Management of chronic myeloid leukemia in children and adolescents: tyrosine kinase inhibitor efficacy, survivorship challenges, and long-term hemostatic safety
Bibliographic record
Abstract
Background. The introduction of BCR::ABL1 tyrosine kinase inhibitors (TKIs) has transformed pediatric chronic myeloid leukemia (CML) from a life-threatening disease often requiring transplantation into a manageable chronic condition. However, this success necessitates a shift in clinical focus from acute survival to the multi-system, long-term toxicities incurred over a lifetime of therapy. Objective. The systematic scoping review synthesizes evidence from 2021 to the present, evaluating the comparative efficacy of TKI generations, long-term developmental and reproductive safety, and the complex cardiovascular and hemostatic risks in children and adolescents with CML. Methods. Following PRISMA-ScR guidelines, a systematic search of PubMed, Scopus, and Web of Science was conducted for studies published from January 2021. Key guidelines from the last decade were included. Observational studies were appraised using the Newcastle-Ottawa Quality Assessment Scale (NOQAS). Data were extracted and synthesized narratively across six key domains: 1) epidemiology, 2) comparative efficacy, 3) growth and endocrine safety, 4) fertility and reproductive safety, 5) cardiovascular and hemostatic safety, and 6) emergent therapies. Results. Pediatric CML presents with more aggressive features (e. g., higher leukocytosis, larger splenomegaly) than adult CML. While second-generation (2G) TKIs (dasatinib, nilotinib) demonstrate superior rates of deep and rapid molecular response (DMR) compared to imatinib, this has not translated into a proven overall survival (OS) benefit. However, achieving DMR is a prerequisite for treatment-free remission (TFR), a critical goal in pediatrics to mitigate long-term toxicities. Safety analysis revealed significant, TKI class-effect toxicities, including high rates of short stature (up to 26.5% in pre-pubertal patients) and low bone mineral density (35.2%). Growth impairment is comparable across imatinib and 2G-TKIs. A critical, sex-specific risk exists for fertility, with TKI teratogenicity confirmed in maternal exposure (5% anomaly rate) but not in paternal exposure, where large registry data show no increased risk. A critical analysis of “cardiovascular risk” reveals a divergent hemostatic risk spectrum: Nilotinib and ponatinib confer a pro-thrombotic (arterial, venous) risk, whereas dasatinib induces an anti-platelet (hemorrhagic) risk via SRC-kinase inhibition. Surveys confirm these specific risks are poorly recognized, with no standardized surveillance in pediatric practice. Conclusions. TKI selection in pediatric CML must evolve beyond efficacy alone to a multi-disciplinary, risk-stratified model. This includes balancing the TFR-enabling efficacy of 2G-TKIs against their specific toxicity profiles. This review proposes a “Hemostatic Risk Spectrum” as an essential framework, mandating that TKI selection be guided by the patient’s baseline hemostatic risk (e. g., avoiding nilotinib in thrombophilia, avoiding dasatinib in bleeding disorders). Standardized protocols for monitoring endocrine, metabolic, and hemostatic health are urgently required to ensure safe, long-term survivorship.
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 | 0.027 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".