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Enregistrement W2489746138 · doi:10.1182/blood.v126.23.2944.2944

Comparing Single-Agent Ibrutinib, Bendamustine Plus Rituximab (BR) and Ibrutinib Plus BR in Patients with Previously Treated Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma (CLL/SLL): An Indirect Comparison of the RESONATE and HELIOS Trials

2015· article· en· W2489746138 sur OpenAlexaff
Peter Hillmen, Graeme Fraser, Jeffrey A. Jones, Simon Rule, Susan O’Brien, Marie Sarah Dilhuydy, Ulrich Jaeger, Sebastian Grosicki, Florence Cymbalista, Steven Sun, Joi Ninomoto, Michelle Mahler, Mei Cheng, Joris Diels, Fong Clow, Mariya Salman, Danelle F. James, Angela Howes, Asher Chanan‐Khan

Notice bibliographique

RevueBlood · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Lymphocytic Leukemia Research
Établissements canadiensMcMaster UniversityJuravinski Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineIbrutinibChemoimmunotherapyBendamustineInternal medicineRituximabClinical endpointOfatumumabOncologyPlaceboProgression-free survivalChronic lymphocytic leukemiaSurgeryClinical trialLeukemiaLymphomaChemotherapyPathology

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction In 2 large phase 3 trials of patients (pts) with relapsed or refractory (R/R) CLL/SLL, single-agent ibrutinib (ibr) was superior to ofatumumab (ofa) (RESONATE; Byrd. NEJM 2013) and ibr + BR was superior to placebo + BR (HELIOS; Chanan-Khan. ASCO 2015). Both studies evaluated ibr in different pt populations with different relevant comparators (eg, ofa in pts who had relapsed following prior anti-CD20-based chemoimmunotherapy [CIT] and/or with del17p, and BR in pts eligible for CIT). In the absence of head-to-head evaluations of single-agent ibr vs BR or single-agent ibr vs ibr + BR, indirect comparisons can be used for hypothesis testing by potentially providing insights on the relative efficacy of treatments. As such, an indirect comparative analysis of data from RESONATE and HELIOS was performed. Recognizing biases inherent in cross-trial comparisons, including lack of randomization across trials and consequent differences in distributions of important confounding variables (eg, pt characteristics, prognostic factors), we used pt-level data from both studies to risk adjust for confounders using accepted multivariate statistical approaches. Methods In RESONATE, pts received 420 mg oral ibr daily until disease progression or unacceptable toxicity or intravenous ofa for up to 24 weeks. The primary end point was IRC-assessed PFS, with secondary end points of OS and ORR. In HELIOS, pts received BR (≤ 6 cycles) with either 420 mg oral ibr daily or placebo until disease progression or unacceptable toxicity. Pts with del17p were excluded. The primary end point was IRC-assessed PFS, with secondary end points of ORR and OS. Per protocol amendment in both studies, pts in comparator arms could switch to ibr upon IRC-confirmed progression. The current exploratory analysis was based on the latest available data from each trial (median time on study: RESONATE, 19 months; HELIOS, 17 months) using investigator assessments, but excluding del17p pts from RESONATE. Analyses were performed using data from both the overall CLL/SLL population and only the CLL pts. Separate multivariate Cox proportional hazards models were constructed for PFS and OS, including treatment and clinically relevant prognostic variables as covariates (age, gender, Rai staging, ECOG score, del11q status, refractory status, number of prior lines of therapy, bulky disease, IgVH status). Adjusted HRs and 95% CIs are presented vs single-agent ibr, along with predicted survival curves derived from the multivariate Cox regressions. Results RESONATE and HELIOS enrolled populations with notable differences making naïve comparison flawed. Because HELIOS enrolled only CIT-eligible pts, the trial included younger pts who had received fewer lines of therapy, as well as lower proportions of pts with purine analog refractory disease, del11q, or Rai stage 4 disease. These factors have been previously reported to influence outcomes in pts with R/R CLL/SLL and thus were included as covariates in the statistical models. Other baseline factors (gender, ECOG score, bulky disease, and IgVH status) were not notably different between the trials, but were found to impact PFS and OS and thus were included as additional covariates. In the overall CLL/SLL population, PFS and OS were comparable for single-agent ibr vs ibr + BR, and were significantly improved for single-agent ibr vs BR (Figure 1). Results for only the CLL pts were similar to those shown in Figure 1 for both PFS (ibr + BR vs single-agent ibr: 1.03 [0.61-1.75], p = 0.9042; BR vs single-agent ibr: 7.52 [4.72-11.99], p < 0.0001; single-agent ibr reduced the risk of progression/death by 87% vs BR) and OS (ibr + BR vs single-agent ibr: 1.20 [0.59-2.43], p = 0.6197; BR vs single-agent ibr: 2.24 [1.14-4.40], p = 0.0197; single-agent ibr reduced the risk of death by 55% vs BR). Conclusions The adjusted indirect comparisons reported here suggest superiority of single-agent ibr over BR for PFS and OS in patients with R/R CLL/SLL. The comparisons also suggest that the addition of BR to ibr did not improve PFS or OS compared with single-agent ibr. However, as median PFS has not been reached for either ibr arm, it is too early to draw firm conclusions. Longer follow-up in the ibr arms of these studies will be required to give an indication of whether CIT adds any benefit to ibrutinib for PFS and OS. Overall, these findings provide support for single-agent ibr as an appropriate choice for all pts with previously treated CLL/SLL. Disclosures Hillmen: Roche Pharmaceuticals: Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Gilead: Honoraria, Research Funding; AbbVie: Honoraria, Research Funding; Celgene: Research Funding; Pharmacyclics LLC, an AbbVie Company: Honoraria, Research Funding. Fraser:Janssen: Honoraria, Research Funding, Speakers Bureau; Hoffman LaRoche: Consultancy, Honoraria; Celgene: Honoraria, Research Funding. Jones:Acerta Pharma BV: Research Funding. Rule:Roche: Consultancy, Other: Travel reimbursement; J&J: Consultancy, Other: Travel reimbursement, Research Funding; Celgene: Consultancy, Other: Travel reimbursement; Gilead: Research Funding. Dilhuydy:Roche: Honoraria, Other: Travel reimbursement; Janssen: Honoraria, Other: Travel reimbursement; Mundipharma: Honoraria. Jaeger:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Cymbalista:Karyopharm: Honoraria; Roche: Honoraria; Gilead: Honoraria; Janssen: Honoraria, Research Funding. Sun:Janssen/J&J: Employment, Equity Ownership. Ninomoto:Pharmacyclics LLC, an AbbVie Company: Employment. Mahler:Janssen: Employment, Other: Travel reimbursement. Cheng:Pharmacyclics LLC, an AbbVie Company: Employment. Diels:Janssen: Employment. Clow:Pharmacyclics LLC, an AbbVie Company: Employment. Salman:Janssen/J&J: Employment, Equity Ownership. James:Pharmacyclics LLC, an AbbVie Company: Employment. Howes:Janssen/J&J: Employment, Equity Ownership.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,651
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,001
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0030,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,092
Tête enseignante GPT0,308
Écart entre enseignants0,216 · 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 tête enseignante, pas un consensus.

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

Citations29
Publié2015
Routes d'admission1
Résumé présentoui

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