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Record W2907100365 · doi:10.1182/blood-2018-99-112067

Nivolumab for Relapsed or Refractory Classical Hodgkin Lymphoma (cHL) after Autologous Hematopoietic Cell Transplantation (auto-HCT): Extended Follow-up of the Phase 2 Single-Arm CheckMate 205 Study

2018· article· en· W2907100365 on OpenAlexaffabout
Philippe Armand, Andreas Engert, Anas Younes, Hun Ju Lee, Armando Santoro, Pier Luigi Zinzani, John M. Timmerman, Graham P. Collins, Radhakrishnan Ramchandren, Jonathon B. Cohen, Jan Paul de Boer, Kerry J. Savage, John Kuruvilla, Marek Trněný, Margaret A. Shipp, Mariana Sacchi, Anne Sumbul, Stephen M. Ansell

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicLymphoma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineCohortInternal medicineNivolumabOncologyClinical endpointTransplantationRefractory (planetary science)Brentuximab vedotinPhases of clinical researchSurgeryLymphomaToxicityClinical trialCancerImmunotherapyHodgkin lymphoma

Abstract

fetched live from OpenAlex

Abstract Introduction: Genetic alterations at 9p24.1 resulting in overexpression of programmed death-1 (PD-1) ligands are near-universal in cHL (Roemer et al, J Clin Oncol 2016); cHL may thus be uniquely sensitive to PD-1 blockade. Nivolumab (nivo), an anti-PD-1 monoclonal antibody, was associated with an objective response rate (ORR) of 69% in relapsed/refractory (R/R) cHL after auto-HCT and irrespective of prior brentuximab vedotin (BV) in the phase 2 CheckMate 205 study (Armand et al, J Clin Oncol 2018; NCT02181738). Whether some patient (pts) can derive very long clinical benefit, whether depth of response predicts long-term outcome, whether treatment (Tx) can be interrupted in complete remission (CR), and whether the safety profile of nivo in R/R cHL changes with prolonged Tx all remain unclear. We therefore present an updated analysis of CheckMate 205, focusing on long-term efficacy and safety. Methods: This international, single-arm, multi-cohort study enrolled pts aged ≥18 y with R/R cHL after auto-HCT. Pts were BV naïve (Cohort A), had prior BV failure after auto-HCT (Cohort B), or had received BV before and/or after auto-HCT (Cohort C). Pts received nivo 3 mg/kg every 2 wk until disease progression (PD)/unacceptable toxicity. Pts in Cohort C discontinued nivo after 1 y in CR and could resume if they relapsed within 2 y of the last dose. Primary endpoint was ORR per independent radiology review committee (IRC); additional endpoints included duration of response (DOR) per IRC, progression-free survival (PFS) per IRC, overall survival (OS), and safety. Time to next Tx (TTNT: time from first dose to next systemic Tx or death) was an exploratory post-hoc analysis. Responses were assessed using International Working Group 2007 criteria. Results: In total, 243 pts were enrolled to Cohorts A (n=63), B (n=80), and C (n=100). Baseline characteristics have been previously described (Armand et al, J Clin Oncol 2018). At data cut-off, minimum follow-up was 31 mo and 49 pts (20%) were still on Tx; the most common reason for discontinuation was PD (35%). Median duration of Tx was 14 mo. ORR per IRC was 71% (65%, 71%, 75% in Cohorts A, B, C, respectively) with a best overall response (BOR) of CR in 21% (32%, 14%, 20% in Cohorts A, B, C, respectively). Among 51 pts who achieved CR, 20 had CR as the first response and 31 improved from partial remission (PR), mostly (n=28/31) within 1 year of first PR. Median time to response was 2 mo, and to CR was 4 mo. Within the first 6, 12, and 18 mo, 68%, 71%, and 71% of pts, respectively, achieved a response. Median DOR was 18 mo overall, and was 32 and 13 mo in pts with a BOR of CR and PR, respectively. Among responders, 64%, 44%, 31%, and 21% of pts had a DOR of at least 6, 12, 18, and 24 mo, respectively. Overall, 11 pts in Cohort C discontinued with persistent investigator-assessed CR; 2 reinitiated nivo due to PD. Median (95% CI) PFS per IRC among all pts was 15 (11-19) mo (Figure A), and was 17, 12 and 15 mo in Cohorts A, B, and C, respectively. Median OS was not reached in any cohort; 24-mo OS rates were 90%, 86%, and 86% in Cohorts A, B, and C, respectively, and were similar among pts in CR, PR, or with stable disease (SD; Figure B). Median TTNT was 29, 27, and 20 mo in Cohorts A, B, and C, respectively. The most common Tx-related adverse events (AEs) of any grade (G) were fatigue (24%), diarrhea (16%), and rash (12%), each <1% G3-4. Tx-related infections were reported in 15% of pts, 2% G3-4. Tx-related infusion related reactions were reported in 34 pts (14%), <1% G3-4. The most commonly reported immune-mediated AE category was rash, which was G3-4 in 4 pts (2%). In total, 26 pts (11%) experienced an AE of any