Relapse in children with acute lymphoblastic leukemia involving selection of a preexisting drug-resistant subclone
Why this work is in the frame
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Bibliographic record
Abstract
Relapse following remission induction chemotherapy remains a barrier to survival in approximately 20% of children suffering from acute lymphoblastic leukemia (ALL). To investigate the mechanism of relapse, 27 matched diagnosis and relapse ALL samples were analyzed for clonal populations using polymerase chain reaction (PCR)-based detection of multiple antigen receptor gene rearrangements. These clonal markers revealed the emergence of apparently new populations at relapse in 13 patients. More sensitive clone-specific PCR revealed that, in 8 cases, these "relapse clones" were present at diagnosis and a significant relationship existed between presence of the relapse clone at diagnosis and time to first relapse (P < .007). Furthermore, in cases where the relapse clone could be quantified, time to first relapse was dependent on the amount of the relapse clone at diagnosis (r = -0.84; P = .018). This observation, together with demonstrated differential chemosensitivity between subclones at diagnosis, argues against therapy-induced acquired resistance as the mechanism of relapse in the informative patients. Instead these data indicate that relapse in ALL patients may commonly involve selection of a minor intrinsically resistant subclone that is undetectable by routine PCR-based methods. Relapse prediction may be improved with strategies to detect minor potentially resistant subclones early during treatment, hence allowing intensification of therapy.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it