Pasireotide LAR maintains inhibition of GH and IGF-1 in patients with acromegaly for up to 25 months: results from the blinded extension phase of a randomized, double-blind, multicenter, Phase III study
Bibliographic record
Abstract
PURPOSE: A large, randomized, double-blind, Phase III core study demonstrated that pasireotide LAR was significantly superior to octreotide LAR at providing GH <2.5 μg/L and normalized IGF-1 after 12 months' treatment in patients with acromegaly. We report the efficacy and safety of pasireotide LAR and octreotide LAR after up to 26 months' treatment. METHODS: Patients with GH <2.5 μg/L and IGF-1 ≤1× ULN at month 12, or patients considered to be experiencing clinical benefit, were eligible to continue receiving their randomized therapy in the extension. Efficacy and safety in the pasireotide LAR and octreotide LAR groups were evaluated for up to 26 months. RESULTS: Overall, 120 patients who completed the core study continued receiving pasireotide LAR (n = 74) or octreotide LAR (n = 46) in the extension. At month 25, biochemical control (GH <2.5 μg/L and normal IGF-1) was achieved by 48.6% (36/74) and 45.7% (21/46) of patients in the pasireotide LAR and octreotide LAR arms [60.8% (45/74) and 52.2% (24/46) when including patients with IGF-1 < LLN], respectively. In total, 74.7% of pasireotide LAR and 71.6% of octreotide LAR patients had tumor volume decrease ≥20% from baseline to month 26. Most AEs were mild or moderate. Hyperglycemia-related AEs were seen in 62.9 and 25.0% of pasireotide LAR and octreotide LAR patients, respectively. No new safety signals were observed in the extension compared with the core study. CONCLUSIONS: GH and IGF-1 suppression is maintained for up to 25 months during pasireotide LAR treatment. The safety profile of pasireotide LAR is typical of a somatostatin analogue, except for the frequency and degree of hyperglycemia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".