Double high-dose therapy with dose-intensive cyclophosphamide, etoposide, cisplatin (DICEP) followed by high-dose melphalan and autologous stem cell transplantation for relapsed/refractory Hodgkin lymphoma
Bibliographic record
Abstract
The purpose of the present study was to review retrospectively our results of double high-dose therapy with DICEP (dose-intensified cyclophosphamide 5.25 g/m(2), etoposide 1.05 g/m(2), and cisplatin 105 mg/m(2)) re-induction followed by high dose melphalan 200 mg/m(2) (HDM) and autologous stem cell transplantation (ASCT) for 73 consecutive patients with relapsed (n = 43) or refractory (n = 30) classical Hodgkin lymphoma (HL) treated between June 1995 and November 2009. DICEP chemotherapy resulted in successful stem cell mobilization in 71 patients (97%), with a median CD34 (+) cell collection of 15.6 × 10(6)/kg. With a median follow-up of 56 months post-DICEP, the 5-year progression free survival (PFS) and overall survival (OS) rates were 61% [95%CI = 49-72%] and 80% [95%CI = 69-89%], respectively. The 5-year PFS was 65% vs. 30% for DICEP responders vs. nonresponders (logrank p = 0.003) and 89% for International Prognostic Score (IPS) = 0-1, 56% for IPS = 2-3, and 24% for IPS = 4-7 (logrank p < 0.001). Response to DICEP and IPS at relapse were the only two factors that independently predicted PFS and OS in multivariate analyses. Treatment-related mortality was 1%. In conclusion, DICEP-HDM/ASCT is well tolerated double high-dose therapy associated with excellent stem cell mobilization and favorable PFS and OS outcomes for relapsed as well as primary refractory 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) | 0.000 | 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 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".