Comparison of outcomes among patients aged 80 and over and younger patients with diffuse large B-cell lymphoma: a population based study
Bibliographic record
Abstract
In this retrospective cohort study of 174 consecutive, newly diagnosed cases of diffuse large B-cell lymphoma (DLBCL), clinical and pathological variables, treatment, response and survival were compared for patients aged 80 and over (n = 40) to those under 80. Eastern Cooperative Oncology Group (ECOG) status and International Prognostic Index (IPI) were significantly worse among older patients. Standard treatment was given to only 32.5% of older versus 86.6% of younger patients, and 65% of the elderly did not receive standard therapy. At 12 months, overall and event-free survival were 51.3% (95% confidence interval [CI]: 35-66%) vs. 93% (CI: 88-97%) and 41.9% (CI: 25-58%) vs. 84.8% (CI: 77-90%), for older versus younger patients, respectively. Choice of therapy was significantly associated with survival in the elderly, and low albumin but not comorbidity score was associated with not receiving standard therapy. Patients with DLBCL aged 80 and over are distinct from all other age groups with regard to treatment tolerance. A minority can receive standard therapy, but for the majority, novel therapeutic options are needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".