Intensity of survivin expression linked to features of aggressive relapsed/refractory diffuse large B-cell lymphoma
Bibliographic record
Abstract
SPiReL is a phase II clinical trial evaluating combination immunotherapy, pembrolizumab and cyclophosphamide, with maveropepimut-S, in survivin-expressing relapsed/refractory (R/R) Diffuse Large B Cell Lymphoma (DLBCL). We describe baseline tumor survivin expression and associations with clinico-pathological variables in 25 participants. The median number of survivin-expressing cells was 99%, and the intensity of survivin expression within tumors was heterogeneous by semi-quantitative immunohistochemistry assessment. Tumors with higher numbers of cells expressing 2+/3+ survivin were associated with characteristics of poor outcome, (Lactate dehydrogenase and cell-of-origin). Greater total baseline tumor area was associated with lower proportions of 1+ cells and greater proportions of 2+/3+ cells. High intensity survivin expression is associated with aggressive clinical features supporting a pathobiological role in R/R DLBCL. Future prognostic models incorporating survivin as a clinical biomarker require assessment of intensity, overall expression and should include potential threshold effects of survivin in DLBCL pathobiology.
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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) | 0.001 | 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".