Response‐adapted therapy for aggressive non‐Hodgkin's lymphomas based on early [18F] FDG‐PET scanning: ECOG‐ACRIN Cancer Research Group study (E3404)
Bibliographic record
Abstract
A persistently positive positron emission tomography (PET) scan during therapy for diffuse large B-cell lymphoma (DLBCL) is predictive of treatment failure. A response-adapted strategy consisting of an early treatment change to four cycles of R-ICE (rituximab, ifosfamide, carboplatin, etoposide) was studied in the Eastern Cooperative Oncology Group E3404 trial. Previously untreated patients with DLBCL stage III, IV, or bulky II, were eligible. PET scan was performed after three cycles of R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone) and scored as positive or negative by central review during the fourth cycle. PET-positive patients received four cycles of R-ICE, PET-negative patients received two more cycles of R-CHOP. A ≥ 45% 2-year progression-free survival (PFS) for mid-treatment PET-positive patients was viewed as promising. Of 74 patients, 16% were PET positive, 79% negative. The PET positivity rate was much lower than the 33% expected. Two-year PFS was 70%; 42% [90% confidence interval (CI), 19-63%] for PET-positives and 76% (90% CI 65-84%) for PET-negatives. Three-year overall survival (OS) was 69% (90% CI 43-85%) and 93% (90% CI 86-97%) for PET-positive and -negative cases, respectively. The 2-year PFS for mid-treatment PET-positive patients intensified to R-ICE was 42%, with a wide confidence interval due to the low proportion of positive mid-treatment PET scans. Treatment modification based on early PET scanning should remain confined to clinical trials.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".