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

Clinical decision rules Prevalence Prostatitis Surveys and questionnaires Undiagnosed diseases

Journal

World journal of urology
ISSN: 1433-8726
Titre abrégé: World J Urol
Pays: Germany
ID NLM: 8307716

Informations de publication

Date de publication:
Oct 2023
Historique:
received: 04 07 2023
accepted: 10 08 2023
medline: 23 10 2023
pubmed: 15 9 2023
entrez: 15 9 2023
Statut: ppublish

Résumé

We developed a simple self-checkable screening tool for chronic prostatitis (S-CP) and internally validated it to encourage men (in the general population) with possible chronic prostatitis to consult urologists. The expert panel proposed the S-CP, which comprises three domains: Area of pain or discomfort (6 components), accompanying Symptom (6 components), and Trigger for symptom flares (4 components). We employed logistic regression to predict chronic prostatitis prevalence with the S-CP. We evaluated the predictive performance using data from a representative national survey of Japanese men aged 20 to 84. We calculated the optimism-adjusted area under the curve using bootstrapping. We assessed sensitivity/specificity, likelihood ratio, and predictive value for each cutoff of the S-CP. Data were collected for 5,010 men-71 (1.4%) had a chronic prostatitis diagnosis. The apparent and adjusted area under the curve for the S-CP was 0.765 [95% confidence interval (CI) 0.702, 0.829] and 0.761 (0.696, 0.819), respectively. When the cutoff was two of the three domains being positive, sensitivity and specificity were 62.0% (95% CI 49.7, 73.2) and 85.4% (95% CI 84.4, 86.4), respectively. The positive/negative likelihood ratios were 4.2 (95% CI 3.5, 5.2) and 0.45 (95% CI 0.33, 0.60), respectively. The positive/negative predictive values were 5.7 (95% CI 4.2, 7.6) and 99.4 (95% CI 99.1, 99.6), respectively. The reasonable predictive performance of the S-CP indicated that patients (in the general population) with chronic prostatitis were screened as a first step. Further research would develop another tool for diagnostic support in actual clinical settings.

Identifiants

pubmed: 37712967
doi: 10.1007/s00345-023-04574-x
pii: 10.1007/s00345-023-04574-x
pmc: PMC10582131
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2759-2765

Informations de copyright

© 2023. The Author(s).

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Auteurs

Yoichiro Tohi (Y)

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

Yasukazu Hijikata (Y)

Department of Healthcare Epidemiology, School of Public Health in the Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Section of Clinical Epidemiology, Department of Community Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.

Mikio Sugimoto (M)

Department of Urology, Faculty of Medicine, Kagawa University, 1750-1, Ikenobe, Miki-Cho, Kita-Gun, Kagawa, 761-0701, Japan. sugimoto.mikio@kagawa-u.ac.jp.

Hideya Kuroda (H)

Kuroda Urology Clinic, Osaka, Japan.

Mineo Takei (M)

Department of Urology, Harasanshin General Hospital, Fukuoka, Japan.

Takakazu Matsuki (T)

Matsuki Urology Clinic, Kagawa, Japan.

Tsukasa Kamitani (T)

Section of Education for Clinical Research, Kyoto University Hospital, Kyoto, Japan.

Yoshiyuki Kakehi (Y)

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

Shunichi Fukuhara (S)

Section of Clinical Epidemiology, Department of Community Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.
Shirakawa STAR for General Medicine, Fukushima Medical University, Fukushima, Japan.

Yosuke Yamamoto (Y)

Department of Healthcare Epidemiology, School of Public Health in the Graduate School of Medicine, Kyoto University, Kyoto, Japan.

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