Effect of green tea catechins in patients with high-grade prostatic intraepithelial neoplasia: Results of a short-term double-blind placebo controlled phase II clinical trial
AbstractBackground and study objective: Several studies suggest a protective role of green tea catechins against prostate cancer (PCa). In order to evaluate the efficacy of green tea catechins for chemoprevention of PCa in patients with high-grade prostate intraepithelial neoplasia (HG-PIN) we performed a phase II clinical trial. Methods: Sixty volunteers with HG-PIN were enrolled to carry out a double-blind randomized placebo-controlled phase II clinical trial. Treated group took daily 600 mg of green tea catechins (Categ Plus®) for 1 year. Patients were screened at 6 and 12 months through prostatic biopsy and measurements of prostate-specific antigen (PSA). Results: Despite the statistically significant reduction of PSA observed in subjects who received green tea catechins for 6 and 12 months, we did not find any statistical difference in PCa incidence between the experimental groups neither after 6 nor after 12 months. However, throughout the one-year follow- up we observed very limited adverse effects induced by green tea catechins and a not significant improvement in lower urinary tract symptoms and quality of life. Conclusions: Although the small number of patients enrolled in our study and the relatively short duration of intervention, our findings seems to deny the efficacy of green tea catechins. However, results of our clinical study, mainly for its low statistical strength, suggest that the effectiveness of green tea catechins should be evaluated in both a larger cohort of men and longer trial.
PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.
- Abstract views: 1258
- PDF: 628
Copyright (c) 2017 Michele Navarra
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.