Efficacy and safety of ritlecitinib in adolescents with alopecia areata: Results from the <scp>ALLEGRO</scp> phase 2b/3 randomized, double‐blind, placebo‐controlled trial
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: This subgroup analysis of the ALLEGRO phase 2b/3 trial (NCT03732807) evaluated the efficacy and safety of ritlecitinib, an oral, selective dual JAK3/TEC family kinase inhibitor, for the treatment of alopecia areata (AA) in patients aged 12-17 years. METHODS: In ALLEGRO-2b/3, patients aged ≥12 years with AA and ≥50% scalp hair loss received once-daily ritlecitinib 50 or 30 mg (±4-week 200-mg loading dose) or 10 mg or placebo for 24 weeks. In a subsequent 24-week extension period, ritlecitinib groups continued their doses, and patients initially assigned to placebo switched to 200/50 or 50 mg daily. Clinician- and patient-reported hair regrowth outcomes and safety were assessed. RESULTS: In total, 105 adolescents were randomized. At Week 24, 17%-28% of adolescents achieved a Severity of Alopecia Tool (SALT) score ≤20 (≤20% scalp without hair) in the ritlecitinib 30 mg and higher treatment groups versus 0% for placebo. At Week 48, 25%-50% of patients had a SALT score ≤20 across ritlecitinib treatment groups (30 mg and higher). Adolescents reporting that their AA "moderately" or "greatly" improved were 45%-61% in the ritlecitinib groups (30 mg and higher) (vs. 10%-22% for placebo) at Week 24 and 44%-80% at Week 48. The most common adverse events in adolescents were headache, acne, and nasopharyngitis. No deaths, major adverse cardiovascular events, malignancies, pulmonary embolisms, opportunistic infections, or herpes zoster infections were reported. CONCLUSION: Ritlecitinib treatment demonstrated clinician-reported efficacy, patient-reported improvement, and an acceptable safety profile through Week 48 in adolescents with AA with ≥50% scalp hair loss.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".