The Impact of Drug Reimbursement Policy on Rates of Testosterone Replacement Therapy among Older Men
Bibliographic record
Abstract
BACKGROUND: Despite a lack of data describing the long-term efficacy and safety of testosterone replacement therapy (TRT), prescribing of testosterone to older men has increased with the availability of topical formulations. The magnitude of this increase and the impact of formulary restrictions on testosterone prescribing are poorly characterized. METHODS: We conducted a time series analysis using the linked health administrative records of men aged 66 years or older in Ontario, Canada between January 1, 1997 and March 31, 2012. We used interventional autoregressive integrated moving average models to examine the impact of a restrictive drug reimbursement policy on testosterone prescribing and examined the demographic profile of men initiating testosterone in the final 2 years of the study period. RESULTS: A total of 28,477 men were dispensed testosterone over the study period. Overall testosterone prescribing declined 27.9% in the 6 months following the implementation of the restriction policy (9.5 to 6.9 men per 1000 eligible; p<0.01). However, the overall decrease was temporary and testosterone use exceeded pre-policy levels by the end of the study period (11.0 men per 1000 eligible), largely driven by prescriptions for topical testosterone (4.8 men per 1000 eligible). Only 6.3% of men who initiated testosterone had a documented diagnosis of hypogonadism, the main criteria for TRT reimbursement according to the new policy. CONCLUSION: Government-imposed restrictions did not influence long-term prescribing of testosterone to older men. By 2012, approximately 1 in every 90 men aged 66 or older was being treated with TRT, most with topical formulations.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 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".