The Stromal Cell Marker SPARC Predicts for Survival in Patients With Diffuse Large B-Cell Lymphoma Treated With Rituximab
Why this work is in the frame
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Bibliographic record
Abstract
The cellular composition of the tumor microenvironment may affect survival in diffuse large B-cell lymphoma (DLBCL). We performed immunostains for 2 stromal cell markers, CD68 and SPARC (secreted protein, acidic and rich in cysteine), in 262 patients with DLBCL treated with rituximab and cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) or CHOP-like therapies. Patients with any SPARC+ cells in the microenvironment had a significantly longer overall survival, and patients with high SPARC positivity in the microenvironment also had a significantly longer event-free survival. Survival differences were mainly due to the prognostic effect of SPARC+ cells in activated B-cell (ABC)-type DLBCL, with no effect found in the germinal center B-cell-type DLBCL. Of clinical features examined, only the number of extranodal sites was significantly associated with SPARC expression. Multivariate analysis revealed that SPARC expression predicted patient survival independent of the International Prognostic Index or tumor cell of origin. SPARC expression in the microenvironment of DLBCL can be used for prognostic purposes, determining a subgroup of patients with ABC DLBCL who have significantly longer survival. More aggressive chemotherapy protocols should be considered for patients with ABC DLBCL without SPARC+ stromal cells. CD68 expression by cells in the microenvironment did not predict survival.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it