Dasatinib for a Child with Philadelphia Chromosome–Positive Acute Lymphoblastic Leukemia and Persistently Elevated Minimal Residual Disease during Imatinib Therapy
Bibliographic record
Abstract
Imatinib has improved outcomes in patients with Philadelphia chromosome-positive (Ph+) acute lymphoblastic leukemia (all). Minimal residual disease (mrd) is a useful tool for predicting leukemia relapse. However, there is no consensus on how to treat children with elevation of BCR-ABL transcripts but no evidence of hematologic relapse during chemotherapy combined with imatinib. Here, we report the case of a child with Ph+ all who had persistent elevation of mrd, but no evidence of hematologic relapse while receiving imatinib plus intensive chemotherapy. Dasatinib was substituted for imatinib because no suitable donor for allogeneic hematopoietic stem-cell transplantation (hsct) was available. Less-intensive chemotherapy with methotrexate and 6-mercaptopurine was administered concomitantly. No serious adverse events were encountered. With continuous dasatinib combined with chemotherapy, but no allogeneic hsct, our patient reached complete molecular remission and has been in complete molecular remission for more than 13 months. This report is the first about the long-term use of dasatinib in patients with Ph+ all and mrd elevation but hematologic remission during imatinib chemotherapy. In a similar situation, chemotherapy combined with dasatinib instead of allogeneic hsct could be considered to avoid hsct-related mortality and morbidity. Clinical trials are needed.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".