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Enregistrement W3212675168 · doi:10.1182/blood-2021-144820

Early Integration of High Dose Methotrexate to Frontline DLBCL Therapy Does Not Impact CNS Relapse Compared to End of Treatment Delivery: A Multicentre International Analysis of 1384 Patients

2021· article· en· W3212675168 sur OpenAlexaff
Matthew R. Wilson, Toby A. Eyre, Amy A. Kirkwood, Nicole Wong Doo, Carole Soussain, Sylvain Choquet, Nicolas Martinex-Calle, Gavin Preston, Matthew J. Ahearne, Elisabeth Schorb, Marie‐Pierre Moles‐Moreau, Matthew Ku, Chiara Rusconi, Jahanzaib Khwaja, Mayur Narkhede, Katharine L. Lewis, Teresa Calimeri, Éric Durot, Loïc Renaud, Andreas Kiesbye Øvlisen, Graham McIlroy, Tim Ebsworth, Johnathon Elliot, Anna Santarsiere, Laure Ricard, Nimish Shah, Qin Liu, Adam Zayac, Francesco Vassallo, Laure Lebras, Louise Roulin, Naëlle Lombion, Kate Manos, Rubén Fernández, Nada Hamad, Alberto López‐García, Deirdre O’Mahony, Praveen Gounder, Nathalie Forgeard, Charlotte Lees, Kossi Agbétiafa, Tim Strüßmann, Thura Win Htut, Aline Clavert, Hamish W Scott, Anna Guidetti, Brett Barlow, Jeffrey W. Smith, Tarec Christoffer El‐Galaly, Chan Y. Cheah, Andrés JM Ferreri, Fiona Miall, Christopher P. Fox, Kate Cwynarski, Pam McKay

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueCNS Lymphoma Diagnosis and Treatment
Établissements canadiensPrincess Margaret Cancer Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineMethotrexateInternal medicinePrimary central nervous system lymphomaOncologyDiffuse large B-cell lymphomaProportional hazards modelLymphomaSurgery

