Management of patients with Cushing's disease: a Canadian cost of illness analysis.
Bibliographic record
Abstract
BACKGROUND: Cushing's disease (CD) is a rare disorder caused by increased pituitary secretion of adrenocorticotropic hormone (ACTH) resulting in elevated production of cortisol. It is associated with multiple adverse cardiovascular, metabolic, musculoskeletal and mental consequences. Patients with CD require substantial health care resources both in terms of treatments with a curative intent and control of disease related co-morbidities. In this study, a cost of illness analysis was conducted to estimate the direct cost of CD care in Canada. METHODS: This was a retrospective cohort study of 86 CD patients. Data collection included patient demographic and disease related information, existing comorbidities, treatments received and all clinical outcomes. In addition, healthcare resource utilization to manage CD was also collected. Once the mean cost per patient was determined, the overall disease prevalence was used to estimate the total direct cost of illness in Canada. RESULTS: The sample included 86 CD patients, with a mean age of 43 years at diagnosis, 72% were female. All received a first line intervention consisting of transsphenoidal pituitary surgery (78%), bilateral adrenalectomy (5%), radiation therapy (5%) or medical therapy ± radiation (13%). In addition, 18 and 14 patients subsequently received a second and third line intervention, respectively. The mean cost was $85,946 per patient over the first three lines of therapy. Combining this estimate with the reported disease prevalence (5.5 patients per 100,000 [95%CI: 4.2 to 6.8]), the total direct cost of CD in Canada was estimated to be approximately $80.6 million (95%CI: $61.5 to $99.6 million) over the first 3 lines of therapy. CONCLUSIONS: CD is a debilitating condition that is associated with substantial health care costs. Strategies that provide clinical cure or long term disease control need to be identified to reduce patient morbidity and to save health care costs in patients who remain uncontrolled.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".