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Enregistrement W3095898239 · doi:10.1182/blood-2020-136457

Rituximab Monotherapy Compared to Observation in Patients with Newly Diagnosed Asymptomatic Advanced Stage Follicular Lymphoma: A Retrospective Population-Based Analysis

2020· article· en· W3095898239 sur OpenAlexaffabout
Sarah E. Perry, Derrick G. Lee, Ciara L. Freeman, Diego Villa, Alina S. Gerrie, Pedro Farinha, Jeffrey W. Craig, Graham W. Slack, Joseph M. Connors, David W. Scott, Kerry J. Savage, Laurie H. Sehn

Notice bibliographique

RevueBlood · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphoma Diagnosis and Treatment
Établissements canadiensBC Cancer AgencyUniversity of British ColumbiaSpinal Cord Injury BC
Organismes subventionnairesnon disponible
Mots-clésMedicineRituximabAsymptomaticInternal medicineFollicular lymphomaPopulationCohortClinical endpointPediatricsLymphomaClinical trialSurgeryOncology

Résumé

récupéré en direct d'OpenAlex

Introduction Many pts with advanced (adv) stage follicular lymphoma (FL) present with low burden asymptomatic disease and are suitable for observation. Previous studies have shown that rituximab can delay the need for definitive therapy in these pts (Ardeshna et al, Lancet Oncol 2014), and that rituximab maintenance does not offer a long-term advantage (Kahl et al, JCO 2014). Based on early results of these trials, BC Cancer endorsed the use of rituximab monotherapy (R-mono), administered as 4 weekly doses for pts with newly diagnosed asymptomatic adv stage FL in British Columbia in 2011. The aim of this study was to assess the benefit of R-mono and to compare outcomes to pts undergoing observation (OBSE) prior to the introduction of R-mono (OBSE-1) or since the availability of R-mono (OBSE-2). Methods The BC Cancer Lymphoid Cancer and Provincial Pharmacy Databases were used to identify all pts >16 y of age with newly diagnosed, adv stage (extensive stage 2-4), asymptomatic (low tumour burden), grades 1-3a FL betw Jan 2011-Aug 2019, who were treated with R-mono. Results were compared with two OBSE cohorts with similar clinical inclusion criteria; a historical cohort (OBSE-1) diagnosed Jan 2004-Dec 2010 and a current-era cohort (OBSE-2) diagnosed Jan 2011-Aug 2019. Use of R-mono was at the discretion of the treating physician and reflected patient preference. The primary endpoint was time-to-new treatment (TTNT), measured from date of diagnosis to start of any therapy following R-mono or OBSE (systemic, radiotherapy or splenectomy); pts who did not need new treatment were censored at last follow-up. Clinical factors were compared using chi-square tests, ANOVA, and Kruskal-Wallis tests. Kaplan-Meier curves were used to generate survival estimates and differences between cohorts were examined using a log-rank test. Multivariable cox proportional hazard models were used to estimate hazard ratios for each cohort adjusting for relevant clinical factors, including the FLIPI group. Results In total, 843 pts were identified; R-mono (n=301), OBSE-1 (n=302), OBSE-2 (n=240). Median f/up was longer for OBSE-1 (12.1y, range 0.2-16.2), compared with R-mono (4.5y, 0.1-8.8) and OBSE-2 (4.3y, 0.4-9.3). Median time from diagnosis to R-mono was 0.21y (range, 0.05-1.06). Clinical characteristics were largely comparable betw the historical (OBSE-1) and current-era cohorts (R-mono + OBSE-2). However, in the current era, pts receiving R-mono were slightly younger and more likely to have stage 3/4 disease than OBSE-2 pts, indicating a possible selection bias in the use of R-mono (Table). Of the 301 pts receiving R-mono, 298 were evaluable for response, with 210 (70%) achieving CR(u), 70 (23%) PR, and 18 with non-response (2 stable disease, 16 progression, 6%). 