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: Central nervous system (CNS) relapse in diffuse large B-cell lymphoma (DLBCL) is uncommon but is associated with poor outcomes. In selected high risk patients (pts), high dose methotrexate (HDMTX) is often used as CNS prophylaxis with frontline (1L) DLBCL therapy despite uncertain efficacy, optimum dose and timing of delivery. A recent UK study (Wilson et al 2020) showed that intercalated HDMTX (i-HDMTX) was associated with increased toxicity and R-CHOP delays compared to end of treatment (EOT) delivery. Although hypothesis generating, the study size was insufficient to determine whether EOT was non-inferior in terms of CNS relapse risk. Methods: We conducted an international, multicentre retrospective analysis of consecutive DLBCL or high grade BCL pts between 2007-20 from 47 centers in Europe, Australia and N. America. Pts were included if they received R-CHOP or R-CHOP-like 1L therapy with curative intent as well as HDMTX CNS prophylaxis (≥1 cycle). Concurrent intrathecal (IT) prophylaxis was permitted. Pts with known CNS involvement at baseline and those treated with more intensive protocols (e.g. R-DA-EPOCH) were excluded. i-HDMTX was defined as any pt receiving a HD-MTX cycle before the final R-CHOP cycle. CNS relapse events were excluded if occurring after first systemic lymphoma relapse/progression. Time to event endpoints were measured from diagnosis to first event or censor and analysed using Kaplan-Meier and Cox regression methods. Time to CNS relapse was analysed using competing risk Fine and Gray method (for death and non-synchronous systemic relapse). To mitigate for possible immortality bias in the EOT arm, a landmark analysis for pts alive and free from progression at 6 months was conducted. We aimed to exclude a 5% difference in 2-year (y) CNS relapse rates. Results: 1,384 pts were analysed. 750 received i-HDMTX and 634 received EOT HDMTX. Key baseline characteristics are summarised in Table 1. Median follow up was 37.9 months. 44.2% had high CNS IPI (4-6) with no significant difference between i-HDMTX and EOT groups (45.1% vs 43.1%, p=0.087). ≥2 cycles of HDMTX were used in 86.6% with no difference between groups (85.6% vs 87.9%, p=0.22). Concurrent IT prophylaxis use was higher for EOT pts (55.6% vs 38.1% p<0.0001). 78 CNS relapses (42 i-HDMTX, 36 EOT) were observed: parenchymal in 41 (53%), parenchymal and leptomeningeal in 16 (21%) and isolated leptomeningeal in 21 (27%). There was no significant difference in 2y CNS relapse rates between i-HDMTX and EOT in all pts: 5.2% vs 3.9%, adjusted hazard ratio (HR) 0.92 (95% CI 0.58-1.47), p=0.74, 2y difference -0.2% (-2.0-2.5) or landmark analysis: 2.8% vs 4.1%, HR: 0.93 (0.56-1.55), p=0.79, 2y difference: -0.3% (-1.8-2.2%) (Fig 1a/b). Exploratory analyses focusing on pts with isolated CNS relapse (n=57) demonstrated similar results (2y rates 3.6% vs 3.0%, p=0.99). On multivariable analysis (MVA) of risk factors for CNS relapse, renal/adrenal involvement was the only variable associated with increased CNS relapse risk (adjusted HR 1.74 (1.03-2.92), p=0.038). Notably, IT prophylaxis was not associated with reduction in CNS relapse. In 600 high CNS IPI (4-6) pts, there was no difference in CNS relapse risk between i-HD-MTX and EOT (3y rates 9.4% vs 8.6%, HR 0.92 (95% CI 0.52-1.62)). In a composite high risk group including CNS IPI 4-6 and/or any of the following: ≥3 extranodal sites, renal, adrenal, testicular or breast involvement (n=885) there was no difference in 3y CNS relapse rates between groups (i-HDMTX 7.6% vs EOT 7.4%, HR 0.94 (0.58-1.53)). Progression-free survival (PFS) and overall survival (OS) in the i-HDMTX and EOT groups were as follows: 3y PFS 70.7% vs 76.7% (p=0.098), 3y OS 79.9% vs 87.0% (p=0.0016). However, there were no PFS/OS differences between groups on landmark analysis (n=1259) (Fig 1c). On analysis of pts experiencing ≥1 R-CHOP delay of ≥7 days, use of i-HDMTX was the only factor on MVA associated with increased delays (p<0.0001). Discussion: We found no evidence that EOT delivery increases CNS relapse risk when compared to i-HDMTX in this large analysis of pts treated with 1L R-CHOP. Delays to R-CHOP cycles were increased with i-HDMTX. Findings in a high risk subgroup were unchanged and rates of CNS relapse in this HDMTX treated group were similar to published comparable high risk cohorts receiving infrequent CNS prophylaxis. Where HDMTX prophylaxis is used, delivery could be deferred until R-CHOP completion. Figure 1 Figure 1. Disclosures Wilson: Takeda: Other: Conference fees; Janssen: Other: Conference fees; Abbvie: Honoraria. Eyre: Janssen: Honoraria; Secura Bio: Consultancy, Honoraria; Gilead/KITE: Honoraria, Other: Travel support for conferences, Research Funding, Speakers Bureau; Roche: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria, Other: Travel to conferences; AstraZeneca: Honoraria, Research Funding; Loxo Oncology: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte: Consultancy; Beigene: Honoraria, Research Funding. Ahearne: Pfizer: Research Funding; Takeda: Honoraria; Roche: Honoraria. Schorb: Roche: Research Funding; Riemser Pharma GmbH: Honoraria, Research Funding; AbbVie: Research Funding. Ku: Antegene: Consultancy; Roche: Consultancy; Genor Biopharma: Consultancy. Narkhede: Genentech/Roche: Research Funding; Gilead: Research Funding; Genmab: Other: Medical writing support, Research Funding; TG Therapeautics: Research Funding. Lewis: AstraZeneca: Consultancy, Honoraria; Janssen: Honoraria, Patents & Royalties; Novartis: Patents & Royalties; Roche: Consultancy, Honoraria. Øvlisen: Abbvie: Other: Travel expenses. Santarsiere: Janssen: Honoraria. Shah: Abbvie, Janssen and Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees. Roulin: Janssen: Other: Travel and meetings. Manos: Bristol-Myers Squibb: Other: Travel and meetings. Hamad: Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Lopez-Garcia: Roche: Other: Speaker Honoraria, Travel and accommodation grants; Janssen: Other: Speaker Honoraria, Advisor, Travel and accommodation grants, Research Funding; Abbvie: Other: Speaker Honoraria, Advisor, Travel and accommodation grants; Celgene: Other: Speaker Honoraria; Fresenius: Other: Speaker Honoraria; Novonordisk: Other: Speaker Honoraria. El-Galaly: ROCHE Ltd: Ended employment in the past 24 months; Abbvie: Other: Speakers fee. Cheah: Beigene: Consultancy, Honoraria, Other: advisory; AbbVie: Research Funding; Celgene: Research Funding; AstraZeneca: Consultancy, Honoraria, Other: advisory; Loxo/Lilly: Consultancy, Honoraria, Other: advisory; TG Therapeutics: Consultancy, Honoraria, Other: advisory; Roche: Consultancy, Honoraria, Other: advisory and travel expenses, Research Funding; Janssen: Consultancy, Honoraria, Other: advisory; MSD: Consultancy, Honoraria, Other: advisory, Research Funding; Gilead: Consultancy, Honoraria, Other: advisory; Ascentage pharma: Consultancy, Honoraria, Other: advisory. Ferreri: Gilead, Novartis, Juno, PletixaPharm, Roche, Incyte: Membership on an entity's Board of Directors or advisory committees; BMS, Beigene, Pharmacyclics, Hutchison Medipharma, Amgen, Genmab, ADC Therapeutics, Gilead, Novartis, Pfizer: Research Funding. Fox: Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Other: speaker fees. Cwynarski: Gilead: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; Atara: Consultancy; Celgene: Consultancy; Takeda: Consultancy, Other: travel to scientific conferences, Speakers Bureau; Kite, a Gilead Company: Consultancy, Other: travel to scientific conferences, Speakers Bureau; Janssen: Consultancy, Other: travel to scientific conferences; Roche: Consultancy, Other: travel to scientific conferences, Speakers Bureau; BMS/Celgene: Other: travel to scientific conferences. McKay: Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Gilead: Honoraria, Other: Travel Support; KITE: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel Support; Janssen: Honoraria, Other: Travel Support; Beigene: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS/Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees.

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)0,003
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 seuil0,008

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
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 Opus0,020
Tête enseignante GPT0,301
Écart entre enseignants0,281 · 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

Citations2
Publié2021
Routes d'admission1
Résumé présentoui

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