ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2025
Variation in PSA Levels by Age, Adiposity, Race and Ethnicity, and Genetic Risk: Implications for Prostate Cancer Screening.
Kevin H Kensler, Shakuntala Baichoo, Mathias Nuris-Souquet, Faith Morley, Michelle Lee-Bravatti, Pranoti Pradhan, Charlotte Roscoe, Barbra A Dickerman, Hari S Iyer, Timothy R Rebbeck
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In one paragraphArticle in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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2 · The registryThe trial behind it
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4 · The recordCorrections and comments
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5 · Who and what moneyAuthors and funding
10 authors.
Kevin H KenslerDepartment of Population Health Sciences, Weill Cornell Medicine, New York, New York.ORCID 0000-0001-7515-7270 Mathias Nuris-SouquetSchool of Life Sciences, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland.ORCID 0009-0001-7952-3079 Michelle Lee-BravattiDivision of Population Sciences, Dana Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0002-3991-7014 Pranoti PradhanDivision of Population Sciences, Dana Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0002-6423-0484 Charlotte RoscoeEnvironmental Systems and Human Health, Oregon Health & Science University, Portland, Oregon.ORCID 0000-0002-9169-6458 Barbra A DickermanDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.ORCID 0000-0003-2843-687X Hari S IyerSection of Cancer Epidemiology and Health Outcomes, Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey.ORCID 0000-0002-7596-9049 Timothy R RebbeckDivision of Population Sciences, Dana Farber Cancer Institute, Boston, Massachusetts.ORCID 0000-0002-4799-1900 Funding
Technology to Empower Changes in Health (TECH) Network Participant Technologies CenterU24OD023176 · OD · SCRIPPS RESEARCH INSTITUTE, THE · PI TOPOL, ERIC JEFFREY · 2016 to 2022
$204.7MPrecision Medicine Initiative Cohort Program BiobankU24OD023121 · OD · MAYO CLINIC ROCHESTER · PI CEKANOVA, MARIA, CICEK, MINE · 2016 to 2024
$185.5MEnhancing All of Us Data Resources for Nutrition Precision Health: the All of Us Data and Research CenterU2COD023196 · OD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GLAZER, DAVID, HARRIS, PAUL A. · 2016 to 2022
$143.7MAdaptive Platform for Personalized EngagementU24OD023163 · OD · VIGNET, INC. · PI JAIN, PRADUMAN · 2017 to 2020
$102.6MUniversity of Arizona-Banner Health All of Us Research Program OT2OD026549 · OD · UNIVERSITY OF ARIZONA · PI MORENO, FRANCISCO A, REIMAN, ERIC MICHAEL · 2018 to 2023
$78.9MCalifornia Precision Medicine Research Program ConsortiumOT2OD026552 · OD · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANTON-CULVER, HODA A, OHNO-MACHADO, LUCILA · 2018 to 2023
$73.4MAll of Us PennsylvaniaOT2OD026554 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E, VISWESWARAN, SHYAM · 2018 to 2023
$72.1MNew York City Consortium for Precision MedicineOT2OD026556 · OD · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BIER, LOUISE E, GHARAVI, ALI G · 2018 to 2023
$67.3MSouthEast Enrollment Center (SEEC) OT2OD026551 · OD · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI CARRASQUILLO, OLVEEN, COLON, VIVIAN · 2018 to 2023
$62.8MSouthern All of Us NetworkOT2OD026548 · OD · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI FOUAD, MONA N., KORF, BRUCE R · 2018 to 2023
$60.5MIllinois Precision Medicine Consortium OT2OD026557 · OD · NORTHWESTERN UNIVERSITY AT CHICAGO · PI AHSAN, HABIBUL, ARGOS, MARIA · 2018 to 2023
$60.5MThe New England Precision Medicine Consortium of the All of Us Research ProgramOT2OD026553 · OD · MASSACHUSETTS GENERAL HOSPITAL · PI CLARK, CHERYL RENEE, KARLSON, ELIZABETH W · 2018 to 2023
$58.8MNational Cancer Institute (NCI) P20CA233255National Cancer Institute (NCI) R00CA245900National Cancer Institute (NCI) R00CA248335National Institute of Environmental Health Sciences (DEHS) K01ES035734NCI NIH HHS P20 CA233255NCI NIH HHS R00 CA245900NCI NIH HHS R00 CA248335NIEHS NIH HHS K01 ES035734NIH HHS OT2 OD023205NIH HHS OT2 OD023206NIH HHS OT2 OD025276NIH HHS OT2 OD025277NIH HHS OT2 OD025315NIH HHS OT2 OD025337NIH HHS OT2 OD026548NIH HHS OT2 OD026549NIH HHS OT2 OD026550NIH HHS OT2 OD026551NIH HHS OT2 OD026552NIH HHS OT2 OD026553NIH HHS OT2 OD026554NIH HHS OT2 OD026555NIH HHS OT2 OD026556NIH HHS OT2 OD026557NIH HHS U24 OD023121NIH HHS U24 OD023163NIH HHS U24 OD023176NIH HHS U2C OD023196Prostate Cancer UK (ProstateUK)
6 · The paper itselfAbstract
backgroundThe benefit-to-harm ratio of PSA-based prostate cancer screening may be improved through implementation of PSA reference ranges that consider innate individual characteristics. We evaluated variation in PSA levels by factors that may influence PSA levels among men eligible to undergo prostate cancer screening.
methodsWe identified men ages 40 to 79 years in the All of Us Research Program who had no history of prostate cancer or elevated PSA at cohort enrollment. PSA distributions were compared across age groups, self-identified race or ethnicity (SIRE), body mass index (BMI), polygenic risk score (PRS) for prostate cancer risk, and PRS for PSA level. Multivariable associations between these factors and PSA percentiles were evaluated using quantile regression.
resultsAmong 13,749 eligible men, 95th percentiles (p95) of PSA values increased with age (40-49 years: 1.81 ng/mL, 50-59 years: 3.23 ng/mL, 60-69 years: 4.15 ng/mL, and 70-79 years: 5.53 ng/mL). p95 of PSA was 0.83 ng/mL lower [95% confidence interval (CI), 0.44-0.1.22] among participants with BMI 35 to 39 kg/m2 versus <25 kg/m2. p95 of PSA was 2.32 ng/mL higher (95% CI, 1.20-3.44) among those with PRS for prostate cancer >90th percentile versus ≤50th percentile and 1.21 ng/mL higher (95% CI, 0.50-1.92) among males with PRS for PSA >90th percentile versus ≤50th percentile. SIRE was not consistently associated with PSA levels.
conclusionsPSA levels vary by age, BMI, and PRS but not SIRE. Further work is needed to understand how tailoring PSA reference ranges based on these characteristics would affect screening outcomes. IMPACT: Consideration of factors that endogenously influence PSA levels may lead to improved benefit-to-harm ratios of prostate cancer screening.
Indexed as
AdiposityEarly Detection of CancerProstate-Specific AntigenProstatic NeoplasmsAdultAgedAge FactorsBody Mass IndexGenetic Predisposition to DiseaseHumansMaleMiddle AgedRisk FactorsProstate-Specific Antigen
Identifiers
PMID40178947
PMCPMC12133409
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