Clinicoepidemiologic Profile and Outcome Predicted by Minimal Residual Disease in Children With Mixed-phenotype Acute Leukemia Treated on a Modified MCP-841 Protocol at a Tertiary Cancer Institute in India
Bibliographic record
Abstract
INTRODUCTION: Mixed-phenotype acute leukemia (MPAL) accounts for 1.2% to 5% of acute leukemia across age groups with intermediate prognosis. We evaluated clinicoepidemiologic profiles and outcomes of MPAL. METHODS: Records of children younger than 15 years of age with acute leukemia from January 2010 to December 2016 were reviewed on the basis of the MPAL WHO 2008 criteria. Treatment was uniform with a modified MCP-841 protocol. Descriptive analysis tools were used. Outcomes were measured by the Kaplan-Meier method on MedCalc, version 14.8.1. RESULTS: Among 3830 children with acute leukemia in the study period, 2892 received treatment from our center, of whom 24 (0.83%) had MPAL, median age 9 years, with a male:female ratio of 3:1, and median white blood cell of 13.4×10/L. Common immunophenotypes were B/myeloid-12 (50%), T/myeloid-9 (37.5%), and B/T-lymphoid-3 (12.5%). Some B/myeloid cases had abnormal cytogenetics. Seventeen patients were evaluable for outcome. Sixteen patients underwent postinduction bone marrow and 13 (81%) achieved morphologic remission. Thirteen patients underwent flow cytometry-based minimal residual disease evaluation; 9 (69%) were <0.01% (4 postinduction, 5 postconsolidation), and 67% of these had sustained remission till the last follow-up. None underwent bone marrow transplant. The projected 3-year event-free and overall survival rates were 40% and 48%, respectively (median follow-up: 22 mo). CONCLUSION: MPAL represented <1% of childhood acute leukemia. acute lymphoblastic leukemia-type chemotherapy that incorporated high-dose cytarabine was effective in achieving an minimal residual disease-negativity rate of 69% in evaluated patients, which was also predictive of better outcome.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".