FC-Gamma Receptor (FCGR) 2A and 3A Polymorphisms Do Not Influence the Outcome of Relapsed or Refractory CLL Patients Treated with Rituximab, Fludarabine, and Cyclophosphamide (R-FC) or Fludarabine, and Cyclophosphamide (FC) Alone.
Bibliographic record
Abstract
Abstract Abstract 2338 Poster Board II-315 The addition of rituximab to fludarabine/cyclophosphamide chemotherapy for the treatment of both previously untreated and relapsed/refractory patients with CLL has yielded a substantial increase in PFS as demonstrated in phase III trials (Hallek et al. ASH 2008, Robak et al. ASH 2008. Polymorphisms of the FC-g-R IIIa gene (SNP 158) results in a higher (VV genotype) or lower (FV and FF genotype) affinity for IgG1 monoclonal antibodies and subsequently modulate ADCC activity. In patients with follicular NHL treated with rituximab as monotherapy it has been shown that patients displaying the higher affinity FCGR3A variant had higher response rates compared to patients displaying the lower affinity variant (Cartron et al. Blood 2002; Weng et al. JCO 2003). Furthermore, the high affinity polymorphism of the FCGR2A gene (SNP 131) (HH genotype), has also demonstrated higher response rates compared to the lower affinity variant (RH and RR genotype) in this context (Weng et al. JCO 2003). The objective of this study was to evaluate the prognostic significance of FCGR polymorphisms in patients treated with FC vs R-FC within the REACH trial. REACH was an open-label, multicenter, randomized, phase III study to evaluate the efficacy and tolerability of R-FC versus FC in relapsed or refractory patients with CD20 positive CLL (N=552). The primary endpoint of the study was progression free survival. Results from allele specific PCR for FCGR2A (SNP 131, rs1801274) and FCGR3A (SNP 158, rs396991) genes were available from n= 419 of 546 unselected patients (FC: n=209 and R-FC: n=210). In the FC arm n=29 (14%) displayed the FCGR3A VV genotype, n=96 (46%) FV genotype, and n=84 (40%) FF genotype. ). In the R-FC arm n=20 (10%) displayed the FCGR3A VV genotype, n=106 (50%) FV genotype, and n=84 (40%) FF genotype. The incidences of FCGR2A for HH, RH, RR genotypes were 27%, 49%, 24%, respectively in the FC arm and 26%, 55%, 19%, respectively in the R-FC arm. Overall, the study demonstrated prolonged PFS for R-FC vs FC treatment (HR=0.65 (0.51,0.82); p=0.00022). With respect to PFS, FCGR3A and FCGR2A polymorphisms did not demonstrate prognostic significance in the FC arm (p=0.42 and p=0.64, respectively) or R-FC arm (p=0.41 and p=0.88, respectively). Subgroup analysis revealed that those patients with lower affinity genotypes (FCGR3A: FV/FF; FCGR2A: RH/RR) benefited significantly from the addition of rituximab (HR=0.68 (0.51,0.9); p=0.0063 and HR=0.68 (0.51,0.93); p=0.014, respectively). Similar levels of benefits were suggested for those patients with higher affinity genotype (HR=0.86 (0.4,1.84); p=0.7 and HR=0.7 (0.41,1.18); p=0.18, respectively) but not statistically significant, potentially due to the lower number of patients in the high affinity groups. Multivariate analysis including FCGR genotypes, treatment arm (FC vs R-FC), Binet stage (c vs a/b), age, del(17p), IgVH mutational status revealed age (HR=1.02 (1.01,1.04); p=0.0042), binet stage HR=1.81 (1.37,2.39); p=0.000027), del(17p) (HR=2.49 (1.66,3.74); p=0.000011), treatment arm (HR=0.71 (0.54,0.92); p=0.011), IgVH (HR=2.09 (1.55-2.81); p=0.0000014), as independent prognostic factors for PFS. In summary these data demonstrate that FCGR2A and FCGR3A polymorphisms do not significantly influence the outcome of relapsed or refractory CLL patients treated with FC with or without rituximab. Disclosures: Dornan: Genentech, Inc.: Employment, Equity Ownership. Off Label Use: Rituximab together with FC chemotherapy in relapsed/refractory CLL. Spleiss:Roche: Employment. Yeh:Genentech, Inc.: Employment, Equity Ownership. Duchateau-Nguyen:Roche: Employment. Robak:Celgene: Consultancy; Roche: Honoraria, Research Funding; Genmab: Research Funding; Cambridge Antibody Technology: Research Funding; GlaxoSmithKline: Honoraria. Solal-Celigny:Roche: Honoraria, Research Funding. Warzocha:BMS: Consultancy, Honoraria; Celgene: Consultancy; Roche: Honoraria; Pfizer: Honoraria; Amgen: Honoraria. Loscertales:Roche: Consultancy. Catalano:Roche: Honoraria, Research Funding, Travel grants. Larratt:Roche: Honoraria; Novartis: Honoraria. Bence-Bruckler:Roche: Consultancy. Geisler:Bayer Schering: Consultancy, Research Funding, Speakers Bureau; Santaris Pharma: Consultancy; Celgene: Consultancy; Fresenius: Consultancy. Montillo:Bayer Schering: Honoraria, Research Funding, Speakers Bureau. Wenger:Roche: Employment. Weisser:Roche: Employment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".