SUN-356 Burosumab Resulted in Greater Clinical Improvements Compared with Higher-dose Conventional Therapy in Children with X-linked Hypophosphatemia (XLH)
Bibliographic record
Abstract
Abstract In XLH, excess circulating FGF23 causes hypophosphatemia, rickets, lower limb deformity, and impaired growth and mobility. An active-controlled, phase 3 trial (CL301; NCT02915705) showed treatment with burosumab, a fully human monoclonal antibody against FGF23, resulted in significantly greater improvements in all of these outcomes in children with XLH, compared with continuing oral phosphate and active vitamin D as conventional therapy (Pi/D) per established guidelines. In a post-hoc analysis, we compared children who received burosumab vs those who received an average 64-week oral phosphate daily dose >40 mg/kg (higher-dose Pi) vs ≤40 mg/kg (lower-dose Pi). Sixty-one children with XLH (1–12 years-old) were randomized 1:1 after a 7-day Pi/D washout to receive burosumab (n=29) starting at 0.8 mg/kg subcutaneously Q2W or to resume Pi/D (n=32) titrated by their investigator, for 64 weeks. Eligibility criteria included Rickets Severity Score (RSS) ≥2.0 despite prior Pi/D treatment. Of the 32 subjects randomized to Pi/D, 12 received average higher-dose Pi and 20 received average lower-dose Pi (as specified above). The primary endpoint was rickets healing, using the Radiographic Global Impression of Change (RGI-C) Scale. At week 64, the improvement in the least square (LS) mean (LS mean [±SE; 95%CI]) RGI-C Global Score for rickets was greater on burosumab (+2.06 [0.072; 1.92, 2.20]) compared with either higher-dose (+1.02 [0.241; 0.55, 1.50]) or lower-dose (+1.04 [0.162; 0.73, 1.36]) Pi. The mean decrease in the total RSS from baseline was also greater on burosumab (-2.23 [0.117; -2.46, -2.00]) compared with higher-dose (-0.87 [0.264; -1.39, -0.35] or lower-dose (-1.09 [0.180; -1.45, -0.74]) Pi. Similarly, the mean RGI-C Lower Limb Deformity Score was greater on burosumab (+1.25 [0.170; 0.92, 1.59]) compared with either higher-dose (+0.32 [0.188; -0.05, 0.69]) or lower-dose (+0.26 [0.146; -0.02, 0.55]) Pi. Adverse events including hypersensitivity and injection site reactions, were more frequent with burosumab, and were mild to moderate in severity overall. No discontinuations occurred. In conclusion, children with XLH treated with burosumab had greater improvements in rickets and lower limb deformity compared with subjects receiving higher or lower doses of Pi.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".