Retreatment with R-CHOP–like therapy in patients with late relapse of diffuse large B-cell lymphoma
Bibliographic record
Abstract
ABSTRACT: Patients with diffuse large B-cell lymphoma (DLBCL) with late relapse (>2 years from diagnosis) may be treated with a second course of R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone)-like therapy particularly if comorbidities preclude more intensive options. Patients with de novo DLBCL initially treated with an R-CHOP-like regimen who later developed late relapse and were re-treated with curative-intent R-CHOP-like therapy were identified using the BC Cancer databases. Sixty-five patients were identified; at relapse, the median age was 77 years (range, 52-89), 81% had stage III to IV DLBCL, 52% had an Eastern Cooperative Oncology Group performance status of 2 to 4, and 78% had an International Prognostic Index score of 3 to 5. The median time from original diagnosis was 7.4 years (range, 2.5-15.9). Median number of cycles of R-CHOP-like therapy received at relapse was 5 (range, 1-6). Overall response rate was 72%, and 57% complete response. With a median follow-up of 31 months, 2-year time to progression (TTP) was 54%, 2-year progression-free survival was 46%, 2-year disease-specific survival was 64%, and 2-year overall survival was 54%. Patients relapsing >5 years from diagnosis had better TTP, with a 2-year TTP of 66% compared with 9% for patients relapsing between 2 and 5 years (hazard ratio, 0.30; 95% confidence interval, 0.14-0.64; P = .001). Many patients with late-relapsing DLBCL may be effectively treated with further R-CHOP-like therapy, avoiding more intensive and costly secondary therapies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".