Gemcitabine, dexamethasone, and cisplatin (GDP) is an effective and well-tolerated salvage therapy for relapsed/refractory diffuse large B-cell lymphoma and Hodgkin lymphoma
Bibliographic record
Abstract
The optimal choice of salvage therapy for patients with relapsed/refractory diffuse large B-cell lymphoma (DLBCL) or Hodgkin lymphoma (HL) remains unknown. Based on promising results of phase II trials, the preferred salvage regimen in British Columbia since 2002 has been the out-patient regimen, gemcitabine, dexamethasone, and cisplatin (GDP). We conducted a retrospective analysis including all patients with relapsed/refractory DLBCL or HL who received GDP as salvage therapy between September 2002 and June 2010. We identified 235 patients: 152 DLBCL, 83 HL. Overall response rates were 49% and 71% for patients with DLBCL and HL, respectively. Within the transplant-eligible population, 52% of patients with DLBCL and 96% of patients with HL proceeded to stem cell transplantation. The 2-year progression-free survival and overall survival were 21% and 28% in the DLBCL cohort, and 58% and 85% in the HL group. GDP is an effective and well-tolerated out-patient salvage regimen for relapsed/refractory DLBCL and HL.
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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 | 0.000 | 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".