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Enregistrement W2902790828 · doi:10.1182/blood-2018-99-117448

Checkpoint Blockade Therapy May Sensitize Aggressive and Indolent Non-Hodgkin Lymphoma to Subsequent Therapy

2018· article· en· W2902790828 sur OpenAlexaffabout
Nicole A. Carreau, Orrin Pail, Philippe Armand, Reid W. Merryman, Ranjana H. Advani, Michael A. Spinner, Alex F. Herrera, Robert W. Chen, Sarah Tomassetti, Radhakrishnan Ramchandren, Muhammad Saad Hamid, Sarit Assouline, Raoul Santiago, Nina D. Wagner‐Johnston, Suman Paul, Jakub Svoboda, Steven M. Bair, Stefan K. Barta, Yang Liu, Sunita Nathan, Madelyn Burkart, Reem Karmali, Pallawi Torka, Kevin A. David, Catherine Wei, Frederick Lansigan, Lukas Emery, Daniel O. Persky, Sonali M. Smith, Julio C. Chávez, Yuhe Xia, Andrea B. Troxel, Catherine Diefenbach

Notice bibliographique

RevueBlood · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensMcGill University
Organismes subventionnairesnon disponible
Mots-clésBlockadeMedicineLymphomaOncologyInternal medicineImmunology

