The effect of different administrations of testosterone therapy on adverse prostate events: A Bayesian network meta-analysis
Bibliographic record
Abstract
Background Hypogonadism has become a major cause endangering men’s health and quality of life all over the world. Testosterone Therapy (TT) is a widely accepted treatment for relieving hypogonadal symptoms. However, the effect of different administrations of TT on prostate safety is still unclear. Methods We did a thorough search of PubMed, Embase and Cochrane Library to identify eligible studies up to January 2022. Randomized controlled trials (RCTs) and Cohort studies evaluating the impacts of using different formulations of TT on prostate parameters were included. Changes of prostate-specific antigen (PSA) level and prostate cancer (Pca) cases were used as the primary outcomes. Quality of individual studies was estimated by RoB2 (Cochrane tool for assessing the risk of bias in randomized trials) and the Newcastle-Ottawa scale (Tool for assessing non-RCTs). Certainty of evidence for each study was evaluated according to the evidence assessment criteria of the Oxford Evidence-based Medicine Center. Random-effect network meta-analysis(NMA)was performed based on the Bayesian model. Results Thirty-five studies (30 RCTs and 5 Cohort studies) with 7,740 participants were included. TT administration led to fewer Pca patients (RR=0.62, 95%CI [0.39,0.99], I2=0%), while little decreasing in PSA level (MD=-0.05, 95%CI [-0.08, -0.02], I2=0%). The NMA revealed that compared with other formulations, the intramuscular injection was the most likely to rank first in decreasing Pca cases. The TT also resulted in more biopsy cases (RR=2.38, 95%CI [1.01,5.60], I2=0%). As for NMA, intramuscular injection also performed relatively better in fewer prostate biopsy cases compared with transdermal group. Conclusion TT does not lead to abnormal PSA changes and increased risk of Pca in patients with hypogonadism or low testosterone level. Compared with other preparations of TT, intramuscular injection proved better in minimizing Pca cases and was more likely to result in fewer prostate biopsy cases.
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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 | 0.051 | 0.076 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.065 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".