Long-term prophylaxis with lanadelumab for HAE: authorization for temporary use in France
Bibliographic record
Abstract
BACKGROUND: Hereditary angioedema (HAE) is associated with a heavy burden of illness. OBJECTIVE: To evaluate use of lanadelumab in a French Authorization for Temporary Use (ATU) program. METHODS: ATU requests were made between October 12, 2018, and March 13, 2019; patients were followed through September 23, 2019. At entry, patients received lanadelumab 300 mg every 2 weeks. HAE attack characteristics were evaluated at day (D) 0 and months (M) 3 and 6. Patients completed the Angioedema Quality of Life (AE-QoL) questionnaire at initiation and monthly and the Angioedema Activity Score questionnaire daily in 28 day cycles (AAS28). RESULTS: In total, 77 patients received ≥ 1 lanadelumab dose; 69 had ≥ 1 quarterly follow-up visit (analyzed population). Mean (standard deviation [SD]) lanadelumab exposure was 240.4 (53.7) days. Lanadelumab dose was modified in 12 patients (mostly to every 4 weeks). For the analyzed population, compared with attacks/month (mean [SD]) within 6 months before ATU (2.68 [2.54]), fewer attacks occurred between initiation and first visit (0.16 [0.42]; P < 0.001) or last visit (0.16 [0.42]; P < 0.001); D15 and last visit (0.15 [0.41]); and D70 and last visit (0.17 [0.70]). AE-QoL total and domain scores were significantly higher at initiation versus M3 and M6; 55% and 65% of patients, respectively, achieved a minimal clinically important difference from D0 to M3 and D0 to M6. Proportion of patients with AAS28 of 0 was higher during M3 (90%) and M6 (83%) than initiation (59%). The most frequently reported adverse events included headache (7.3%) and injection site pain (6.3%). CONCLUSIONS: Lanadelumab reduced attack rates, improved quality of life, and was generally well tolerated.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".