Treatment strategies, outcomes and prognostic factors in 291 patients with secondary CNS involvement by diffuse large B-cell lymphoma
Bibliographic record
Abstract
PURPOSE: Secondary CNS involvement (SCNS) is a profoundly adverse complication of diffuse large B-cell lymphoma. Evidence from older series indicated a median overall survival (OS) < 6 months; however, data from the immunochemotherapy era are limited. METHODS: Patients diagnosed with SCNS during or after first-line immunochemotherapy were identified from databases and/or regional/national registries from three continents. Clinical information was retrospectively collected from medical records. RESULTS: In total, 291 patients with SCNS were included. SCNS occurred as part of first relapse in 254 (87%) patients and 113 (39%) had concurrent systemic relapse. With a median post-SCNS follow-up of 48 months, the median post-SCNS OS was 3.9 months and 2-year OS rate was 20% (95% CI: 15-25). In multivariable analysis of 173 patients treated with curative/intensive therapy (such as high-dose methotrexate [HDMTX] or platinum-containing regimens), age ≤60 years, performance status 0-1, absence of combined leptomeningeal and parenchymal involvement, and SCNS occurring after completion of first-line therapy were associated with superior outcomes. Patients ≤60 years with performance status 0-1 and treated with HDMTX-based regimens for isolated parenchymal SCNS had a 2-year OS of 62% (95% CI: 36-80). In patients with isolated SCNS, the addition of rituximab to HDMTX-based regimens was associated with improved OS. Amongst patients with isolated SCNS in CR following intensive treatment, high-dose chemotherapy and autologous stem cell transplantation did not improve OS (P = 0.9). CONCLUSIONS: In this large international cohort of patients treated with first-line immunochemotherapy, outcomes following SCNS remain poor. However, a moderate proportion of patients with isolated SCNS who received intensive therapies achieved durable remissions.
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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 | 0.001 |
| 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) | 0.001 | 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".