Efficacy of Nasal Testosterone Gel (Natesto®) Stratified by Baseline Endogenous Testosterone Levels
Bibliographic record
Abstract
OBJECTIVE: Pharmacokinetic and efficacy data from a phase 3 testosterone nasal gel (TNG) study were stratified by baseline endogenous testosterone level in patients with testosterone deficiency. Total testosterone (TT), LH, and FSH levels, as well as erectile function, mood, and lean body mass for each group were compared. In a subset of patients with very low baseline endogenous testosterone levels (<100 ng/dL), we investigated whether TNG is a suitable treatment option. MATERIALS AND METHODS: Patients with testosterone deficiency (serum TT <300 ng/dL) were treated with TNG for 3 months, followed by safety extension periods of 90 and/or 180 days. Pharmacokinetic parameters were calculated from serum hormone levels on days 30 and 90, along with efficacy measurements, which were analyzed by comparison with baseline values. Baseline and/or predose TT values were used for patient stratification. RESULTS: Prestudy and predose endogenous testosterone concentrations correlated. The maximal concentration of TT was nearly identical across all cohorts at days 30 and 90, whereas the average concentration over 24 hours had a slight positive dependence relative to predose levels. LH levels remained in the normal range but were decreased more in patients with higher starting baseline levels. These findings indicate that TNG works with an active hypothalamic-pituitary-gonadal axis that responds to each dose of TNG throughout the treatment period. Patients with the lowest endogenous testosterone levels received maximum exposure impact from each TNG dose. Patients with severe testosterone deficiency had similar efficacy improvements as the remainder of the study population. CONCLUSION: All testosterone-deficient cohorts were successfully treated with TNG.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".