil0,030

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,004
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,000
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 Opus0,036
Tête enseignante GPT0,310
Écart entre enseignants0,274 · 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'étudeObservationnel
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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