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Enregistrement W3214525102 · doi:10.1182/blood-2021-145870

A Retrospective Cohort Study of Treatment Outcomes of Adult Patients with Relapsed or Refractory Low-Grade Follicular Lymphoma (ReCORD-FL)

2021· article· en· W3214525102 sur OpenAlexaff
Gilles Salles, Stephen J. Schuster, Luca Fischer, John Kuruvilla, Piers Patten, Bastian von Tresckow, Sonali M. Smith, Ana Isabel Jiminez Ubieto, Keith L. Davis, Saurabh Nagar, Jie Zhang, Vamsi Bollu, Etienne Jousseaume, Roberto Ramos, Yucai Wang, Brian K. Link

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensPrincess Margaret Cancer CentreUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésMedicineInternal medicineFollicular lymphomaRetrospective cohort studyCohortSalvage therapyPopulationOncologyProgression-free survivalRituximabChemotherapy regimenHazard ratioClinical trialSurgeryLymphomaChemotherapyConfidence interval

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Novel therapies for multiply relapsed follicular lymphoma (FL) are often evaluated in single arm trials with no comparative data on patients receiving usual care. This study (ReCORD-FL) therefore sought to construct a historical control cohort to augment current and future single arm trials in relapsed/refractory (r/r) FL. The analytic aims were to document patient characteristics, treatment patterns and clinical outcomes in a r/r FL population treated with standard therapies in routine practice. Methods: This was a retrospective cohort study via medical record review in 10 oncology centers across North America and Europe. Adult patients were required to meet several criteria defining multiply r/r FL (i.e., r/r after ≥2 lines of therapy, or relapsed during or within 6 months after completion of anti-CD20 antibody maintenance, or relapsed after autologous HSCT). Patients were also required to have ≥1 line of systemic therapy (i.e., first qualifying salvage therapy) after first meeting the r/r FL criteria; the date of first qualifying salvage therapy defined the study index date. At index, patients were required to have grade 1-3A FL, Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1, and no evidence of prior histological transformation. Outcomes were observed from the index date and from the start of each therapy line until the earliest of death, last follow-up, or December 31, 2020 (data cutoff). Endpoints were complete response (CR) rate, overall response rate (ORR), time to next treatment (TTNT), progression-free survival (PFS), and overall survival (OS). In a subgroup analysis, endpoints were examined by double refractoriness (r/r to both an anti-CD20 mAb and an alkylator) and POD24 status at index (best response of stable/progressive disease or relapsed within 24 months of front-line anti-CD20 mAb-containing therapy). Time to event outcomes were analyzed using the Kaplan-Meier method. Results: A total of 187 patients were identified for inclusion (Table 1). Most patients' (80.2%) first qualifying salvage (index) therapy occurred in third line (3L) (range: 3L - 6L). Anti-CD20 mAb plus chemotherapy (including alkylating and/or non-alkylating agents) was the most common index regimen (64.2% of patients); 8% received anti-CD20 mAb monotherapy, 11.2% received alkylator-based chemotherapy alone (i.e., an alkylator-containing regimen without anti-CD20 mAb), and 16.6% received other therapies (i.e., other regimens containing neither anti-CD20 mAb nor alkylator). Median follow-up from FL diagnosis was 9 years (range: 1 - 21 years), over which a median of 5 (range: 3 - 11) lines of therapy were observed per patient. CR rate and ORR to the index treatment were 39.0% and 70.6%, respectively (Table 2). Median (95% confidence interval [CI]) TTNT and PFS from index were 14.4 (11.8 - 18.6) and 14.6 (11.0 - 18.0) months, respectively; median OS from index was 128 months (10.6 years). Compared with non-double refractory, those with double refractory disease at index had numerically lower CR (34.3% vs. 45.1%) and ORR (67.6% vs. 74.4%) and substantially shorter median (95% CI) TTNT (11.8 [9.0 - 15.2] vs. 20.9 [14.4 - 26.2] months), PFS (10.7 [7.7 - 14.5] vs. 20.1 [14.4 - 25.4] months), and OS (78.1 [45.8 - 146.7] vs. [Not Reached] months). Outcomes were similarly less favorable for patients who were POD24 at index. All outcomes steadily worsened across successive treatment lines (Table 2, Figures 1a-c). ORR, for example, decreased from 69.5% in 3L (n = 187) to 45.8% in 