Ineffectiveness of high‐dose methotrexate for prevention of <scp>CNS</scp> relapse in diffuse large <scp>B</scp>‐cell lymphoma
Bibliographic record
Abstract
Central nervous system (CNS) relapse affects 5% of diffuse large B-cell lymphoma (DLBCL) patients and portends a poor prognosis. Prophylactic intravenous high-dose methotrexate (HD-MTX) is frequently employed to reduce this risk, but there is limited evidence supporting this practice. We conducted a multicenter retrospective study to determine the CNS relapse risk with HD-MTX in DLBCL patients aged 18-70 years treated in Alberta, Canada between 2012 and 2019. Provincial guidelines recommended HD-MTX for patients at high-risk of CNS relapse based upon CNS-IPI score, double-hit lymphoma, or testicular involvement. Among 906 patients with median follow-up 35.3 months (range 0.29-105.7), CNS relapse occurred in 1.9% with CNS-IPI 0-1, 4.9% with CNS-IPI 2-3, and 12.2% with CNS-IPI 4-6 (p < .001). HD-MTX was administered to 115/326 (35.3%) high-risk patients, of whom 96 (83.5%) had CNS-IPI score 4-6, 45 (39.1%) had double-hit lymphoma, and four (3.5%) had testicular lymphoma. The median number of HD-MTX doses was two (range 1-3). Central nervous system relapse risk was similar with versus without HD-MTX (11.2% vs. 12.2%, p = .82) and comparable to previous reports of high-risk patients who did not receive CNS prophylaxis (10-12%). In multivariate and propensity score analyses, HD-MTX demonstrated no association with CNS relapse, progression-free survival, or overall survival. This study did not demonstrate a benefit of prophylactic HD-MTX in this high-risk patient population. Further study is required to determine the optimal strategy to prevent CNS relapse in DLBCL.
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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 | 0.000 |
| 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 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".