Upfront thiotepa, busulfan, cyclophosphamide, and autologous stem cell transplantation for primary CNS lymphoma: a single centre experience
Bibliographic record
Abstract
Treatment of primary central nervous system lymphoma (PCNSL) with high-dose methotrexate-based chemotherapy and whole-brain radiotherapy (WBRT) is associated with high rates of relapse and severe neurotoxicity. In an attempt to improve upon these poor results, we treated 21 patients with PCNSL aged 34-69 years (median 56) with high-dose thiotepa, busulfan, cyclophosphamide (TBC) and autologous stem cell transplant (ASCT) as part of front-line therapy, without WBRT. Patient characteristics included: Karnofsky performance status (KPS) <70% (n = 17), age >60 years (n = 8), deep brain involvement (n = 16). Treatment-induced neurotoxicity was not observed in any of these patients. Currently, 11 of 21 patients (52%) are alive and progression-free at a median follow-up of 60 (7-125) months post-ASCT. Causes of death included progressive PCNSL (n = 4), progressive systemic lymphoma (n = 1), early treatment-related mortality (TRM, n = 3) and two late deaths from pneumonia 3 years post-ASCT. All patients who died of TRM were over 60 years of age and had poor performance status. In conclusion, TBC/ASCT offers potential long-term progression-free survival without neurotoxicity when used as part of upfront therapy for PCNSL. However, efforts to reduce TRM through improved patient selection and possibly through decreased intensity of the TBC regimen for older or less fit patients are recommended.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".