A big data-based prediction model for prostate cancer incidence in Japanese men.
Sci Rep
; 13(1): 6579, 2023 04 21.
Article
en En
| MEDLINE
| ID: mdl-37085532
ABSTRACT
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.
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Neoplasias de la Próstata
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Antígeno Prostático Específico
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Macrodatos
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Pueblos del Este de Asia
Tipo de estudio:
Etiology_studies
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Incidence_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
País/Región como asunto:
Asia
Idioma:
En
Revista:
Sci Rep
Año:
2023
Tipo del documento:
Article