The significance of peripheral blood minimal residual disease to predict early disease response in patients with B‐cell acute lymphoblastic leukemia
Bibliographic record
Abstract
INTRODUCTION: Minimal residual disease (MRD) assessment in the bone marrow (BM) postinduction therapy is now standard of care in patients with B-cell acute lymphoblastic leukemia (B-ALL). We examined the use of peripheral blood as a less invasive means of MRD assessment at days 8 and 15 of induction therapy and established the cutoff level that would allow the most accurate prediction of BM MRD postinduction therapy. METHODS: MRD analysis was performed using 5-color flow cytometry on BM and PB samples from 77 B-ALL patients. BM MRD at diagnosis and day 29 of induction therapy was analyzed using the following antibody combinations: CD45-PC5/CD19-PC7/CD20-PE/CD10-ECD/CD38-FITC/CD13 + CD33-PE/CD10-ECD/CD34-FITC. PB MRD at days 8 and 15 was determined using CD45-PC5/CD19-PC7/CD20-ECD/CD10-PE/CD34-FITC. RESULTS: Day 8 and day 15 PB MRD levels were significantly higher in patients who had persistent BM MRD at day 29. PB MRD <0.01% at day 8 and/or day 15 predicted negative day 29 BM MRD status with 100% sensitivity but poor specificity. ROC curve analysis showed that day 15 PB MRD level of 0.1% yielded the highest sensitivity (78%) and specificity (82%). CONCLUSIONS: PB MRD cutoff level of 0.1% at day 15 has the best predictive value in determining positive day 29 BM MRD.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".