C034 | THE ROLE OF STEM CELL TRANSPLANTATION IN PATIENTS WITH RELAPSED/REFRACTORY CLASSICAL HODGKIN LYMPHOMA TREATED WITH CHECKPOINT INHIBITORS: ITALIAN MULTICENTER EXPERIENCE
Bibliographic record
Abstract
Background. There is no agreement on the role of stem cell transplantation (SCT) in patients (pts) with relapsed/refractory (R/R) classical Hodgkin lymphoma (cHL) treated with checkpoint inhibitors (CPI). The aim of this study is to evaluate the real-life outcomes of R/R cHL pts treated with CPI, focusing on consolidation with autologous (autoSCT) and allogeneic SCT (alloSCT). Methods. Observational, retrospective, multicenter study enrolling consecutive R/R cHL pts aged 18-70 years, treated with CPI monotherapy in Italy (Jan 2016 - Jun 2023). Primary objective: proportion of pts who received alloSCT. Results. We enrolled 126 pts from 15 centers. Median age at CPI start was 36 years (18-70), 54% male, 95% received first-line ABVD, 51% had prior autoSCT. Pembrolizumab and nivolumab were used in 86 patients (68%) and 40 (32%), respectively. Overall response rate to CPI was 81%, with 49% complete responses (CRs). Ultimately, 41 pts (32%) received alloSCT (29 pts in this groups had already received autoSCT before CPI), 36 (29%) consolidated with autoSCT and 49 (39%) received no consolidation. Reasons for no SCT consolidation after CPI were age/comorbidity (n=19), center’s choice (n=9), alloSCT refusal or donor unavailability (n=9), PD (n=7), other (n=5). In pts consolidated with alloSCT or autoSCT, median PFS and OS were not reached at a median follow-up from CPI start of 27 months (range 7-90) for alloSCT and 47.5 months (range 4-99) for autoSCT. 48-months PFS probability were 80.6% and 81% for alloSCT and autoSCT recipients, respectively. Transplant-related mortality was 14.6% after alloSCT and 0% after autoSCT. In non-SCT consolidated pts median PFS was 27 months (median follow-up 21 months). 17 pts (35%) were still receiving CPI at last follow-up; the main reason for interruption was PD in 18/32 pts (56%). Among SCT-consolidated patients, CR status before SCT did not affect PFS (P=0.93 alloSCT, p=0.6 autoSCT). Instead, non-consolidated pts without CR had poorer PFS (not reached vs 11 months; p<0.001) -Figure1. Conclusions. This retrospective real-life analysis shows that outcomes after autoSCT and alloSCT consolidation are excellent regardless the achievement of CR with CPI, though alloSCT carries higher toxicity. Pts achieving CR with CPI have good outcomes even without SCT consolidation. Pts who don’t achieve/loss the CR and have already had autoSCT may benefit from alloSCT. Those who don’t achieve CR and don’t consolidate have the worst outcome.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".