5L (n = 96) and 41.2% in ≥8L (n = 51), while median (95% CI) PFS decreased from 11.8 (10.1 - 16.6) months in 3L to 9.4 (6.8 - 13.1) months in 5L and 4.4 (1.7 - 5.9) months in ≥8L; median (95% CI) OS had a similar trend: 133.7 (78.1 - 232.4), 46.3 (31.7 - 76.5), and 11.4 (5.9 - 21.2) months in 3L, 5L, and ≥8L, respectively. Conclusions: Our findings further demonstrate the poor outcomes and limited survival in FL patients with multiply r/r, double refractory, or POD24 disease. In assessing response rates and PFS, it is important to consider that response assessment criteria and schedules were more heterogenous in the routine practice settings of ReCORD-FL than in clinical trials. Based on comparability of results with another similar study (SCHOLAR-5), the robustness of data collected, and continued low likelihood of randomized trials in this area, ReCORD-FL provides valuable historical control data for new r/r FL therapies in development. Figure 1 Figure 1. Disclosures Salles: Beigene, BMS/Celgene, Debiopharm, Genentech/Roche, Genmab, Incyte, Ipsen, anssen, Novartis. Kite/Gilead, Loxo, Miltneiy, Rapt, TAKEDA, Velosbio, Allogene: Consultancy; Abbvie, Epizyme, Morphosys, Regeneron: Consultancy, Honoraria; Bayer: Honoraria. Schuster: Abbvie: Consultancy, Research Funding; Acerta Pharma/AstraZeneca: Consultancy; Alimera Sciences: Consultancy; BeiGene: Consultancy; Juno Theraputics: Consultancy, Research Funding; Loxo Oncology: Consultancy; Tessa Theraputics: Consultancy; Genentech/Roche: Consultancy, Research Funding; Merck: Research Funding; Pharmacyclics: Research Funding; Adaptive Biotechnologies: Research Funding; Incyte: Research Funding; TG Theraputics: Research Funding; Novartis: Consultancy, Honoraria, Patents & Royalties, Research Funding; Nordic Nanovector: Consultancy; Celgene: Consultancy, Honoraria, Research Funding. Kuruvilla: Seattle Genetics: Honoraria; Merck: Honoraria; Novartis: Honoraria; Gilead: Honoraria; BMS: Honoraria; Antengene: Honoraria; Amgen: Honoraria; AbbVie: Honoraria; Karyopharm: Honoraria, Other: Data and Safety Monitoring Board; Janssen: Honoraria, Research Funding; Incyte: Honoraria; Medison Ventures: Honoraria; Roche: Honoraria, Research Funding; AstraZeneca: Honoraria, Research Funding; Pfizer: Honoraria; TG Therapeutics: Honoraria. Patten: GILEAD SCIENCES: Honoraria, Research Funding; ROCHE: Research Funding; ASTRA ZENECA: Honoraria; NOVARTIS: Honoraria; JANSSEN: Honoraria; ABBVIE: Honoraria. von Tresckow: Amgen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Other, Research Funding; Pentixafarm: Consultancy, Honoraria; AbbVie: Other: congress and travel support; BMS-Celgene: Consultancy, Honoraria, Other: congress and travel support; AstraZeneca: Honoraria, Other: congress and travel support; Pfizer: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Kite-Gilead: Consultancy, Honoraria; MSD: Consultancy, Honoraria, Other: congress and travel support, Research Funding; Novartis: Consultancy, Honoraria, Other: congress and travel support, Research Funding. Smith: Alexion, AstraZeneca Rare Disease: Other: Study investigator; Celgene, Genetech, AbbVie: Consultancy. Davis: Novartis, Vertex Pharmaceuticals, Pfizer, Eisai, Eli Lilly, AstraZeneca: Research Funding. Nagar: Novartis, AstraZeneca, Eisai: Research Funding. Zhang: Novartis: Current Employment, Current equity holder in publicly-traded company. Bollu: Novartis: Current Employment, Current equity holder in publicly-traded company. Jousseaume: Novartis: Current Employment, Current equity holder in publicly-traded company. Ramos: Novartis: Current Employment, Current equity holder in publicly-traded company. Wang: Eli Lilly: Membership on an entity's Board of Directors or advisory committees; Novartis: Research Funding; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; MorphoSys: Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; InnoCare: Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding. Link: Genentech/Roche: Consultancy, Research Funding; MEI: Consultancy; Novartis, Jannsen: Research Funding.

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)0,002
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 enseignants0,006
Score d'incertitude au seuil0,011

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,008
Tête enseignante GPT0,240
Écart entre enseignants0,231 · 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
Publié2021
Routes d'admission1
Résumé présentoui

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