
pmid: 35152271
pmc: PMC9372232
handle: 10230/54443 , 10852/98287 , 1854/LU-01HY11235RXA40PZKBEAP18GAP , 11343/301480
pmid: 35152271
pmc: PMC9372232
handle: 10230/54443 , 10852/98287 , 1854/LU-01HY11235RXA40PZKBEAP18GAP , 11343/301480
AbstractBackgroundProstate cancer risk stratification using single-nucleotide polymorphisms (SNPs) demonstrates considerable promise in men of European, Asian, and African genetic ancestries, but there is still need for increased accuracy. We evaluated whether including additional SNPs in a prostate cancer polygenic hazard score (PHS) would improve associations with clinically significant prostate cancer in multi-ancestry datasets.MethodsIn total, 299 SNPs previously associated with prostate cancer were evaluated for inclusion in a new PHS, using a LASSO-regularized Cox proportional hazards model in a training dataset of 72,181 men from the PRACTICAL Consortium. The PHS model was evaluated in four testing datasets: African ancestry, Asian ancestry, and two of European Ancestry—the Cohort of Swedish Men (COSM) and the ProtecT study. Hazard ratios (HRs) were estimated to compare men with high versus low PHS for association with clinically significant, with any, and with fatal prostate cancer. The impact of genetic risk stratification on the positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was also measured.ResultsThe final model (PHS290) had 290 SNPs with non-zero coefficients. Comparing, for example, the highest and lowest quintiles of PHS290, the hazard ratios (HRs) for clinically significant prostate cancer were 13.73 [95% CI: 12.43–15.16] in ProtecT, 7.07 [6.58–7.60] in African ancestry, 10.31 [9.58–11.11] in Asian ancestry, and 11.18 [10.34–12.09] in COSM. Similar results were seen for association with any and fatal prostate cancer. Without PHS stratification, the PPV of PSA testing for clinically significant prostate cancer in ProtecT was 0.12 (0.11–0.14). For the top 20% and top 5% of PHS290, the PPV of PSA testing was 0.19 (0.15–0.22) and 0.26 (0.19–0.33), respectively.ConclusionsWe demonstrate better genetic risk stratification for clinically significant prostate cancer than prior versions of PHS in multi-ancestry datasets. This is promising for implementing precision-medicine approaches to prostate cancer screening decisions in diverse populations.
SELECTION, Male, Aging, [SDV]Life Sciences [q-bio], Clinical sciences, LASSO, MESH: Risk Assessment, UKGPCS collaborators, MESH: Risk Factors, Risk Factors, multi-ancestry datasets, Medicine and Health Sciences, PRACTICAL Consortium, Minority Health, Precision Medicine, Cancer genetics, Early Detection of Cancer, Cancer, Prostatic Neoplasms/diagnosis, Manchester Cancer Research Centre, Prostate Cancer, MESH: Genetic Predisposition to Disease, APCB, Single Nucleotide, Urology & Nephrology, Prostate-Specific Antigen/genetics, prostate cancer, MESH: Prostate-Specific Antigen, Health Disparities, [SDV] Life Sciences [q-bio], Oncology, Life Sciences & Biomedicine, Urologic Diseases, Clinical Sciences, Oncology and Carcinogenesis, 610, The Profile Study Steering Committee, -, Polymorphism, Single Nucleotide, Risk Assessment, Article, Cancer screening, APCB (Australian Prostate Cancer BioResource), Cancer epidemiology, SDG 3 - Good Health and Well-being, NC-LA PCaP Investigators, 3211 Oncology and carcinogenesis, Genetics, MESH: Early Detection of Cancer, Humans, 1112 Oncology and Carcinogenesis, Genetic Predisposition to Disease, Polymorphism, MESH: Polymorphism, prostate cancer ; multi-ancestry datasets, Cancer och onkologi, Canary PASS Investigators, MESH: Humans, Science & Technology, Biomedical and Clinical Sciences, IMPACT Study Steering Committee and Collaborators, RC0254 Neoplasms. Tumors. Oncology (including Cancer), Profile Study Steering Committee, Prevention, 3202 Clinical sciences, Prostatic Neoplasms, Oncology and carcinogenesis, Prostate-Specific Antigen, MESH: Male, ResearchInstitutes_Networks_Beacons/mcrc; name=Manchester Cancer Research Centre, Good Health and Well Being, MESH: Prostatic Neoplasms, Cancer and Oncology, The PRACTICAL Consortium, The IMPACT Study Steering Committee and Collaborators
SELECTION, Male, Aging, [SDV]Life Sciences [q-bio], Clinical sciences, LASSO, MESH: Risk Assessment, UKGPCS collaborators, MESH: Risk Factors, Risk Factors, multi-ancestry datasets, Medicine and Health Sciences, PRACTICAL Consortium, Minority Health, Precision Medicine, Cancer genetics, Early Detection of Cancer, Cancer, Prostatic Neoplasms/diagnosis, Manchester Cancer Research Centre, Prostate Cancer, MESH: Genetic Predisposition to Disease, APCB, Single Nucleotide, Urology & Nephrology, Prostate-Specific Antigen/genetics, prostate cancer, MESH: Prostate-Specific Antigen, Health Disparities, [SDV] Life Sciences [q-bio], Oncology, Life Sciences & Biomedicine, Urologic Diseases, Clinical Sciences, Oncology and Carcinogenesis, 610, The Profile Study Steering Committee, -, Polymorphism, Single Nucleotide, Risk Assessment, Article, Cancer screening, APCB (Australian Prostate Cancer BioResource), Cancer epidemiology, SDG 3 - Good Health and Well-being, NC-LA PCaP Investigators, 3211 Oncology and carcinogenesis, Genetics, MESH: Early Detection of Cancer, Humans, 1112 Oncology and Carcinogenesis, Genetic Predisposition to Disease, Polymorphism, MESH: Polymorphism, prostate cancer ; multi-ancestry datasets, Cancer och onkologi, Canary PASS Investigators, MESH: Humans, Science & Technology, Biomedical and Clinical Sciences, IMPACT Study Steering Committee and Collaborators, RC0254 Neoplasms. Tumors. Oncology (including Cancer), Profile Study Steering Committee, Prevention, 3202 Clinical sciences, Prostatic Neoplasms, Oncology and carcinogenesis, Prostate-Specific Antigen, MESH: Male, ResearchInstitutes_Networks_Beacons/mcrc; name=Manchester Cancer Research Centre, Good Health and Well Being, MESH: Prostatic Neoplasms, Cancer and Oncology, The PRACTICAL Consortium, The IMPACT Study Steering Committee and Collaborators
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 23 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
