MétaCan
Menu
Retour à la cohorte
Enregistrement W2951482915 · doi:10.1002/hon.99_2630

EXPLORATORY BIOMARKER ANALYSIS IN THE PH 3 ECHELON‐1 STUDY: WORSE OUTCOME WITH ABVD IN PATIENTS WITH ELEVATED BASELINE LEVELS OF SCD30 AND TARC

2019· article· en· W2951482915 sur OpenAlexaff
John Radford, Joseph M. Connors, Anas Younes, Andrea Gallamini, Stephen M. Ansell, W.S. Kim, June‐Won Cheong, Ian W. Flinn, Nagesh Kalakonda, Mark Kaminski, Ruth Pettengell, Matthew Onsum, Neil C. Josephson, Shingo Kuroda, R. Liu, Harry Miao, Ashish Gautam, William L. Trepicchio, Anna Sureda

Notice bibliographique

RevueHematological Oncology · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensSpinal Cord Injury BC
Organismes subventionnairesnon disponible
Mots-clésMedicineBrentuximab vedotinInternal medicineDacarbazineOncologyABVDBiomarkerPost-hoc analysisProgression-free survivalGastroenterologyLymphomaOverall survivalCD30VincristineChemotherapyCyclophosphamide

Résumé

récupéré en direct d'OpenAlex

Introduction: Soluble (s)CD30 and thymus and activation-regulated chemokine (TARC) are established prognostic biomarkers in Hodgkin lymphoma (HL): higher baseline serum levels are associated with poorer survival outcomes. Elevated sCD30 and TARC levels are also associated with established poor prognostic factors in HL, e.g. Stage IV disease, higher International Prognostic Score (IPS), and extranodal involvement (ENI). The phase 3 ECHELON-1 study compared frontline brentuximab vedotin (a CD30-directed antibody-drug conjugate) plus doxorubicin, vinblastine, and dacarbazine (A+AVD) vs ABVD in patients (pts) with advanced classical HL (cHL). A+AVD demonstrated superior modified progression-free survival (modified PFS) vs ABVD (HR = 0.77 [95% CI 0.60–0.98]; p = 0.035; 2-yr mPFS 82.1% vs 77.2%. An exploratory ad-hoc biomarker analysis evaluated mPFS according to baseline sCD30 and TARC levels. Methods: Serum samples were collected from 1334 pts with Stage III (36%) or IV (64%) cHL during the screening period and analyzed using validated assays for sCD30 (Covance Labs) and TARC (ICON Labs). mPFS (defined as time to progression, death, or evidence of noncomplete response followed by subsequent anticancer therapy) per independent review facility (IRF) was analyzed according to baseline sCD30 and TARC levels; the association of biomarker levels with treatment outcomes along with other potential predictive factors was explored in a multivariate Cox model. Results: For the ad-hoc sCD30 analysis, pts were dichotomized around the median sCD30 baseline level (207.9 ng/mL). Pts in the A+AVD arm performed similarly regardless of baseline sCD30 level, with a 2-yr mPFS of 80.7% (sCD30 >median) and 82.7% (sCD30 ≤median). However, a decrease in effectiveness of ABVD was observed in pts with sCD30 >median with a 2-yr mPFS of 68.9% [sCD30 >median] and 85.7% [sCD30 ≤median]). A mPFS benefit in favor of A+AVD vs ABVD was observed in pts with sCD30 >median (HR (95% CI) = 0.600 (0.428-0.841)) . Multivariate Cox analysis with the interaction between treatment group and sCD30 level showed an increased risk of experiencing an mPFS event with ABVD and sCD30 >median (interaction p = 0.025) when adjusted by other prognostic factors (Ann Arbor stage, IPS and ENI). Similar trends were observed with the exploratory ad-hoc TARC analysis. No new safety signals were reported in subgroups with elevated sCD30 or TARC levels. Conclusions: Preliminary adhoc analysis indicates that ABVD treated patients do not perform as well with elevated baseline sCD30 and TARC levels. A+AVD treated patients perform well regardless of levels of these poor prognostic markers. Prospective studies need to be conducted in order to further validate these findings. If validated, these