Cost‐effectiveness evaluation of clobetasol propionate shampoo (CPS) maintenance in patients with moderate scalp psoriasis: a Pan‐European analysis
Bibliographic record
Abstract
BACKGROUND: Scalp psoriasis is a difficult to treat and usually chronic manifestation of psoriasis. The CalePso study showed that CPS (Clobex(®) Shampoo) in maintenance therapy of scalp psoriasis (twice weekly) significantly increases the probability of keeping patient under remission during 6 months, compared with vehicle (40.3% relapses vs. 11.6% relapses, ITT). OBJECTIVE: The objective of the study was to assess the cost-effectiveness of a maintenance therapy with CPS vs. its vehicle in nine European countries. METHODS: A 24-week decision tree model was developed with 4-weekly time steps. The considered population has moderate scalp psoriasis successfully treated with a daily application of CPS up to 4 weeks. Data were taken from the CalePso study and from national experts' recommendations for alternative treatment choices, with their probabilities of success taken from literature to develop country-specific models. Health benefits are measured in disease-free days (DFD). The economic analysis includes drug and physician costs. A probabilistic sensitivity analysis (PrSA) assesses the uncertainty of the model. RESULTS: Depending on the country, the mean total number of DFDs per patient is 21-42% higher with CPS compared with vehicle, and the mean total cost is 11-31% lower. The mean costs per DFD are 30-46% lower with CPS compared with the vehicle. The PrSA showed in 1000 simulations that CPS is more effective vs. vehicle in 100% of the cases and less expensive than its vehicle in 80-99% of the cases. CONCLUSION: This model suggests that CPS is cost-effective in maintaining the success achieved in moderate scalp psoriasis patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".