cause leading to discontinuation. There were no Tx-related deaths. Conclusions: With the longest phase 2-3 study follow-up of a checkpoint inhibitor in R/R cHL to date, nivo was associated with frequent and durable responses regardless of BV Tx history. More than 1 in 5 responders remained in response ≥2 years later. With extended follow-up, additional pts achieved CR in all cohorts. Pts with CR had longer PFS than pts with PR or SD. However, pts with both PR and SD had prolonged OS, unlike pts with PD, which may suggest that clinical benefit duration is not well predicted by conventional response criteria. Nivo continued to be well tolerated, with no new safety signals. Characteristics of long-term responders will be presented. Study support: BMS. Medical writing: A Gill, Caudex, funded by BMS Figure. Figure. Disclosures Armand: Infinity: Consultancy; Affimed: Consultancy, Research Funding; Pfizer: Consultancy; Otsuka: Research Funding; Adaptive: Research Funding; Merck: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Roche: Research Funding; Tensha: Research Funding. Younes:Celgene: Honoraria; Genentech: Research Funding; Janssen: Honoraria, Research Funding; Bayer: Honoraria; Novartis: Research Funding; J&J: Research Funding; Astra Zeneca: Research Funding; BMS: Honoraria, Research Funding; Merck: Honoraria; Abbvie: Honoraria; Takeda: Honoraria; Seattle Genetics: Honoraria; Roche: Honoraria, Research Funding; Sanofi: Honoraria; Incyte: Honoraria; Curis: Research Funding; Pharmacyclics: Research Funding. Zinzani:PFIZER: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; TG Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees; Verastem: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; PFIZER: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Honoraria, Speakers Bureau; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; MSD: Honoraria, Speakers Bureau; Celltrion: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Merck: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bayer: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Speakers Bureau; Merck: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; SERVIER: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; TG Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bayer: Membership on an entity's Board of Directors or advisory committees. Collins:ADC Therapeutics: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Speakers Bureau; Celleron: Consultancy, Honoraria; Gilead: Consultancy, Honoraria, Speakers Bureau; Pfizer: Consultancy, Honoraria; Roche: Consultancy, Honoraria, Speakers Bureau; Celgene Corporation: Research Funding; BMS: Consultancy, Honoraria, Research Funding; MSD: Consultancy, Honoraria; Amgen: Research Funding. Ramchandren:Merck: Research Funding; Bristol-Myers Squibb: Consultancy; Seattle Genetics: Consultancy, Research Funding; Pharmacyclics LLC an AbbVie Company: Consultancy, Research Funding; Janssen: Consultancy, Research Funding. Cohen:Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BioInvent: Consultancy; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Janssen: Research Funding; Takeda: Research Funding; Seattle Genetics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Infinity Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Consultancy, Membership on an entity's Board of Directors or advisory committees; Millennium: Consultancy, Membership on an entity's Board of Directors or advisory committees. De Boer:Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; MSD: Membership on an entity's Board of Directors or advisory committees; EISA: Membership on an entity's Board of Directors or advisory committees. Kuruvilla:Lundbeck: Honoraria; Gilead: Consultancy, Honoraria; Seattle Genetics: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Princess Margaret Cancer Foundation: Research Funding; Leukemia and Lymphoma Society Canada: Research Funding; Abbvie: Consultancy; Merck: Consultancy, Honoraria; Karyopharm: Honoraria; Roche: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria; Amgen: Honoraria; Celgene: Honoraria. Trněný:F. Hoffman-La Roche Ltd: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory board, Research Funding; Sandoz: Honoraria; Gilead: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory board; Abbvie: Honoraria, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Advisory board; Incyte: Membership on an entity's Board of Directors or advisory committees, Other: Advisory board; Morphosys: Membership on an entity's Board

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.281
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations19
Published2018
Admission routes2
Has abstractyes

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