Statin and cyclooxygenase‐2 inhibitors improve survival in newly diagnosed diffuse large B‐cell lymphoma: a large population‐based study of 4913 subjects
Bibliographic record
Abstract
Preclinical data suggests anti-lymphoma potential for statins, metformin and cyclooxygenase-2 (COX-2) inhibitors. We performed a retrospective population-based study of all adults aged ≥66 years diagnosed with diffuse large B-cell lymphoma (DLBCL) or transformed lymphoma treated with a rituximab containing regimen, between 2005 and 2015 in Ontario, Canada. Using administrative databases, we assessed the impact of medication exposures, prior to chemo-immunotherapy, on lymphoma survival. Cox regression analyses, controlling for sociodemographic factors and comorbidities, examined the relationship between medication exposure and survival. In total, 4913 patients were treated with curative intent (median age 75 years, 51% male) and 52·2% died at a median of 1 year from treatment initiation (67% due to DLBCL). In the year prior to commencing treatment, 45·7% received statins, 16·3% metformin, and 25·0% a COX-2 inhibitor. Adjusting for confounders, exposure to statin and COX-2 inhibitors prior to chemo-immunotherapy independently conferred a survival advantage: statin exposure for 30 days (hazard ratio [HR] 0·97, 95% confidence interval [CI] 0·96-0·98), 180 days (HR 0·84, 95% CI 0·80-0·89) and 365 days (HR 0·71, 95% CI 0·63-0·79) and COX-2 inhibitor exposure for 30 days (HR 0·95, 95% CI 0·95-0·98), 180 days (HR 0·76, 95% CI 0·66-0·86) and 365 days (HR 0·57, 95% CI 0·43-0·74). Metformin had no significant impact. This population-based study found a dose-related survival benefit of exposure to statins and COX-2 inhibitors prior to chemo-immunotherapy for newly diagnosed DLBCL.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; 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".