<i>FCGR3A</i>/<i>2A</i> polymorphisms and diffuse large B‐cell lymphoma outcome treated with immunochemotherapy: a meta‐analysis on 1134 patients from two prospective cohorts
Bibliographic record
Abstract
Single nucleotide polymorphisms (SNPs) in FCγ-receptor genes FCGR3A (rs396991) and FCGR2A (rs1801274) influence the affinity of the Fc portion of anti-CD20 immunoglobulin G1 monoclonal antibody. Their roles in diffuse large B-cell lymphoma (DLBCL) treated with rituximab in combination with anthracycline-based chemotherapy remain controversial. To address this question, we genotyped FCGR2A and FCGR3A SNPs in two prospective DLBCL cohorts from Lymphoma Study Association trials (N = 554) and Iowa/Mayo Specialized Program Of Research Excellence (N = 580). Correlations with treatment response and hematological toxicity were assessed in Lymphoma Study Association. Correlation with event-free survival (EFS) and overall survival (OS) was performed in both cohorts, followed by a meta-analysis to increase power. Our study shows the absence of correlation between these SNPs and treatment response. Grades 3 and 4 febrile neutropenia during treatment was more frequently observed in FCGR3A VV (39%) than VF (29%) and FF (32%) carriers (p = 0.04). Our analysis for EFS and OS shows that FCGR3A was not associated with outcome. In a meta-analysis using an ordinal model, FCGR2A (per R allele) was associated with a better EFS (hazard ratio = 0.87; 95%CI, 0.76-0.99; p = 0.04) and OS (hazard ratio = 0.86; 95%CI, 0.73-1.00; p = 0.05) which was not altered after adjustment for the International Prognostic Index. Overall, our data demonstrate that patients with DLBCL with the low-affinity FCγRIIA RR had an unexpectedly better outcome than FCγRIIA H carriers. Whether rituximab efficacy is improved in FCγRIIA RR patients due a clearance reduction or other functions of FCγRIIA in DLBCL should be investigated (clinicaltrials.gov identifiers: NCT00135499, NTC00135499 NCT00140595, NCT00144807, NCT00144755, NCT01087424, and NCT00301821). Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".