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European Society of Sexual Medicine consensus statement on the use of animal models for studying Peyronie’s disease

Fabio Castiglione, Ömer Onur Çakır, Nicolò Schifano, Giovanni Corona, Yacov Reisman, Carlo Bettocchi, Selim Cellek, Marcus Maximillian Ilg

Sexual Medicine, 2023

7 citations

Abstract

Introduction: Animal models are frequently used for translational research in Peyronie's disease (PD). However, due to lack of availability of guidelines, there is some heterogeneity in study design, data reporting, and outcome measures. Aim: This European Society for Sexual Medicine consensus statement aims to provide guidance in utilization of animal models in PD research in a standardized and uniform fashion. Methods: PubMed was searched for studies using animal models for PD. The following search terms were used: ("Peyronie's disease" OR "penile fibrosis" OR "penile curvature" OR "induration penis plastica" OR "erectile dysfunction") AND ("rodent" OR "mouse" OR "mice" OR "rat" OR "rabbit"). Outcomes: This European Society for Sexual Medicine statement describes best practice guidelines for utilization of animals in PD research: power calculation, details of available models, surgical procedures, and measurement techniques, while highlighting possible pitfalls and translational limitations of the models. Results: In total, 2490 studies were retrieved and 2446 articles were excluded. A total of 44 studies were included, of which 40 studies used rats, 1 study used both rats and mice, 1 study used a genetic mouse model, and 2 studies used rabbits. A significant number of the studies (70.5%) used transforming growth factor β 1 for induction of fibrosis. Oxford 2011 Levels of Evidence criteria could not be applied due to the nature of the studies. Conclusion: Despite certain…

How strong is the evidence?

Evidence Hub reads this as a guideline, done in animal, not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.

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