Cabergoline monotherapy in the long-term treatment of Cushing's disease
Bibliographic record
Abstract
BACKGROUND: Cabergoline is a long-acting dopamine receptor agonist used to treat prolactinomas. Identification of D(2) receptors in corticotroph tumors led to clinical trials of cabergoline therapy in limited cases of Nelson's syndrome, ectopic ACTH-secreting tumors, and recently Cushing's disease (CD). OBJECTIVE: To evaluate the long-term efficacy of cabergoline monotherapy in patients with CD. METHODS: Retrospective analysis of non-randomized clinical therapy with cabergoline in 30 patients with CD treated in academic centers of Buenos Aires and Montreal. Cabergoline was initiated at 0.5-1.0 mg/week and adjusted up to a maximal dose of 6 mg/week based on urinary free cortisol (UFC) levels. Complete response to cabergoline was defined as a sustained normalization of UFC with at least two normal values measured at 1-3 months interval; partial response was defined as a decrease of UFC to <125% of the upper limit of normal, and treatment failure as UFC ≥ 125% of it. RESULTS: Within 3-6 months, complete response was achieved in 11 patients (36.6%) and partial response in 4 patients (13.3%). After long-term therapy, nine patients (30%) remain with a complete response after a mean of 37 months (range from 12 to 60 months) with a mean dose of 2.1 mg/week of cabergoline. Two patients escaped after 2 and 5 years of complete response, but one patient transiently renormalized UFC after an increase in cabergoline dosage. No long-term response was maintained in four initial partial responders. CONCLUSIONS: Cabergoline monotherapy can provide an effective long-term medical therapy for selected patients with CD, but requires close follow-up for dose adjustments.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".