Cinacalcet normalizes serum calcium in a double-blind randomized, placebo-controlled study in patients with primary hyperparathyroidism with contraindications to surgery
Bibliographic record
Abstract
OBJECTIVE: Primary hyperparathyroidism (PHPT) is diagnosed by the presence of hypercalcemia and elevated or nonsuppressed parathyroid hormone (PTH) levels. Although surgery is usually curative, some individuals fail or are unable or unwilling to undergo parathyroidectomy. In such individuals, targeted medical therapy may be of value. Cinacalcet normalized calcium level and lowered PTH in patients with PHPT in several phase 2 and open-label studies. We compared cinacalcet and placebo in subjects with PHPT unable to undergo parathyroidectomy. DESIGN: Phase 3, double-blind, multi centere, randomized, placebo-controlled study. METHODS: Sixty-seven subjects (78% women) with moderate PHPT were randomized (1:1) to cinacalcet or placebo for ≤28 weeks. MAIN OUTCOME MEASURE: Achievement of a normal mean corrected total serum calcium concentration of ≤10.3 mg/dl (2.575 mmol/l). RESULTS: Baseline median (quartile 1 (Q1), Q3) serum PTH was 164.0 (131.0, 211.0) pg/ml and mean (s.d.) serum Ca was 11.77 (0.46) mg/dl. Serum Ca normalized (≤10.3 mg/dl) in 75.8% of cinacalcet- vs 0% of placebo-treated subjects (P<0.001). Corrected serum Ca decreased by ≥1.0 mg/dl from baseline in 84.8% of cinacalcet- vs 5.9% of placebo-treated subjects (P<0.001). Least squares mean (s.e.m.) plasma PTH change from baseline was -23.80% (4.18%) (cinacalcet) vs -1.01% (4.05%) (placebo) (P<0.001). Similar numbers of subjects in the cinacalcet and placebo groups reported adverse events (AEs) (27 vs 20) and serious AEs (three vs four). Most commonly reported AEs were nausea and muscle spasms. CONCLUSIONS: These results demonstrate that cinacalcet normalizes serum calcium in this PHPT population and appears to be 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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".