10/18 R-mono non-responders developed transformed disease, with significantly poorer OS than responders (p<0.001) (Fig. 1). However, time-to-transformation was not significantly different betw the R-mono, OBSE-1 and OBSE-2 cohorts (p=0.40). Overall, TTNT was significantly improved in the R-mono cohort (p<0.001), with 3y and 5y TTNT estimates as follows: 3y TTNT R-mono 73% (95% CI 67-79), OBSE-1 52% (47-58), OBSE-2 57% (51-65); 5y TTNT R-mono 61% (54-68), OBSE-1 40% (35-46), OBSE-2 44% (37-52) (Fig. 2a). Median TTNT was 6.4y, 3.3y and 3.6y in R-mono, OBSE-1 and OBSE-2, respectively. Hemoglobin <120 (p=0.037), number of nodal sites >4 (p<0.0001), and high-risk FLIPI (p< 0.001) were associated with a shorter TTNT. On multivariate analysis controlling for relevant clinical factors and FLIPI, R-mono remained an independent predictor for TTNT (HR 0.53, 95% CI 0.41-0.69, p<0.001). With available f/up, OS was not statistically different (p=0.32). 5y OS was 86% (95% CI 81-91), 81% (76-85) and 80% (74-86) in R-mono, OBSE-1 and OBSE-2, respectively (Fig. 2b). Conclusions This is the largest study to date evaluating the benefit of R-mono in pts with newly diagnosed adv stage asymptomatic FL. The use of R-mono administered over 1 month delayed the median time to start of new treatment by approximately 3 years. Non-responders to R-mono had a high rate of transformation and poor OS, and may represent pts with high-risk biology. While the overall rate of transformation and OS were not altered, pts receiving R-mono were approximately 50% less likely to require definitive therapy at 5-years, enabling some pts to avoid treatment toxicity and providing time for novel therapies to emerge. Disclosures Perry: Seattle Genetics: Honoraria. Villa:Seattle Genetics: Consultancy, Honoraria; Purdue Pharma: Consultancy, Honoraria; Nano String: Consultancy, Honoraria; Kite/Gilead: Consultancy, Honoraria; AZ: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Sandoz Canada: Consultancy, Honoraria; Immunovaccine: Consultancy, Honoraria. Gerrie:Sandoz: Consultancy; Roche: Research Funding; Janssen: Consultancy, Honoraria, Research Funding; AbbVie: Consultancy, Honoraria, Research Funding; Astrazeneca: Consultancy, Research Funding. Scott:Abbvie: Consultancy; AstraZeneca: Consultancy; Celgene: Consultancy; Janssen: Consultancy, Research Funding; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoString, Research Funding; NIH: Consultancy, Other: Co-inventor on a patent related to the MCL35 assay filed at the National Institutes of Health, United States of America.; Roche/Genentech: Research Funding. Savage:Abbvie: Consultancy, Honoraria; Verastem: Honoraria; Takeda: Honoraria; Servier: Consultancy; Seattle Genetics: Consultancy, Honoraria, Research Funding; Merck: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Sehn:AbbVie: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; AstraZeneca: Consultancy, Honoraria; Genentech, Inc.: Consultancy, Honoraria, Research Funding; Acerta: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Kite: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria; Lundbeck: Consultancy, Honoraria; Merck: Consultancy, Honoraria; MorphoSys: Consultancy, Honoraria; F. Hoffmann-La Roche Ltd: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Teva: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Servier: Consultancy, Honoraria; Chugai: Consultancy, Honoraria; Verastem Oncology: Consultancy, Honoraria; TG therapeutics: Consultancy, Honoraria; Apobiologix: Consultancy, Honoraria.

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 enseignants0,005
Score d'incertitude au seuil0,011

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
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0010,001
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 Opus0,010
Tête enseignante GPT0,236
Écart entre enseignants0,225 · 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

Citations1
Publié2020
Routes d'admission2
Résumé présentoui

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