A big data-based prediction model for prostate cancer incidence in Japanese men

Sci Rep. 2023 Apr 21;13(1):6579. doi: 10.1038/s41598-023-33725-8.


To define a normal range for PSA values (ng/mL) by age and create a prediction model for prostate cancer incidence. We conducted a retrospective analysis using 263,073 observations of PSA values in Japanese men aged 18-98 years (2007-2017), including healthy men and those diagnosed with prostate cancer. Percentiles for 262,639 PSA observations in healthy men aged 18-70 years were calculated and plotted to elucidate the normal fluctuation range for PSA values by age. Univariable and multivariable logistic regression analyses were performed to develop a predictive model for prostate cancer incidence. PSA levels and PSA velocity increased with age in healthy men. However, there was no difference in PSA velocity with age in men diagnosed with prostate cancer. Logistic regression analysis showed an increased risk of prostate cancer for PSA slopes ranging from 0.5 to 3.5 ng/mL/year. This study provides age-specific normal fluctuation ranges for PSA levels in men aged 18-75 years and presents a novel and personalized prediction model for prostate cancer incidence. We found that PSA slope values of > 3.5 ng/mL/year may indicate a rapid increase in PSA levels caused by pathological condition such as inflammation but are unlikely to indicate cancer risk.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Big Data*
  • Biomarkers, Tumor / blood
  • East Asian People*
  • Humans
  • Incidence
  • Japan / epidemiology
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Prostate-Specific Antigen* / blood
  • Prostatic Neoplasms* / blood
  • Prostatic Neoplasms* / epidemiology
  • Reference Values
  • Retrospective Studies
  • Risk Assessment
  • Risk Factors
  • Young Adult


  • Prostate-Specific Antigen
  • Biomarkers, Tumor