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Development and internal validation of a screening tool for chronic prostatitis (S-CP).

Yoichiro Tohi1, Yasukazu Hijikata2,3, Mikio Sugimoto4

  • 1Department of Urology, Faculty of Medicine, Kagawa University, 1750-1, Ikenobe, Miki-Cho, Kita-Gun, Kagawa, 761-0701, Japan.

World Journal of Urology
|September 15, 2023
PubMed
Summary

A new self-checkable screening tool for chronic prostatitis (S-CP) was developed and validated. This tool helps men with potential chronic prostatitis symptoms consult urologists for early diagnosis and management.

Keywords:
Clinical decision rulesPrevalenceProstatitisSurveys and questionnairesUndiagnosed diseases

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Area of Science:

  • Urology
  • Public Health
  • Diagnostic Tool Development

Background:

  • Chronic prostatitis affects a significant number of men, often leading to delayed diagnosis and treatment.
  • A simple, accessible screening method is needed to encourage early consultation with urologists.

Purpose of the Study:

  • To develop and validate a simple self-checkable screening tool for chronic prostatitis (S-CP).
  • To encourage men with potential chronic prostatitis symptoms to seek professional medical advice.

Main Methods:

  • An expert panel developed the S-CP tool with three domains: pain, accompanying symptoms, and triggers.
  • Logistic regression was used to predict chronic prostatitis prevalence based on S-CP scores.
  • The tool's predictive performance was evaluated using data from a national survey of Japanese men aged 20-84.

Main Results:

  • The S-CP demonstrated an optimism-adjusted area under the curve of 0.761, indicating reasonable predictive performance.
  • With a cutoff of two positive domains, the S-CP achieved 62.0% sensitivity and 85.4% specificity.
  • Positive and negative likelihood ratios were 4.2 and 0.45, respectively, with high negative predictive value (99.4%).

Conclusions:

  • The S-CP shows promise as a first-step screening tool for identifying individuals with chronic prostatitis in the general population.
  • Further research is recommended to develop diagnostic support tools for clinical settings.