Long-Term Treatment Patterns of Testosterone Replacement Medications
Bibliographic record
Abstract
INTRODUCTION: Testosterone replacement therapy (TRT) is prescribed to men diagnosed with hypogonadism to alleviate symptoms, improve quality of life, and improve overall health. However, most men use TRT for only a short duration. AIM: To evaluate the long-term treatment patterns in hypogonadal men using topical TRT or short-lasting TRT injections. METHODS: Using the Truven MarketScan(®) Database, 15,435 men who received their first (index) topical TRT prescription and 517 men who received their short-lasting TRT injection index prescription in 2009 were followed from 12 to 30 months after treatment initiation. Treatment interruption was defined as a medication gap of >30 days. Patients who remained off treatment were classified as having discontinued treatment. Patients who restarted therapy after 30 days were classified as cyclic users. Patients were required to have continuous insurance coverage during 1 year prior to treatment initiation and at least 1 year afterward. MAIN OUTCOME MEASURES: Main outcome measures were length of therapy, discontinuation, and restarts of topical TRT or short-lasting TRT injections. RESULTS: The patient characteristics were similar for patients who received topical TRT or short-lasting TRT injections. Of the patients who discontinued therapy during the follow-up period, the percentages of patients who were still on therapy after 3 months were 52% and 31% for topical TRT and short-lasting TRT users, respectively. For cyclic users, there was an attrition rate of approximately 40% to 50% of patients in each cycle. For both topical TRT and short-lasting TRT injections, the gap between stopping and restarting therapy tended to decrease over time. CONCLUSIONS: In this analysis, high discontinuation rates were observed. The treatment pattern of TRT may be related to the disease state rather than dosing, daily use, or mode of administration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".