MétaCan
Menu
← Retour à la cohorte
Enregistrement W3097649246 · doi:10.1182/blood-2020-135935

Prognostication for Advanced Stage Hodgkin Lymphoma (HL) in the Modern Era: A Project from the Hodgkin Lymphoma International Study for Individual Care (HoLISTIC) Consortium

2020· article· en· W3097649246 sur OpenAlexaff
Angie Mae Rodday, Susan K. Parsons, Carlton Scharman, Ranjana H. Advani, Massimo Federico, Jonathan W. Friedberg, Andrea Gallamini, David Hodgson, Peter Hoskin, Martin Hutchings, Peter Johnson, Kara M. Kelly, Brian K. Link, John Radford, Pier Luigi Zinzani, James R. Cerhan, John Raemaekers, Andrew M. Evens

Notice bibliographique

RevueBlood · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensPrincess Margaret Cancer CentreUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésHodgkin lymphomaLymphomaMedicineStage (stratigraphy)Internal medicineOncologyBiology

Résumé

récupéré en direct d'OpenAlex

Background: While HL is a highly curable cancer, patients (pts) with advanced stage disease experience increased risk of relapse. Delineation of prognosis is desired to compare cohorts and outcomes between trials, and to define groups of pts for whom reduction in treatment may be appropriate or where novel therapeutic approaches are needed. The International Prognostic Score (IPS), which was derived from a discovery set of 1,618 HL pts with complete data, was a seminal publication in the field (Hasenclever and Diehl NEJM 1998). However, these data were published >20 years ago with a significant minority of pts having received chemotherapy regimens no longer in clinical use. More contemporary analyses have shown altered utility of the IPS (e.g., Moccia JCO 2012; Diefenbach BJH 2015). In addition, prior studies identified bulk disease as an adverse prognostic factor in advanced stage HL (Laskar JCO 2004; Johnson JCO 2010). Our objective was to leverage individual pt data (IPD) from HoLISTIC (www.hodgkinconsortium.com) to discover a new, robust, and modern prognostication index for advanced-stage HL pts applicable to diverse settings across the world. Methods: We created a data repository of IPD from clinical trials for newly diagnosed HL pts, which includes 4,085 advanced-stage (III or IV) pts treated in 8 large, prospective studies completed in the modern era (ie, IIL HD9601: Gobbi JCO 2005; Italian HD2000: Federico JCO 2009; ECOG 2496: Gordon JCO 2013; SWOG 0816: Press JCO 2016; IIL HD0801: Zinzani JCO 2016; RATHL: Johnson NEJM 2016; GITIL HD0607: Gallamini JCO 2017; and COG AHOD 0831: Kelly BJH 2019) as well as prominent cancer registries (eg, the Mayo/Iowa Molecular Epidemiologic Resource (MER)). The discovery analysis herein included pts from the ECOG 2496, HD0801 IIL, GITIL HD0607, and SWOG 0816 studies. Furthermore, it was restricted to pts (n=1,279) on these trials with complete data for all 9 covariates of interest: age; sex; advanced stage (III vs IV); B symptoms; any bulk; and values of hemoglobin, white blood count (WBC), lymphocyte count, and albumin. Using Cox proportional hazard (PH) models, we evaluated univariate associations between 5-year progression-free survival (PFS) and overall survival (OS) with the aforementioned prognostic variables. Age was categorized based on plots and optimum model fit (c statistic). Lab values were dichotomized using cut-points from the 1998 IPS. Per convention, treatment factors were not included in the model. To identify independent prognostic factors of PFS and OS, a parsimonious Cox PH model was fit using backward selection of all potential risk factors (P<0.05). Hazard ratios (HR) with 95% confidence interval (CI) were reported. Kaplan Meier (KM) plots were also reported for risk factors in the multivariable (MVA) models to visualize differences. Results: Among all pts, characteristics included: median age of 32.9 years (IQR 25.4-44, range 15-83); 55% male; 49% stage IV; 63% B symptoms; 26% bulk >10 cm; 20% hemoglobin <10.5 g/dL; 15% WBC count ≥15,000/mm3; 9% lymphocyte count <600/mm3; and 63% with albumin <4g/dL. For analysis of age, we observed a U-shaped relationship with PFS (Fig A), which helped delineate optimal cut points of 15-24 years (23.1%), 25-49 years (61.4%), and ≥50 years (15.6%). In univariate analysis: age, stage, B symptoms, bulk, anemia, low lymphocyte count, and low albumin were associated with worse survival. In the MVA model, age >50 years, stage IV disease, B symptoms, and bulky disease were associated with worse PFS; and age >50 years, stage IV disease, bulky disease, anemia, and low albumin were associated with worse OS (Fig B). KM plots for age, stage, and bulk are presented in Fig C. Conclusions. In this international, multi-study analysis of advanced stage HL