GDP (Gemcitabine, Dexamethasone, Cisplatin) Salvage Therapy Results in Superior Progression Free Survival Compared to Mini-Beam Prior to Autologous Stem Cell Transplantation for Relapsed or Refractory Hodgkin’s Lymphoma.
Bibliographic record
Abstract
Abstract Objectives: To compare the response rates and early progression free survival (PFS) after high-dose therapy and autologous stem cell support (ASCT), following salvage chemotherapy with either GDP (gemcitabine 1000 mg/m2 IV d1 & 8, dexamethasone 40 mg PO d1-4, cisplatin 75 mg/m2 day 1) q 3 weeks or mini-BEAM (MB: BCNU, etoposide, cytarabine, melphalan) q3-4 weeks in patients (pts) with relapsed or refractory Hodgkin’s lymphoma. Material and methods: Sixty-eight consecutive pts referred for salvage therapy (34 MB, 34 GDP) were retrospectively compared. All had received prior ABVD chemotherapy except for 3 GDP pts (one received MOPP, one Stanford V, one MOPP/ABV). MB administration required admission to hospital wherease GDP was given in the outpatient setting. Pts typically received 2 cycles of salvage therapy; responding patients had PBSCs mobilized with cyclophosphamide 2 g/m2 day 1, etoposide 200 mg/m2 days 1–3 and filgrastim 10μg/kg. PBSC collection commenced when the blood CD34 cell count was >5–10/μL. Target PBSC number was ≥5 x 106 CD34+ cells/kg and a minimum threshold of 2 x 106 CD34+ cells/kg was required to proceed to high dose therapy (etoposide 60 mg/kg day −4, melphalan160 mg/m2 day −3; PBSC infusion day 0). Pts with bulk disease at relapse > 5cm received involved field radiation (RT) post-ASCT (7/30 GDP pts and 7/28 MB pts). Results: The MB and GDP groups were similar in stage at relapse (limited stage 38% in each group) and disease status (primary refractory: MB 47%, GDP 53%). Ps receiving GDP were older (mean age 43y, range 19–64, vs. MB: mean 34, range 19–60), while more MB pts had previous RT (48% vs. 24%, p=0.03). There were slightly more male pts that received MB versus GDP (M:F MB 24:10, GDP 17:17). The response rate to GDP prior to ASCT (CR, CRu or PR) was 62% (95% CI: 45%–78%) vs. 68% for MB (95% CI: 52%–83%, p=0.61). Nine and 5 pts had stable disease, and 4 and 6 pts progressed on GDP and MB, respectively. 30/34 pts receiving GDP and 28/34 MB pts proceeded to PBSC mobilization. The proportion of pts who had PBSC collections > 2 x 106 CD34+ cells/kg was 97% after GDP vs. 82% after MB (p=0.07), and the proportion collected in a single apheresis procedure was 90% vs 57% (p=0.0043). The proportion of pts who reached the PBSC target of ≥ 5 x 106 CD34+ cells/kg was 97% after GDP and 57% after MB (p=0.0003), and was obtained in a single apheresis more often after GDP (73% vs 36%, p=0.004). Bone marrow harvest was needed in 1 GDP pt (3%) and 5 MB pts (18%, p=0.07). After a median follow up of 1.8 yrs post ASCT for all pts (GDP: 1.2 yrs, range 0.3 – 2.8 yrs; MB: 3 years, range 1.2 – 4.6 yrs), PFS is significantly better for pts receiving GDP compared to MB (74% vs. 35% at 1.5 years, p=0.005). Overall survival at 1.5 yrs is 91% for GDP pts and 82% for MB (p=0.23). Conclusions: Although this is a retrospective analysis, response to and early PFS post-ASCT after GDP compares favourably to MB salvage chemotherapy, our previous standard. Pts receiving GDP have higher PBSC yields, are more likely to have an optimal collection after a single leukapheresis and less likely to experience mobilization failure than pts receiving MB salvage. Based on these data, a phase III trial comparing GDP to MB or dexa-BEAM is warranted.
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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 | 0.000 |
| 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) | 0.002 | 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".