LGG-19. SLIPPED CAPITAL FEMORAL EPIPHYSIS (SCFE): A RARE ADVERSE EVENT ASSOCIATED WITH FGFR TYROSINE KINASE INHIBITOR THERAPY IN A CHILD
Bibliographic record
Abstract
Abstract BACKGROUND FGFR tyrosine kinase inhibitors (FGFR-TKIs) are being increasingly used off-label in children with hard-to-treat tumors harboring specific FGFR alterations. We report a case of Slipped Capital Femoral Epiphysis (SCFE), an on target skeletal toxicity of a pan-FGFR TKI inhibitor, erdafitinib. METHODS Data was extracted from chart review of the patient and literature search for the use of FGFR-TKIs in children and their side effects. RESULTS A 13-year-old boy was diagnosed to have a optic pathway/ hypothalamic glioma with signs of increased intracranial pressure and obstructive hydrocephalus requiring placement of ventriculo-peritoneal (VP) shunt. Sequencing of the tumor showed FGFR1-Tyrosine kinase domain internal tandem duplication (FGFR1-KD-ITD) and was negative for BRAF mutation/ fusion. Two weeks later, he was treated for a VP shunt infection (surgical revision and 6 weeks antibiotics). He developed hypothalamic obesity with rapid weight gain and BMI >30. After a four-month delay from the initial diagnosis, he was started on erdafitinib a pan-FGFR1-4 inhibitor, through a special access program. At 12 weeks of treatment, he developed persistent knee pain. X-ray of the hips showed slipped capital femoral epiphysis (SCFE) of the right hip. Erdafitinib was discontinued and he underwent surgery with in-situ pinning of the right hip and prophylactic pinning of the left hip. MRI at the time of stopping the medication showed a 30% decrease in the size of the tumor, which has remained stable at 6 months follow up. CONCLUSIONS Based on our experience and literature review of pediatric patients who are treated with pan-FGFR TKIs, we recommend: a) monitoring both rate of weight gain/ BMI for obesity and growth velocity while on therapy and b) update the drug toxicity profile of FGFR TKIs to include skeletal toxicities and inform parents/ patients of these toxicities at the time of consent for therapy.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".