in the modern era, we identified several factors that were associated with both worse PFS and OS on MVA (ie, age, stage IV disease, and bulky disease). The finding of bulky disease as a significant prognostic factor warrants further investigation. In addition, we detected an age-related U-shaped impact on PFS with inferior outcomes for pts ages 15-25 years and ≥50 years, the latter in an increasing linear fashion. Altogether, these data will serve as a training cohort for a modern HL prognostication index that will be augmented and analyzed with a large independent validation cohort (vis-à-vis the remaining HL data in the HoLISTIC consortium), which will be presented at the ASH meeting. Disclosures Parsons: Seattle Genetics: Consultancy. Advani:Astra Zeneca, Bayer Healthcare Pharmaceuticals, Cell Medica, Celgene, Genentech/Roche, Gilead, KitePharma, Kyowa, Portola Pharmaceuticals, Sanofi, Seattle Genetics, Takeda: Consultancy; Celgene, Forty Seven, Inc., Genentech/Roche, Janssen Pharmaceutical, Kura, Merck, Millenium, Pharmacyclics, Regeneron, Seattle Genetics: Research Funding. Federico:Spectrum: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sandoz: Consultancy, Membership on an entity's Board of Directors or advisory committees; Mundipharma s.r.l.: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Millennium/Takeda: Research Funding; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Cephalon/Teva: Research Funding. Friedberg:Acerta Pharma - A member of the AstraZeneca Group, Bayer HealthCare Pharmaceuticals.: Other; Bayer: Consultancy; Kite Pharmaceuticals: Research Funding; Portola Pharmaceuticals: Consultancy; Roche: Other: Travel expenses; Seattle Genetics: Research Funding; Astellas: Consultancy. Hutchings:Genmab: Research Funding; Janssen: Research Funding; Roche: Consultancy; Genmab: Consultancy; Takeda: Consultancy; Roche: Research Funding; Celgene: Research Funding; Daiichi: Research Funding; Sankyo: Research Funding; Novartis: Research Funding; Sanofi: Research Funding; Takeda: Research Funding; Roche: Honoraria; Genmab: Honoraria; Takeda: Honoraria. Johnson:MorphoSys: Honoraria; Kymera: Honoraria; Kite Pharma: Honoraria; Incyte: Honoraria; Celgene: Honoraria; Epizyme: Consultancy, Research Funding; Novartis: Honoraria; Takeda: Honoraria; Oncimmune: Consultancy; Boehringer Ingelheim: Consultancy; Janssen: Consultancy; Oncimmune: Consultancy; Janssen: Consultancy; Genmab: Honoraria; Bristol-Myers: Honoraria; Epizyme: Consultancy, Research Funding. Radford:Novartis: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Speakers Bureau; ADCT: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding; Seattle Genetics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; GlaxoSmithKline: Current equity holder in publicly-traded company, Other: Spouse; AstraZeneca: Current equity holder in publicly-traded company, Other: Spouse; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Zinzani:MSD: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Incyte: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees; EUSA Pharma: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Sandoz: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Immune Design: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Eusapharma: Consultancy, Speakers Bureau; Verastem: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Kyowa Kirin: Consultancy, Speakers Bureau; TG Therapeutics, Inc.: Honoraria, Speakers Bureau; Kirin Kyowa: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Servier: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen-Cilag: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celltrion: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; ADC Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Portola: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Immune Design: 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, Spea

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)0,021
score de la tête « metaresearch » (Gemma)0,022
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 enseignants0,021
Score d'incertitude au seuil0,109

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0210,022
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,004
Études des sciences et des technologies0,0000,000
Communication savante0,0020,001
Science ouverte0,0010,004
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

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 Opus0,068
Tête enseignante GPT0,333
Écart entre enseignants0,265 · 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

Citations4
Publié2020
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueBlood→Même sujetLymphoma Diagnosis and Treatment→Travaux en français237 207→