PGS Publication: PGP000356

Publication Information (EuropePMC)
Title Early prediction of prostate cancer risk in younger men using polygenic risk scores and electronic health records.
PubMed ID 35751453(Europe PMC)
doi 10.1002/cam4.4934
Publication Date June 25, 2022
Journal Cancer Med
Author(s) Varma A, Maharjan J, Garikipati A, Hurtado M, Shokouhi S, Mao Q.
Released in PGS Catalog: Aug. 3, 2022

Associated Polygenic Score(s)

Filter PGS by Participant Ancestry
Individuals included in:
G - Source of Variant Associations (GWAS)
D - Score Development/Training
E - PGS Evaluation
List of ancestries includes:
Display options:
Ancestry legend
Multi-ancestry (including European)
Multi-ancestry (excluding European)
African
East Asian
South Asian
Additional Asian Ancestries
European
Greater Middle Eastern
Hispanic or Latin American
Additional Diverse Ancestries
Not Reported

External PGS Evaluated By This Publication

Polygenic Score ID & Name PGS Publication ID (PGP) Reported Trait Mapped Trait(s) (Ontology) Number of Variants Ancestry distribution Scoring File (FTP Link)
PGS000333
(PRS_PC)
PGP000100 |
Mars N et al. Nat Med (2020)
Prostate cancer prostate carcinoma 6,606,785
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000333/ScoringFiles/PGS000333.txt.gz

Performance Metrics

Disclaimer: The performance metrics are displayed as reported by the source studies. It is important to note that metrics are not necessarily comparable with each other. For example, metrics depend on the sample characteristics (described by the PGS Catalog Sample Set [PSS] ID), phenotyping, and statistical modelling. Please refer to the source publication for additional guidance on performance.

PGS Performance
Metric ID (PPM)
Evaluated Score PGS Sample Set ID
(PSS)
Performance Source Trait PGS Effect Sizes
(per SD change)
Classification Metrics Other Metrics Covariates Included in the Model PGS Performance:
Other Relevant Information
PPM014914 PGS000333
(PRS_PC)
PSS009926|
Multi-ancestry (including European)|
91,106 individuals
PGP000356 |
Varma A et al. Cancer Med (2022)
|Ext.
Reported Trait: Prostate cancer AUROC: 0.788 [0.758, 0.819] Age, father's history, body mass index (BMI), smoking status, glycated hemoglobin, C-reactive protein, insulin-like growth factor 1, number of sex partners, diabetes diagnosis, and diabetes medication

Evaluated Samples

PGS Sample Set ID
(PSS)
Phenotype Definitions and Methods Participant Follow-up Time Sample Numbers Age of Study Participants Sample Ancestry Additional Ancestry Description Cohort(s) Additional Sample/Cohort Information
PSS009926 The ICD-10 code used to define PCa was C61-malignant neoplasm of prostate, and the self-reported cancer code was 1044—prostate cancer.
[
  • 624 cases
  • , 82,384 controls
]
,
100.0 % Male samples
European White UKB
PSS009926 The ICD-10 code used to define PCa was C61-malignant neoplasm of prostate, and the self-reported cancer code was 1044—prostate cancer.
[
  • 37 cases
  • , 2,239 controls
]
,
100.0 % Male samples
African unspecified Black UKB
PSS009926 The ICD-10 code used to define PCa was C61-malignant neoplasm of prostate, and the self-reported cancer code was 1044—prostate cancer.
[
  • 13 cases
  • , 3,377 controls
]
,
100.0 % Male samples
Asian unspecified UKB
PSS009926 The ICD-10 code used to define PCa was C61-malignant neoplasm of prostate, and the self-reported cancer code was 1044—prostate cancer.
[
  • 13 cases
  • , 2,419 controls
]
,
100.0 % Male samples
Not reported UKB