Is Prior Rituximab Exposure Associated with a Difference in Outcomes in Relapsed Low-Grade Lymphomas Retreated with Rituximab in Comparison to Rituximab NaïVe Patients?
Notice bibliographique
Résumé
Abstract Introduction: Evidence from several randomized clinical trials demonstrates the survival benefit and superior magnitude of disease control of rituximab use in indolent lymphomas compared to chemotherapy alone in remission induction. However, there is a paucity of evidence regarding retreatment with rituximab in patients who have previously been exposed. Despite this, Canadian agencies fund the use of rituximab retreatment in patients who have previously received rituximab, sustained a response, and been treatment free for over a year. The purpose of this study was to describe the characteristics and outcomes of patients with relapsed indolent lymphomas re-treated with a rituximab-containing regimen at Princess Margaret Cancer Centre (PM). Methods: This was a retrospective chart review of patients treated at a Canadian tertiary care centre (PM) with relapsed low-grade lymphomas (follicular, mantle cell, marginal zone, and lymphoplasmacyticlymphomas) between January 2006 and November 2015. The start date of January 2006 is when provincial rituximab funding became available. Patients were identified from our lymphoma and pharmacy databases. Patients were included if they had sustained a treatment free period ³1 year between first- and second-line therapy, and received rituximab as part of their second-line therapy. They were divided into two groups: Group 1 included patients who received any rituximab exposure as part of their first line therapy; Group 2 included patients na•ve to rituximab, who were treated with a non-rituximab containing first-line regimen. Primary outcome was progression-free survival (PFS) from start of second-line treatment. Secondary outcomes were overall survival (OS), overall response rate (ORR), and number of patients achieving a complete response (CR) at the end of second-line treatment. Results: 687 patients were identified who received rituximab for indolent lymphoma treatment (any line) during this time period. Of the eligible relapsed subset, 41 transformed to aggressive lymphoma, and 39 progressed < 1yr post-first line therapy. 60 patients (55% female) met inclusion criteria, of which 21 (35%) had been retreated with rituximab during this time period. See Table 1 for patient characteristics. From start of second-line treatment, median follow-up was 43 months (range 4 to 132 months). Multivariate cox regression revealed a significant PFS difference between groups, with Group 1 having inferior PFS (2 year PFS 56% vs 77%, OR 2.38 95% CI 1.08-5.26, p=0.03, see Figure 1). Furthermore, patients who were older, had a higherCharlsoncomorbidity score, and those who did not receive maintenance rituximab had a lower PFS. More patients in Group 2 received oral chemotherapy as their first line treatment (such aschlorambuciland prednisone, reflecting an earlier treatment era, p=0.0003). There was no OS difference between groups (2 year OS 87% vs 79%, OR 1.73, 95%CI 0.64-4.64, p=0.28), although male gender and age were associated with lower OS. There was also no difference in groups in terms of ORR (75% vs 72%, p=0.8), or number achieving a CR at the end of second-line treatment (OR 0.38, 95% CI 0.11-1.37, p=0.14). Conclusions: Retreatment with rituximab was associated with an inferior PFS in patients with indolent lymphoma who sustained a one-year or greater response to first-line therapy with a rituximab-containing regimen, compared to rituximab-na•ve patients. This study is limited by small sample size, but our findings are consistent with other studies that evaluated rituximab retreatment in similar patient populations, and in diffuse large B-cell lymphoma. The PFS in patients retreated with rituximab was still superior to prior studies evaluating the use of second-line treatment with non-rituximab containing regimens in patients previously exposed to rituximab. There was no difference between groups in OS, ORR, or number achieving a CR at the end of treatment. Disclosures Crump: Celgene: Consultancy; Janssen-Ortho: Consultancy; Seattle Genetics: Consultancy; Roche: Consultancy. Kukreti:Lundbeck: Honoraria; Celgene: Honoraria; Amgen: Honoraria. Kuruvilla:Abbvie: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Merck: Honoraria; BMS: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Amgen: Honoraria; Roche Canada: Consultancy, Honoraria, Research Funding; Seattle Genetics: Consultancy, Honoraria; Lundbeck: Honoraria. Tiedemann:Celgene: Honoraria; Janssen: Honoraria. Chen:Takeda: Research Funding; Celgene: Honoraria, Research Funding; Janssen: Honoraria, Research Funding. Prica:Celgene: Honoraria; Janssen: 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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».