Real-World Outcomes of Autologous and Allogeneic Hematopoietic Stem Cell Transplantation for Relapsed/Refractory Hodgkin Lymphoma in the Era of Novel Therapies: A Canadian Perspective
Bibliographic record
Abstract
Despite high cure rates with frontline therapy for Hodgkin lymphoma (HL), approximately 30% of patients will relapse or develop primary refractory disease (R/r). Autologous hematopoietic stem cell transplantation (autoHSCT) is the standard of care for R/r disease, and allogeneic HSCT (alloHSCT) is a curative option for patients in second relapse. Novel agents are being incorporated for the treatment of R/r HL, such that the optimal timing of transplantation is currently being challenged. In this rapidly evolving field, we sought to offer a Canadian perspective on the optreatment of R/r HL and demonstrate the role and effectiveness of both autoHSCT and alloHSCT for the treatment of R/r HL. This single-center retrospective study examined outcomes in 89 consecutive patients with R/r HL treated with autoHSCT between January 2007 and December 2019. A total of 17 patients underwent alloHSCT either as a tandem auto-allo approach or as salvage therapy. With a median follow-up of 5.0 years, the estimated 5-year PFS and OS for patients undergoing autoHSCT were 57.5% (95% confidence interval [CI], 45.2% to 68.0%) and 81.3% (95% CI, 70.0% to 88.8%), respectively. Corresponding values for patients who underwent alloHSCT were 76.5% (95% CI, 48.8% to 90.4%) and 82.4% (95% CI, 54.7% to 93.9%). Nonrelapse mortality at 0% at 100 days and 9.4% at 5 years post-autoHSCT and 0% and 5.9%, respectively, post-alloHSCT. The cumulative incidence of acute graft-versus-host disease (GVHD) at day +100 was 35.3% (95% CI, 17.7% to 62.3%), and that of chronic GVHD at 1 year was 23.5% (95% CI, 6.9% to 45.8%). Both autoHSCT and alloHSCT provide robust and prolonged disease control New agents should be used as a bridge to improve the curative potential of these definitive cellular therapies.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".