Testosterone Replacement Therapy Following Radical Prostatectomy
Bibliographic record
Abstract
INTRODUCTION: Controversy exists regarding testosterone replacement therapy (TRT) in men following radical prostatectomy (RP). Many clinicians are hesitant to offer patients TRT after an RP, out of concern that the increased androgen levels may promote tumor progression or recurrence from residual tumor. Recently, several small studies have demonstrated the use of TRT in men following an RP and have shown an improvement in serum testosterone levels with no increase in prostate-specific antigen (PSA) values. AIMS: The aim of this article is to assess changes in PSA and testosterone values in hypogonadal patients on TRT after RP and also to evaluate the impact of pathologic Gleason grade on ultimate PSA values. METHODS: All hypogonadal men who were treated with TRT by members of our department following RP were retrospectively reviewed. PSA values before RP, after RP, and after TRT were evaluated. Serum testosterone levels before and after TRT were also examined. Only patients with undetectable PSA values and negative surgical margins on pathologic specimen were offered TRT and included in the study. MAIN OUTCOME MEASURES: Main outcome measures were changes in PSA and testosterone values after initiation of TRT. RESULTS: Fifty-seven men, ages 53-83 years (mean 64), were identified as having initiated TRT following RP. Men received TRT for an average of 36 months following RP (range 1-136 months). Patients were followed an average of 13 months after initiation of TRT (range 1-99 months). The mean testosterone values rose from 255 ng/dL before TRT to 459 ng/dL after TRT (P < 0.001). There was no increase in PSA values after initiation of TRT and thus no patient had a biochemical PSA recurrence. CONCLUSION: TRT is effective in improving testosterone levels, without increasing PSA values, in hypogonadal men who have undergone RP.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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".