Determinants of persistence with weekly bisphosphonates in patients with osteoporosis.
Bibliographic record
Abstract
OBJECTIVE: To evaluate the relationship between the persistent acquisition of bisphosphonate (BP) osteoporosis (OP) medication and the following factors: BP prescribed; whether BP was first used to replace another non-BP drug for OP; patient age; type of drug coverage; specialty of initial prescribing physician; and number and type of comorbid diseases. METHODS: Data were acquired from a large Canadian public and private claims database, which included information on all prescriptions filled, including drug preparation, dose, dosing schedule, number of tablets dispensed, and the date of dispensing. A total of 62,897 female patients who had initiated weekly BP therapy (risedronate 35 mg once weekly or alendronate 70 mg once weekly) for OP between January 1, 2003, and February 28, 2006 were analyzed, each for 12 months. Persistence rates were determined for 6 and 12 months post initial prescription. Regression models were used to assess the influence of various patient, physician, and drug factors. RESULTS: Persistence of BP declined over the first year of BP prescription, to between 60% and 74% by 6 months, and between 37% and 59% by 12 months, depending upon a variety of factors. The factors that most adversely influenced BP persistence were patient age (< 65 vs > or = 65; p < 0.0001); the type of drug coverage (public vs private; p < 0.0001); prescribing physician specialty (GP vs specialist; p < 0.0001); and number and type of comorbid illnesses (p < 0.01). CONCLUSION: Persistence to BP declined significantly over one year. Healthcare practitioners should take note of several factors when counselling patients taking BP for OP.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".