Canadian trends in testosterone therapy
Bibliographic record
Abstract
INTRODUCTION: Rates of testosterone therapy (TT) prescribing dropped dramatically following the U.S. Food and Drug Administration and Health Canada warning regarding potential cardiovascular morbidity in 2014. Since then, prescription rates appear to be increasing in the U.S., however, data on TT use in Canada is lacking. Current database studies suffer from incomplete prescription capture, lack of information on continued use, and confounding from concurrent population growth. Nova Scotia (NS) is a Canadian province with minimal population growth over the past decade. NS tracks every testosterone prescription and refill through their prescription monitoring program (NSPMP). All testosterone prescriptions must be written on triplicate forms, allowing for comprehensive tracking. The purpose of this study is to describe the long-term prescription trends of testosterone in a mid-sized Canadian province using a database that captures 100% of all TT prescriptions written and filled. METHODS: Data were extracted from the NSPMP database on all prescriptions and prescription refills of androgens for men over 18 years of age from 2007-2019. Population statistics were gained using publicly available data from Statistics Canada. Analysis of patterns on individual years and over time were examined for number of patients, prescriptions, and prescribers, as well as formulation. RESULTS: The male population of Nova Scotia remained relatively stable throughout the study period (2007: 455 064; 2019: 475 478; population increase of 4.3%). A total of 7883 men (1.7% of the male population) received a prescription for TT during the study period; 1673 men received only one prescription in the entire study period and 5446 men remained on TT for longer than six months. Of the 1730 men under 45 who were prescribed TT, 75% (n=1298) of them stayed on it for more than six months; 1856 men (24%) switched the type of testosterone they were on during the study period. The number of men receiving TT yearly increased by 98%, from 1235 in 2007 to 2448 in 2019. The number of men receiving TT plateaued in 2014, except for men under age 35, in whom it has steadily increased every year since 2007. Interestingly, primary care providers (PCPs) wrote 92% of all prescriptions, on average (interquartile range 90-93). CONCLUSIONS: In a mid-sized Canadian province with stable population growth, prescriptions of testosterone increased until 2014, and then either stabilized or decreased. TT prescriptions in young men have continued to increase yearly. Injectable and gel-based formulations have increased in popularity over the past decade. Future efforts to educate prescribers, especially surrounding the effects on fertility in young men, should be largely focused on PCPs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.013 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".