Rituximab Resistant Follicular Lymphoma: Predictors of Rituximab Resistance, Incidence of Transformation and Prognosis
Notice bibliographique
Résumé
Abstract Abstract 4981 Follicular lymphoma (FL) is an indolent lymphoma characterized by slow growth, initial response to treatment with inevitable relapse. Recent trials have demonstrated improved progression free survival (PFS) with rituximab-containing induction, maintenance rituximab (MR) or both. However, a small subset of patients (pts) will show disease progression during the induction or maintenance phase. We evaluated rituximab resistance (RR) including incidence, predictors, rate of transformation and prognosis for pts demonstrating RR. We defined RR as disease progression during induction, maintenance or within 6 months of last dose of rituximab. We retrospectively identified pts who received rituximab for symptomatic FL from July 2006 to April 2010 at 2 regional cancer centres. Those with a diagnosis of FL grades 1, 2 or 3a with first exposure to rituximab (induction, maintenance or both) were included. Exclusion criteria included FL grade 3b and previous rituximab exposure. Progression was ascertained from clinical notes or radiological investigation as per IWG Criteria (1999). Transformation was defined by confirmatory biopsy and clinical suspicion of transformation was also recorded (nodal growth, rapid rise in LDH or new B symptoms). PFS and overall survival (OS) were measured from initiation of rituximab induction. Log-rank statistics were used to identify univariate predictors for RR and Cox regression for multivariate analysis with outcome as time to early progression (RR). Of the pts screened, 132 met inclusion criteria (112 pts receiving primary therapy, 20 for ≥ 2nd line therapy); 22 pts (16.7%) demonstrated RR. Incidence of RR was similar for pts receiving primary therapy (17.0%). Pt characteristics for rituximab sensitive (RS) and RR groups are shown in Table 1. From induction, median follow-up was 33 months (range 9 to 61 months). In univariate analysis, high risk FLIPI score at induction was predictive of RR (p = 0.002). Partial response to induction (p = 0.082) trended to significance. Other factors not predictive of RR included: age, gender, high grade histology (grade 3a), previous chemotherapy received, time from diagnosis to induction therapy and anthracycline-based induction. A Cox regression model was constructed with FLIPI score and anthracycline-based induction as covariates. FLIPI score was independently and significantly predictive of RR (HR 2.43; 95% CI, 1.4 to 4.1; p = 0.001). Of the 22 pts who were RR, 18 (81.8%) required subsequent chemotherapy with only 9 achieving at least a partial response. Ten pts (45.5%) required more than 1 line of chemotherapy post-progression with a median time to next line of therapy of 9 months (95% CI, 2.9 to 15.1; see figure). Among the RR pts, 5 (22.7%) showed evidence of transformation on biopsy at initial resistance and an additional 3 (13.6%) were clinically suspected. Within 12 months of resistance, a further 3 pts in the RR group demonstrated biopsy-proven transformation. Overall, 10 pts (45.5%) transformed (biopsy-proven) with no transformation in the RS group. During follow-up, 9 deaths occurred, all in those with RR, 5 following biopsy-proven transformation. The median PFS and OS in the RR group were 17 months and 47 months, respectively. Table 1 Characteristics RS (n = 110) RR (n = 22) Age (MEAN) 58.9 58.9 Gender (females) 43.6% 40.9% High histological grade (3a) 8.4% 9.1% Previous treatment (yes) 15.5% 13.6% Alkylator 11.8% 13.6% Number of lines of previous treatment >1 4.5% 4.5% Mean time from diagnosis to induction (months) 30.3 28.1 Induction chemo R-CVP based 78.2% 86.4% R-CHOP based 18.2% 9.1% Other 3.6% 4.5% Response to induction PR 77.3% 72.7% CRu 12.7% 0% CR 10.0% 4.5% SD/PD 0% 22.7% FLIPI score at induction Low (0, 1, 2) 57.8% 18.2% Intermediate (3) 26.6% 40.9% High (4 or 5) 15.6% 40.9% Stage 3 or 4 88.2% 100% High tumor burden at diagnosis (GELF criteria) 43.6% 40.9% We demonstrated that the incidence of rituximab resistance in FL on first exposure to rituximab in our population was 16.7%. FLIPI score was predictive for RR and was independent of anthracycline-based induction regimens. Pts with RR had a high rate of histologic transformation (36.3% within 12 months post RR) and a shorter PFS/OS with a poor response to next therapy. Biopsies to confirm transformation should be performed in all pts demonstrating RR, and new therapies are needed for this group of pts. Disclosures: Crump: Ortho Johnson & Johnson: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; Millennium Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees. Kukreti:Celgene: Honoraria; Ortho Biotech: Honoraria; Roche: 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 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».