Patient Subgroup Analysis of Quality-of-Life Outcomes in Checkmate 205, a Phase 2 Study of Nivolumab in Patients with Classical Hodgkin Lymphoma
Notice bibliographique
Résumé
Abstract Introduction: Nivolumab is a fully human IgG4 immune checkpoint inhibitor targeting programmed death receptor-1 (PD-1). It has recently been approved by the FDA in the US for patients with classical Hodgkin lymphoma (cHL) who have failed autologous hematopoietic stem cell transplantation (auto-HSCT) and post-transplant brentuximab vedotin (cohort B of CheckMate 205). The objective response rates in cohort B of CheckMate 205 (NCT02181738) per independent radiologic review committee (IRRC) assessment was 66%, with median time to response of 2.1 months. Furthermore, mean EuroQol Five Dimensions (EQ-5D) visual analog scale (VAS) score increased over time during treatment with nivolumab, and European Organisation for Research and Treatment of Cancer Core Quality-of-Life questionnaire (EORTC QLQ-C30) data suggested an improvement from baseline (BL) across functional, symptom, and global health scores [Younes et al. Lancet Oncol 2016; Jul 20 (Epub ahead of print)]. The aim of the current analysis is to understand if quality-of-life (QoL) changes observed in the cohort of patients with cHL vary across patient subgroups. Methods: CheckMate 205 is a multi-cohort study evaluating the efficacy and safety of nivolumab 3 mg/kg by IV infusion every 2 wks in 3 cohorts of patients with cHL post-auto-HSCT. Patient-reportedgeneral health status was assessed using the 3-level version of the EQ-5D questionnaire, and cancer-specific QoL using the EORTC QLQ-C30. Questionnaires were administered to patients every 4 cycles (every 8 wks). All treated patients with BL and at least 1 post-BL assessment in cohort B were included in this analysis population. Scores were examined across prespecified patient subgroups, including age, sex, Eastern Cooperative Oncology Group (ECOG) performance status (PS) at BL, smoking status, B symptoms at BL, region (USA/Canada or Europe), and best overall response (BOR) per investigator assessment or IRRC at wks 9, 17, 25, and 33. Least squares (LS) means were used to describe post-BL score changes over time for the overall analysis population and subgroups. Minimally important differences were prespecified. Results: 72 patients (90%) from CheckMate 205, cohort B, completed BL and at least 1 post-BL EORTC QLQ-C30 or EQ-5D assessment. By wk 33, 58% of patients were included. The mean (SD) age was 38.9 (13.3) years. 34.7% of patients were female, 45.8% had BL ECOG PS 1, and 68.1% had stage IV disease at study entry. LS mean (standard error) score change from BL at wk 33 was 19.1 (3.1) for EQ-5D VAS and 7.6 (2.3) for the EORTC QLQ-C30 global health/QoL status scale. For the global health status subscale, all subgroup estimates were consistent with the overall changes from BL, except patients with absence of B symptoms who experienced significantly smaller changes at wk 17 only. For other EORTC subscales where statistically significant improvements in LS mean from BL were observed at each time point (fatigue, dyspnea, appetite loss, physical functioning, role functioning), although all subgroup estimates were in line with the overall change, there were some trends for non-smokers (vs smokers), ECOG PS 0 (vs 1), USA/Canada (vs Europe), and B symptoms at BL (vs none) toward better symptom improvement. Changes from BL across responders and non-responders were consistent with overall changes from BL. Conclusions: In this small cohort of patients with cHLwho had failed auto-HSCT and subsequent brentuximab vedotin, the improvement in QoL observed while on-treatment with nivolumab was mostly consistent across the subgroups investigated. Funding: Bristol-Myers Squibb (BMS). Medical writing: S Addison, Caudex, funded by BMS. Disclosures Engert: Takeda, BMS: Consultancy, Honoraria, Research Funding. Taylor:Bristol-Myers Squibb: Consultancy. Bennett:Bristol-Myers Squibb: Consultancy. Hirji:Bristol-Myers Squibb: Employment. Cocks:Bristol-Myers Squibb: Consultancy. McDonald:Bristol-Myers Squibb: Consultancy. Mann:Bristol-Myers Squibb: Consultancy. Kato:Bristol-Myers Squibb: Employment. Cella:Alexion, Inc., Astellas, Biogen Idec, Celgene, Clovis Oncology, Inc., Daiichi Sankyo, Eli Lilly, Evidera, Inc., Exelixis, Fiborgen, Genetech, Helsinn Therapeutics, Inc., Immunogen, Ipsen Pharma, Janssen, Lexicon Pharmaceuticals, Inc., Merck, Novartis, Onc: Consultancy, Research Funding; Bristol-Meyers Squibb: Consultancy, Research Funding; Abbvie, Inc.: Consultancy, Research Funding; GlaxoSmithKline: Consultancy, Research Funding; Bayer Pharmaceuticals, Inc.: Consultancy, Research Funding; Facit.org: Other: President.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,003 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».