All-trans retinoic acid in acute promyelocytic leukemia: long-term outcome and prognostic factor analysis from the North American Intergroup protocol
Bibliographic record
Abstract
We previously reported a benefit for all-trans retinoic acid (ATRA) in both induction and maintenance therapy in patients with acute promyelocytic leukemia (APL). To determine the durability of this benefit and identify important prognostic factors, long-term follow-up of the North American Intergroup APL trial is reported. A total of 350 patients with newly diagnosed APL were randomized to either daunorubicin and cytarabine (DA) or ATRA for induction and then either ATRA maintenance or observation following consolidation chemotherapy. The complete remission (CR) rates were not significantly different between the ATRA and DA groups (70% and 73%, respectively). However, the 5-year disease-free survival (DFS) and overall survival (OS) were longer with ATRA than with DA for induction (69% vs 29% and 69% vs 45%, respectively). Based on both induction and maintenance randomizations, the 5-year DFS was 16% for patients randomized to DA and observation, 47% for DA and ATRA, 55% for ATRA and observation, and 74% for ATRA and ATRA. There was no advantage of either induction regimen among any subgroups when CR alone was considered. However, female sex, classical M3 morphology (vs the microgranular variant [M3v]), and treatment-white blood cell count (WBC) interaction (ATRA/WBC below 2 x 10(9)/L [2000/microL] best, DA/WBC above 2 x 10(9)/L worst) were each significantly associated with improved DFS (P <.05). Treatment with ATRA, WBC below 2 x 10(9)/L, and absence of bleeding disorder were each significantly associated with improved OS. Age more than 15 years, female sex, and treatment-morphology interaction (DA/M3v worst, ATRA best regardless of morphology) were each significantly associated with improved DFS based on maintenance randomization. The improvement in outcome with ATRA in APL was maintained with long-term follow-up.
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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 | 0.014 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".