The market lifecycle of duloxetine for urinary incontinence in Norway
Bibliographic record
Abstract
OBJECTIVE: To investigate the epidemiology of prescriptions for duloxetine for the treatment of stress urinary incontinence during its entire lifecycle in Norway (October 2004-May 2007), including the persistence of use of the drug and the prescribers. DESIGN AND SETTING: Observational study in Norway. SAMPLE: All prescriptions on duloxetine filled in Norwegian pharmacies. METHODS: Data from the Norwegian Prescription Database. MAIN OUTCOME MEASURE: Patient's age, unique identification, date of dispensing, data on specialty of the prescribing doctor, and number of packages purchased. Persistence of use of duloxetine was analyzed by grouping the months of first prescription filled into quarters of a year, from the fourth quarter of 2004 to the third quarter of 2007. RESULTS: A total of 3,024 filled prescriptions were recorded of which 2,903 (96%) could be further analyzed, corresponding to 37 users per 100,000 women in the population. Each patient filled a mean of 3.4 prescriptions. The persistence of use was very low from the second quarter itself, and after 1 year only 12.5% of the patients still purchased the drug. Most prescriptions were written by GPs and gynecologists. A prescription database like ours consists of dispensed prescriptions and not drugs taken. We believe that these biases are of little importance for the main results. CONCLUSIONS: Analyses from the national prescription database show that duloxetine had a low uptake on the market and a low persistence rate among the patients during its full lifecycle on the Norwegian market.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".