Primary gastric diffuse large B‐cell lymphoma: A multicentre retrospective study
Bibliographic record
Abstract
Primary gastric diffuse large B-cell lymphoma (PG-DLBCL) accounts for the majority of extra-nodal DLBCL. Even so, literature is lacking on early, localised presentations. We studied a cohort of patients with stage I disease, diagnosed between 2006 and 2018, from six centres between Australia, Canada and Denmark. Our goal was to characterise outcomes, review treatment and investigate the role of interim positron emission tomography (iPET). Thirty-seven eligible patients were identified. The median duration of follow-up was 42.2 months. All received chemoimmunotherapy with 91.9% (n = 34) given rituximab, cyclophosphamide, doxorubicin, vincristine and prednisolone (R-CHOP). 35.1% (n = 13) underwent consolidative radiotherapy. Eighteen patients were H. pylori positive and 11 had the documentation of H. pylori eradication therapy. The 4-year progression-free survival and overall survival of R-CHOP was 88% (95% CI: 71-95) and 91% (95% CI: 75-97) respectively. All patients who achieved a partial metabolic response or complete metabolic response on iPET went on to achieve complete response at the end of treatment. R-CHOP-based therapy with iPET assessment appears to offer favourable outcomes, with radiotherapy and H. pylori eradication therapy implemented on a case-by-case basis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".