HIGHER MUTATIONAL BURDEN BUT DOES NOT IMPACT TREATMENT EFFICACY IN FOLLICULAR LYMPHOMA
Bibliographic record
Abstract
Introduction: Higher age is associated with shorter overall survival (OS) in patients (pts) with follicular lymphoma (FL), and age > 60 years is a component of the FL International Prognostic Index (FLIPI). However, it is unclear whether higher age directly impacts disease biology or treatment efficacy in FL. Methods: We analyzed 755 pts from the GLSG2000 trial who received R-CHOP for symptomatic, advanced stage FL. Pts who received consolidative autologous stem cell transplantation were censored at time of transplant. Progression of disease (POD) included progressive, relapsed or refractory disease ( 40-50 yrs, 261 (35%) >50-60 yrs, 208 (28%) >60-70 yrs, and 58 (8%) >70 yrs. 5-year OS rates were 97%, 91%, 90%, 85%, and 53% (Figure A); 5-year FFS rates were 82%, 62%, 63%, 55%, and 42% (Figure B), respectively. We used the cohort >50-60 yrs as a reference. Older pts had inferior OS (>60-70 yrs: HR 1.90, 95%-CI [1.15; 3.13], p = 0.012; >70 yrs: HR 7.31, 95%-CI [4.25; 12.59], p < 0.0001). Significantly inferior FFS was only seen in pts >70 yrs (HR 2.17, 95%-CI [1.45; 3.25], p = 0.00016). Competing risk analysis revealed that inferior FFS of pts >70 yrs did not result from increased POD (HR 1.20, 95%-CI [0.75; 1.91], p = 0.45), but from higher incidence of death without prior POD (HR 24.81, 95%-CI [5.38; 114.44], p < 0.0001; Figure C). Sequencing data of diagnostic FL biopsies from 258 pts showed that the number of gene mutations increased with age (RR 1.14/decade, 95%-CI [1.09; 1.20], p < 0.0001). This increase was however caused by silent mutations and mutations predicted to have low functional impact (each p < 0.0001), whereas disruptive mutations or mutations predicted to have high functional impact did not significantly increase with age (p = 0.27 and p = 0.16, respectively). Similarly, the number of mutated genes increased with age (RR 1.12/decade, 95%-CI [1.07; 1.18], p < 0.0001), but the fraction of significantly mutated genes (by MutSigCV) decreased from 89% (range 40-100%) in young adults (18-40 yrs) to 74% (range 0-100%, p = 0.01) in the oldest cohort (>70 yrs). No single gene mutation was found to be associated with older age after correction for multiple testing. Keywords: follicular lymphoma (FL); molecular genetics; R-CHOP.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".