Evidence for the efficacy and safety of tadalafil and finasteride in combination for the treatment of lower urinary tract symptoms and erectile dysfunction in men with benign prostatic hyperplasia
Bibliographic record
Abstract
Benign prostatic hyperplasia (BPH) is an age-related phenomenon associated with prostatic enlargement and bladder outlet obstruction that can cause significant lower urinary tract symptoms (LUTS). These LUTS have a negative impact on an individual's quality of life, which is why treatment of symptomatic BPH has become a major priority. Although surgical interventions exist for treating BPH, pharmacological therapies are often preferred due to their minimal invasiveness and high degree of effectiveness. The three classes of drugs approved for treating BPH include α-blockers, 5-α-reductase inhibitors (5-ARIs) and phosphodiesterase 5 (PDE-5) inhibitors. Individually, each class of drug has been studied and shown to improve symptom relief through a variety of different mechanisms. A more recent focus has been on the development of combinatorial therapies that combine classes of drugs in order to provide maximal benefit. The mTOPS and CombAT studies were the first of their kind to examine whether the combination of 5-ARIs and α-blockers was more effective than monotherapy alone. Both studies found similar results in that the combinatorial therapy was superior to monotherapy. Over the last decade other combinatorial therapies have been at the forefront of investigation. One in particular is the combination of tadalafil, a PDE-5 inhibitor, with finasteride, a 5-ARI. Studies have shown that the combination of tadalafil and finasteride is a safe, effective, and well tolerated treatment for BPH. Evidence suggests that this combination may be particularly effective in reducing treatment-related sexual adverse events associated with 5-ARI treatments. The following review will explore in detail the current evidence surrounding treatment of BPH LUTS using tadalafil and finasteride.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".