Intensive Methotrexate and Cytarabine Followed by High-Dose Chemotherapy With Autologous Stem-Cell Rescue in Patients With Newly Diagnosed Primary CNS Lymphoma: An Intent-to-Treat Analysis
Bibliographic record
Abstract
PURPOSE: To assess the safety and efficacy of intensive methotrexate-based chemotherapy followed by high-dose chemotherapy (HDT) with autologous stem-cell rescue in patients with newly diagnosed primary CNS lymphoma (PCNSL). PATIENTS AND METHODS: Twenty-eight patients received induction chemotherapy using high-dose systemic methotrexate (3.5 g/m2) and cytarabine (3 g/m2 daily for 2 days). Fourteen patients with chemosensitive disease evident on neuroimaging then received high-dose therapy using carmustine, etoposide, cytarabine, and melphalan with autologous stem-cell rescue. RESULTS: The objective response rate to the induction-phase chemotherapy was 57%, and median overall survival is not yet assessable, with a median follow-up time of 28 months. The overall median event-free survival time is 5.6 months for all patients and 9.3 months for 14 patients who underwent transplantation. Six of these 14 patients (43%) remained disease-free at last follow-up. Treatment was well tolerated; there was one transplantation-related death. Prospective neuropsychologic evaluations have revealed no evidence of treatment-related neurotoxicity. CONCLUSION: This treatment approach is feasible in patients with newly diagnosed PCNSL without evidence of significant related neurotoxicity. Although the transplantation results are similar to those achieved in patients with aggressive or poor-prognosis systemic lymphoma, the low response rate to induction chemotherapy and the significant number of patients who experienced relapse soon after HDT suggest that more aggressive induction chemotherapy may be 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".