Patients with high-risk DLBCL benefit from dose-dense immunochemotherapy combined with early systemic CNS prophylaxis
Bibliographic record
Abstract
Survival of patients with high-risk diffuse large B-cell lymphoma (DLBCL) is suboptimal, and the risk of central nervous system (CNS) progression is relatively high. We conducted a phase 2 trial in 139 patients aged 18 to 64 years who had primary DLBCL with an age-adjusted International Prognostic Index (aaIPI) score of 2 to 3 or site-specific risk factors for CNS recurrence. The goal was to assess whether a dose-dense immunochemotherapy with early systemic CNS prophylaxis improves the outcome and reduces the incidence of CNS events. Treatment consisted of 2 courses of high-dose methotrexate in combination with biweekly rituximab (R), cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP-14), followed by 4 courses of R-CHOP-14 with etoposide (R-CHOEP) and 1 course of high-dose cytarabine with R. In addition, liposomal cytarabine was administered intrathecally at courses 1, 3, and 5. Coprimary endpoints were failure-free survival and CNS progression rates. Thirty-six (26%) patients experienced treatment failure. Progression occurred in 23 (16%) patients, including three (2.2%) CNS events. At 5 years of median follow-up, failure-free survival, overall survival, and CNS progression rates were 74%, 83%, and 2.3%, respectively. Treatment reduced the risk of progression compared with our previous trial, in which systemic CNS prophylaxis was given after 6 courses of biweekly R-CHOEP (hazard ratio, 0.49; 95% CI, 0.31-0.77; P = .002) and overcame the adverse impact of an aaIPI score of 3 on survival. In addition, outcome of the patients with BCL2/MYC double-hit lymphomas was comparable to the patients without the rearrangements. The results are encouraging, with a low toxic death rate, low number of CNS events, and favorable survival rates. This trial was registered at www.clinicaltrials.gov as #NCT01325194.
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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) | 0.001 | 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 | 0.001 |
| 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".