Risk Stratification in Acute Promyelocytic Leukemia Based on Elevated White Cell Count and Reduced Platelet Count Does Not Identify Subsequent Relapses: A Retrospective Review of 60 Patients.
Bibliographic record
Abstract
Abstract Acute promyelocytic leukemia (APL) has become one of the more readily treatable subtypes of acute myeloid leukemia on the basis of its particular sensitivity to anthracyclines and the introduction of the differentiating agent all-trans retinoic acid (ATRA). Unfortunately some patients will ultimately relapse after achievement of complete remission. A PETHEMA and GIMEMA (PETH/GIM) cooperative group joint study sought to identify risk factors associated with relapse and developed a predictive model based on white cell count (WCC) and platelet count (Plt) at diagnosis. This model for relapse free survival was capable of segregating patients into low risk (WCC < 10 x 109/L / Plt > 40 x 109/L), intermediate risk (WCC < 10 x 109/L / Plt < 40 x 109/L), and high risk (WCC > 10 x 109/L). A subsequent follow up study demonstrated improved outcomes for intermediate and high risk group patients treated with an anthracycline and ATRA based risk adapted strategy. We reviewed 60 cases of adult de novo APL treated at Vancouver General Hospital from August 1995 to December 2003. Thirty five females (58%) and 25 males (42%) were treated with a standard induction and consolidation protocol consisting of 3 cycles of Daunorubicin (60 mg/m2 OD for 3 days), Cytosine arabinoside (100 mg/m2 BID for 7 days), and ATRA (45 mg/m2/day until complete remission or a maximum of 60 days). In 2000 maintenance therapy was introduced and ATRA and/or varying doses of Methotrexate and 6-Mercaptopurine were then instituted for up to 2 years duration. At the completion of induction chemotherapy complete morphological and cytogenetic remission was achieved in 55/60 patients (92%) with 4 induction failures and only 1 death during induction treatment. Subsequently during and after consolidation and maintenance therapy at a median follow up of 34 months there were a total of 10 episodes of relapse (18%) in these 55 patients. When the 55 patients in complete remission were stratified at diagnosis by the PETH/GIM risk group there were 18 low risk patients (33%), 26 intermediate risk patients (47%), and 11 high risk patients (20%). The number of relapses was 6 in the low risk group (33%), 4 in the intermediate risk group (15%) and no relapses were identified in the high risk group. In our experience the predictive model for relapse free survival developed by the PETH/GIM cooperative group does not identify those at most likelihood for subsequent relapse after achieving an initial complete remission. The greatest number of relapse was seen in the low risk group with no relapses in the high risk group. These variations may be explained in part by the different chemotherapy treatment protocols with variable maintenance therapy. Future investigation will focus on the prognostic role of immunophenotype, additional cytogenetic abnormalities and molecular isoforms in determining outcome in APL.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".