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Enregistrement W3097090129 · doi:10.1182/blood-2020-136645

Risk Profiling of Relapsed/Refractory Diffuse Large B-Cell Lymphoma Patients By Measuring Circulating Tumor DNA

2020· article· en· W3097090129 sur OpenAlexaff
Alex F. Herrera, Samuel Tracy, Brandon Croft, Stephen Opat, Jill Ray, Lisa Musick, Joseph N. Paulson, Laurie H. Sehn, Yanwen Jiang

Notice bibliographique

RevueBlood · 2020
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueCancer Genomics and Diagnostics
Établissements canadiensBC Cancer Agency
Organismes subventionnairesnon disponible
Mots-clésBendamustineInternal medicineDiffuse large B-cell lymphomaRituximabMedicineOncologyLymphomaGastroenterology

Résumé

récupéré en direct d'OpenAlex

Introduction Early identification of patients (pts) with relapsed or refractory diffuse large B-cell lymphoma (R/R DLBCL) at high risk for treatment failure may allow for interventions to improve outcomes; however, known prognostic factors are inadequate. Circulating tumor DNA (ctDNA) has demonstrated the ability to identify previously untreated DLBCL pts at high risk of relapse (Kurtz et al. 2018). We assessed the potential for ctDNA to identify pts with R/R DLBCL receiving bendamustine and rituximab (BR) +/- polatuzumab (pola) at higher risk for disease progression. Methods GO29365 (NCT02257567) is a Phase Ib/II study comparing pola+BR versus BR in pts with transplant-ineligible R/R DLBCL and enrolled 80 pts (n=40 per randomized arm). The primary efficacy objective was independent review committee (IRC)-assessed complete response (CR) rate at primary response assessment (PRA, 6-8 weeks after Cycle 6, Day 1 or last dose of study drug). ctDNA was measured in available cohort samples using a customized DLBCL panel on a modified ctDNA CAPP-Seq workflow developed based on the prototype assay reported in Kurtz et al. 2018, with improvement of sensitivity and specificity. ctDNA was reported as mean mutant molecules per mL (MMPM). Plasma depleted whole blood from baseline was used as a source of germline DNA to filter non-tumor-specific variants. A total of 43 samples were available at baseline; eight pts without a paired germline were excluded from efficacy and correlative analyses. Of the 35 samples (n=21 Pola+BR; n=14 BR) with available germline data, paired samples were available for 25 pts at PRA. Detectable ctDNA (+/-) was determined using empirical p-values (<0.05) through a bootstrap algorithm (Newman et al. 2014, Pati et al. 2018). The proportions of pts with detectable ctDNA are reported by visit with 95% Clopper-Pearson binomial confidence intervals (CI). A Kruskal-Wallis test was used to compare ctDNA levels by response. Univariate and multivariate cox regression was used to correlate ctDNA levels with progression-free survival (PFS) and overall survival (OS). Results are reported descriptively without multiple testing correction. Results Intent-to-treat and biomarker evaluable populations were similar in demographics and efficacy, but there was a higher proportion of pola+BR versus BR pts assayed (60% vs 40%). Analyses are reported for the pooled arms, but results were consistent across both arms. ctDNA was detected in all available baseline (n=43) samples (95% CI: 92-100). Baseline ctDNA levels were correlated with known prognostic factors including International Prognostic Index (IPI), lactate dehydrogenase (LDH), Ann Arbor stage and number of prior therapies (Figure 1A). Higher ctDNA levels at baseline were negatively prognostic; when stratifying pts by median ctDNA levels the hazard ratio (HR) for PFS was 0.16 (95% CI: 0.07-0.41; Figure 1B); OS HR 0.23 (95% CI: 0.10-0.52). Similar results were observed for other quartile stratifications. This significant trend was maintained when adjusted in multivariate analysis for treatment, IPI >3, and LDH > upper limit of normal with an adjusted HR for PFS of 0.24 (95% CI: 0.07-0.81) and for OS an adjusted HR of 0.30 (95% CI: 0.09-0.97). Similar to the first-line setting (Kurtz et al. 2018), on-treatment log fold-changes in ctDNA trended with PRA response (Figure 1C); pts with a CR had a significantly greater average decrease in MMPM across timepoints than non-CR pts (Wilcoxon p-value <0.001). At PRA, four pts (three in pola+BR, one in BR) had cleared ctDNA, potentially due to treatment, all of which achieved CR. ctDNA was detectable in the remaining patients (n=25, 84%, 95% CI: 64-95). There was no clear trend between log fold reduction of ctDNA at PRA and PFS in this cohort, though this analysis is limited by sample size. Conclusions Baseline ctDNA levels were correlated with standard clinical risk factors, and were shown to have independent prognostic value for response, PFS and OS in R/R DLBCL pts treated with BR +/- pola. The degree of ctDNA change upon treatment was also correlated with response, but association with PFS needs further investigation with a larger sample size. This provides early evidence that ctDNA can be used to improve identification of R/R DLBCL pts at high risk for disease progression/relapse. Figure Disclosures Herrera: AstraZeneca: Research Funding; Karyopharm: Consultancy; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Immune Design: Research Funding; Seattle Genetics: Consultancy, Research Funding; Gilead Sciences: Consultancy, Research Funding; Pharmacyclics: Research Funding; Merck: Consultancy, Research Funding; Bristol Myers Squibb: Consultancy, Other: Travel, Accomodations, Expenses, Research Funding. Tracy:F. Hoffmann-La Roche: Current Employment, Current equity holder in publicly-traded company; Genentech, Inc.: Current Employment. Croft:Genentech, Inc.: Current Employment, Current equity holder in publicly-traded company, Divested equity in a private or publicly-traded company in the past 24 months. Opat:Merck: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZenca: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Research Funding; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; CSL: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Mundipharma: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Epizyme: Research Funding; F. Hoffman-La Roche Ltd: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel accomodations, Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Ray:F. Hoffmann-La Roche Ltd: Current Employment, Current equity holder in publicly-traded company; Genentech, Inc.: Current Employment. Musick:F. Hoffmann-La Roche Ltd: Current equity holder in publicly-traded company; Roche/Genentech, Inc.: Current Employment. Paulson:F. Hoffmann-La Roche Ltd.: Current Employment, Current equity holder in publicly-traded company. Sehn:Chugai: Consultancy, Honoraria; Servier: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Teva: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Research Funding; MorphoSys: Consultancy, Honoraria; Merck: Consultancy, Honoraria; Lundbeck: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Kite: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Acerta: Consultancy, Honoraria; Genentech, Inc.: Consultancy, Honoraria, Research Funding; AstraZeneca: Consultancy, Honoraria; Apobiologix: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Verastem Oncology: Consultancy, Honoraria; TG therapeutics: Consultancy, Honoraria. Jiang:F. Hoffmann-La Roche: Current equity holder in publicly-traded company; Genentech, Inc.: Current Employment.

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 enseignants0,002
Score d'incertitude au seuil0,006

Scores du classifieur distillé par catégorie (deux têtes)

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

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 Opus0,007
Tête enseignante GPT0,190
Écart entre enseignants0,183 · 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

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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