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Outcomes to salvage therapy for patients with relapsed/refractory (R/R) non-Hodgkin lymphoma (NHL) are suboptimal. Checkpoint blockade therapy (CBT) has been explored in the relapsed/refractory (R/R) NHL population, but response rates to single agent CBT therapy are modest. To date, there is no literature on whether treatment with CBT may sensitize NHL patients to subsequent therapy. We investigated the outcome of subsequent treatment in patients with R/R NHL who had received CBT in a large multicenter international retrospective analysis. Methods: Seventeen centers across the US and Canada are participating in this study to date. Medical records of each institution were queried to identify lymphoma patients who received CBT and were subsequently treated with an additional line of therapy. The primary aim of the current analysis was to determine the best response to post-CBT treatment in patients who discontinued CBT due to progression of disease (PD) or toxicity. Patients who discontinued CBT due to a complete response (CR), or patients whose best response to post-CBT therapy could not be determined due to death from another cause, were excluded from analysis. Responses were assessed using Lugano criteria. Survival status to date was analyzed for the entire study population and stratified by post-CBT treatment regimen categories and disease subgroups using the Kaplan-Meier method. Progression free survival (PFS) and overall survival (OS) were calculated for patients with at least stable disease (SD) to post-CBT treatment. Log rank tests were performed to test for statistical significance. Two-sided P<0.05 was considered to be statistically significant. Results: To date, out of 121 total lymphoma patients, we identified 42 NHL patients whom received therapy subsequent to CBT. The median age was 62 (range 27-85); 26 patients were men and 16 women. Twelve patients were stage 1-2, and 30 were stage 3-4. Forty patients, with 10 histologic subtypes (Table 1) were included in analysis. At least 24 patients (60%) had aggressive NHL; 12 (30%) had indolent histologies, and 4 (10%) were not otherwise specified (NOS). Seven patients had stem cell transplant (SCT) prior to CBT: 6 autologous (auto) and 1 allogeneic (allo). SCT occurred between 142 days and 8.3 years prior to treatment with CBT. The median number of treatments prior to CBT was 3 (range 1-9), and the median duration of response (DOR) to the treatment immediately prior to CBT was 2 months. The best response to CBT for these patients included: 4 partial response (PR), 11 SD, and 25 PD. Patients discontinued CBT due to PD (90%) and toxicity (10%). Post-CBT treatment regimens included standard chemotherapy (55%), targeted therapy (22.5%), and clinical trial drugs (22.5%). The overall response rate (ORR) to post-CBT treatment was 52.50% with 12 (30%) CR and 9 (22.5%) PR. Five patients (12.5%) had SD as their best response, and 14 (35.0%) PD. Of the patients with CR to post-CBT treatment, their best responses to CBT were PD for 6, SD for 4, and PR for 2. Currently, 13 patients have died: 12 from disease progression and 1 from AML, thus median overall survival (OS) has not been reached (Figure 1). Nine patients have not progressed on their subsequent therapy. For patients with CR, PR, or SD to post-CBT therapy, the median PFS is 12.5 months (Figure 2). The post-CBT treatment regimen used did not impact the survival outcome, and there is no significant evidence that post CBT treatment response and post CBT regimens are associated (Figure 3, Table 2). Fourteen patients had consolidative SCT after their post-CBT treatment: 11 allo and 3 auto. All of these patients remain alive and half have progressed. Conclusions: These data suggest that in a R/R NHL population, treatment with CBT may sensitize some patients to subsequent therapy even if they progress or do not respond to CBT. Patient survival and best response to post-CBT treatment were independent of the treatment regimen, but many of these treatments bridged patients to SCT. In many patients the post-CBT treatment responses with or without SCT were of a significantly greater duration than their pre-CBT DOR (2 months vs 1 year). For this population, especially if they are ineligible for SCT or CAR-T cell therapy, this may be a novel treatment approach. We plan to expand this analysis with additional patients prior to the December meeting. Disclosures Advani: Kura: Research Funding; Infinity: Research Funding; Kyowa: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Agensys: Research Funding; Janssen: Research Funding; Celgene: Research Funding; Bayer: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Forty Seven Inc.: Research Funding; Roche/Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Merck: Research Funding; Regeneron: Research Funding; Gilead/Kite: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Cell Medica: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Autolus: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Astra Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Participated in an advisory board, Research Funding; Millenium: Research Funding; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Herrera:Immune Design: Research Funding; AstraZeneca: Research Funding; Merck, Inc.: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Seattle Genetics: Research Funding; Gilead Sciences: Research Funding; KiTE Pharma: Consultancy, Research Funding; Genentech: Consultancy, Research Funding. Chen:Affimed: Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Seattle Genetics: Consultancy, Honoraria, Research Funding, Speakers Bureau; Millennium Pharmaceuticals: Consultancy, Research Funding; Genentech Inc.: Consultancy; Merck & Co., Inc.: Consultancy, Research Funding, Speakers Bureau. Ramchandren:Bristol-Myers Squibb: Consultancy; Seattle Genetics: Consultancy, Research Funding; Pharmacyclics LLC an AbbVie Company: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Merck: Research Funding. Assouline:Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Honoraria, Research Funding, Speakers Bureau; Pfizer: Honoraria, Research Funding, Speakers Bureau; Roche: Honoraria, Research Funding, Speakers Bureau; Novartis: Research Funding. Wagner-Johnston:Celgene: Research Funding; Merck: Research Funding; Novartis: Research Funding; JUNO: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; ADC Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees; ASTEX: Research Funding. Svoboda:Bristol-Myers Squibb: Consultancy, Research Funding; Regeneron: Research Funding; Merck: Research Funding; KITE: Consultancy; TG Therapeutics: Research Funding; Pharmacyclics: Consultancy, Research Funding; Kyowa: Consultancy; Seattle Genetics: Consultancy, Research Funding. Barta:Janssen: Membership on an entity's Board of Directors or advisory committees; Merck, Takeda, Celgene, Seattle Genetics, Bayer: Research Funding. Karmali:Gilead: Speakers Bureau; AstraZeneca: Speakers Bureau. Persky:Genentech: Honoraria; Morphosys (IDMC): Consultancy; Spectrum: Research Funding; Merck: Research Funding. Smith:BMS: Consultancy; Portola: Honoraria. Chavez:Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Speakers Bureau; Merck: Research Funding; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kite: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Humanigen: Consultancy. Diefenbach:Merck: Consultancy, Research Funding; Seattle Genetics: Consultancy, Research Funding; Incyte: Research Funding; Acerta: Research Funding; Millenium/Takeda: Research Funding; Denovo: Research Funding; Trillium: Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Genentech: 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 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: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,003

Scores du classifieur distillé par catégorie (deux têtes)

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

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 Opus0,019
Tête enseignante GPT0,279
Écart entre enseignants0,259 · 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

Citations1
Publié2018
Routes d'admission2
Résumé présentoui

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