A review of the current status of topical treatments for premature ejaculation
Bibliographic record
Abstract
We examine the progress that has been made towards the development of topical treatments for premature ejaculation (PE). Although generally regarded as one of the most common male sexual problems, the lack of approved pharmacological agents for PE means that treatment options are limited to behavioural therapy, where available, and the use of drugs 'off-label'. There are various theories on the aetiology of PE, but it seems likely that both biological and psychological factors are important. One theory, that men with PE might have a heightened sensory response to penile stimulation, provides the rationale for using topical therapy; reducing the sensitivity of the glans penis with topical desensitizing agents (e.g. local anaesthetics) might improve ejaculatory latency without adversely affecting the sensation of ejaculation. Off-label topical treatments are now relatively widely used, despite limited supportive efficacy data. There are also new topical treatments in various stages of development, designed specifically for use in PE. Treatments reviewed include TEMPE spray, containing a eutectic mixture of the topical anaesthetics lidocaine and prilocaine, and several creams, including one containing natural products (SS-cream), and preliminary results from another containing the local anaesthetic dylonine, with alprostadil (prostaglandin E1). Despite wide variations in the methods of clinical trials, it is possible to conclude that all placebo-controlled studies of topical treatments have reported a significant increase in intravaginal ejaculatory latency time compared to baseline and placebo. Topical treatments for PE are appealing in that they can be applied as needed and only minimal systemic effects are likely. However, without well-controlled drug delivery there is the theoretical possibility of penile hypoaesthesia and/or transvaginal contamination. Unlike the cream formulations, the TEMPE spray has a well-controlled delivery system, making it easy to administer locally, and it appears to be well tolerated in early clinical trials. It appears that topical treatments might be able to satisfy many of the requirements of an ideal treatment for PE, and certainly have the potential for use as a first-line treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".