MY-T study: Symptom-based titration decisions when using testosterone nasal gel, Natesto®
Bibliographic record
Abstract
INTRODUCTION: , testosterone nasal gel (TNG), is a testosterone therapy (TTh) indicated for adult male hypogonadism. This study allowed titration decisions to be based on physicians' assessment of patient symptoms. METHODS: Hypogonadal males on active topical testosterone therapy (TThE) or naive to any form of testosterone therapy (TThN) were treated with 22 mg TNG daily (11 mg twice daily) for 90 days. Titration was determined by the physician at day 90 wherein the dose was increased to 33 mg daily if symptoms were not properly managed. Total testosterone (TT) levels were collected at day 90 and 120 and the quantitative Androgen Deficiency in the Aging Male (qADAM) symptom questionnaire was administered on days 0, 30, 60, 90, and 120. RESULTS: At study endpoint, 77.0% of all patients were in the normal TT range. Mean qADAM scores increased from 30.8 at baseline to 35.5 (6.6) at day 90. Physician assessments resulted in 37% patients being up-titrated for an additional 30 days, however, qADAM scores did not change significantly at the higher dose. CONCLUSIONS: The majority of patients achieved the normal range of testosterone with TNG when physicians based their titration decision on an assessment of symptoms. Sexual function and energy-related symptoms were predictive of improvements resulting from treatment. These symptoms were the most relevant indicators for physicians in making decisions relating to titration.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".