Imatinib Compared with Interferon and Low-Dose Cytarabine for Newly Diagnosed Chronic-Phase Chronic Myeloid Leukemia
Bibliographic record
Abstract
BACKGROUND: Imatinib, a selective inhibitor of the BCR-ABL tyrosine kinase, produces high response rates in patients with chronic-phase chronic myeloid leukemia (CML) who have had no response to interferon alfa. We compared the efficacy of imatinib with that of interferon alfa combined with low-dose cytarabine in newly diagnosed chronic-phase CML. METHODS: We randomly assigned 1106 patients to receive imatinib (553 patients) or interferon alfa plus low-dose cytarabine (553 patients). Crossover to the alternative group was allowed if stringent criteria defining treatment failure or intolerance were met. Patients were evaluated for hematologic and cytogenetic responses, toxic effects, and rates of progression. RESULTS: After a median follow-up of 19 months, the estimated rate of a major cytogenetic response (0 to 35 percent of cells in metaphase positive for the Philadelphia chromosome) at 18 months was 87.1 percent (95 percent confidence interval, 84.1 to 90.0) in the imatinib group and 34.7 percent (95 percent confidence interval, 29.3 to 40.0) in the group given interferon alfa plus cytarabine (P<0.001). The estimated rates of complete cytogenetic response were 76.2 percent (95 percent confidence interval, 72.5 to 79.9) and 14.5 percent (95 percent confidence interval, 10.5 to 18.5), respectively (P<0.001). At 18 months, the estimated rate of freedom from progression to accelerated-phase or blast-crisis CML was 96.7 percent in the imatinib group and 91.5 percent in the combination-therapy group (P<0.001). Imatinib was better tolerated than combination therapy. CONCLUSIONS: In terms of hematologic and cytogenetic responses, tolerability, and the likelihood of progression to accelerated-phase or blast-crisis CML, imatinib was superior to interferon alfa plus low-dose cytarabine as first-line therapy in newly diagnosed chronic-phase CML.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.003 | 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".