biomarkers may help identify patient populations that could benefit from more effectively targeted therapy. Keywords: ABVD; brentuximab vedotin; classical Hodgkin lymphoma (cHL). Disclosures: Radford, J: Consultant Advisory Role: Millennium Pharmaceuticals Inc, ADC Therapeutics, BMS, Novartis; Stock Ownership: GSK, AstraZeneca (spouse); Honoraria: Millennium Pharmaceuticals Inc, Seattle Genetics, Novartis, BMS; Research Funding: Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited. Connors, J: Consultant Advisory Role: Seattle Genetics, Millennium Pharmaceuticals Inc; Honoraria: Seattle Genetics, Millennium Pharmaceuticals Inc; Research Funding: Seattle Genetics. Younes, A: Consultant Advisory Role: BMS, Incyte, Janssen, Genentech, Merck; Honoraria: Genentech, Merck, Millennium Pharmaceuticals Inc, Incyte, BMS, AbbVie; Research Funding: Novartis, J&J, Curis, Roche, BMS. Ansell, S: Research Funding: BMS, Seattle Genetics, Trillium, Affimed, Pfizer, LAM Therapeutics, Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited. Kim, W: Research Funding: Roche, Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited, J&J, Mundupharma, Kyowa-kirin, Celltrion, DongaN. Flinn, I: Consultant Advisory Role: Abbvie, Seattle Genetics, TG Therapeutics, Verastem; Research Funding: Abbvie, Acerta Pharma, Agios, ArQule, AstraZeneca, BeiGene, Calithera Biosciences, Celgene, Constellation Pharmaceuticals, Curis, FORMA Therapeutics, Forty Seven, Genentech, Gilead Sciences, Incyte, Infinity Pharmaceuticals, Janssen, Juno Therapeutics, Karyopharm Therapeutics, Kite Pharma, Merck, MorphoSys AG, Novartis, Pfizer, Pharmacyclics, Portola Pharmaceuticals, Roche, Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited, Teva, TG Therapeutics, Trillium Therapeutics, Unum Therapeutics, Verastem. Pettengell, R: Consultant Advisory Role: CTI Life Sciences Ltd, Immune Design, Pfizer, Roche Ltd, Servier, Millennium Pharmaceuticals Inc, TEVA; Honoraria: CTI Life Sciences Ltd, Immune Design, Pfizer, Roche Ltd, Servier, Millennium Pharmaceuticals Inc, TEVA. Onsum, M: Employment Leadership Position: Seattle Genetics; Stock Ownership: Seattle Genetics. Josephson, N: Employment Leadership Position: Seattle Genetics, Inc.; Stock Ownership: Seattle Genetics, Inc.. Kuroda, S: Employment Leadership Position: Takeda Pharmaceutical Company Limited. Liu, R: Employment Leadership Position: Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited. Miao, H: Employment Leadership Position: Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited. Gautam, A: Employment Leadership Position: Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited; Stock Ownership: Takeda Pharmaceutical Company Limited. Trepicchio, W: Employment Leadership Position: Millennium Pharmaceuticals, Inc., a wholly owned subsidiary of Takeda Pharmaceutical Company Limited. Sureda, A: Consultant Advisory Role: Millennium Pharmaceuticals Inc, BMS, Gilead, Novartis; Honoraria: Millennium Pharmaceuticals Inc, BMS, MSD, Gilead, Novartis, Jannssen, Celgene, Sanofi, Roche.

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)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut 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 enseignants0,012
Score d'incertitude au seuil0,363

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
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)0,0000,000

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 Opus0,046
Tête enseignante GPT0,320
Écart entre enseignants0,275 · 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.

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
Publié2019
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueHematological OncologyMême sujetLymphoma Diagnosis and TreatmentTravaux en français237 207