Lymphoma cell VEGFR2 expression detected by immunohistochemistry predicts poor overall survival in diffuse large B cell lymphoma treated with immunochemotherapy (R‐CHOP)
Bibliographic record
Abstract
Diffuse large B cell lymphoma (DLBCL) is clinically and biologically heterogeneous. In most cases of DLBCL, lymphoma cells co-express vascular endothelial growth factor (VEGF) and its receptors VEGFR1 and VEGFR2, suggesting autocrine in addition to angiogenic effects. We enumerated microvessel density and scored lymphoma cell expression of VEGF, VEGFR1, VEGFR2 and phosphorylated VEGFR2 in 162 de novo DLBCL patients treated with R-CHOP (rituximab, cyclophosphamide, vincristine, doxorubicin and prednisone)-like regimens. VEGFR2 expression correlated with shorter overall survival (OS) independent of International Prognostic Index (IPI) (P = 0.0028). Phosphorylated VEGFR2 (detected in 13% of cases) correlated with shorter progression-free survival (PFS, P = 0.044) and trended toward shorter OS on univariate analysis. VEGFR1 was not predictive of survival on univariate analysis, but it did correlate with better OS on multivariate analysis with VEGF, VEGFR2 and IPI (P = 0.036); in patients with weak VEGFR2, lack of VEGFR1 coexpression was significantly correlated with poor OS independent of IPI (P = 0.01). These results are concordant with our prior finding of an association of VEGFR1 with longer OS in DLBCL treated with chemotherapy alone. We postulate that VEGFR1 may oppose autocrine VEGFR2 signalling in DLBCL by competing for VEGF binding. In contrast to our prior results with chemotherapy alone, microvessel density was not prognostic of PFS or OS with R-CHOP-like therapy.
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 | 0.000 | 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".