| Predicted Trait | |
| Reported Trait | Prostate cancer |
| Mapped Trait(s) | prostate cancer (MONDO_0008315) |
| Score Construction | |
| PGS Name | PRState_Trans |
| Development Method | |
| Name | Genome-wide significant SNPs |
| Parameters | p<5e-08, r2=0.1 |
| Variants | |
| Original Genome Build | GRCh37 |
| Number of Variants | 14 |
| Effect Weight Type | beta |
| PGS Source | |
| PGS Catalog Publication (PGP) ID | PGP000430 |
| Citation (link to publication) | Pagadala MS et al. BMC Cancer (2022) |
| Ancestry Distribution | |
| Source of Variant Associations (GWAS) | European: 54.3% African: 45.7% 9,926 individuals (100%) |
| PGS Evaluation | African: 100% 1 Sample Sets |
| Study Identifiers | Sample Numbers | Sample Ancestry | Cohort(s) |
|---|---|---|---|
| — | 5,393 individuals, 100.0 % Male samples |
European | ELLIPSE |
| — | 4,533 individuals, 100.0 % Male samples |
African unspecified | ELLIPSE |
|
PGS Performance Metric ID (PPM) |
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 |
|---|---|---|---|---|---|---|---|---|
| PPM017072 | PSS010114| African Ancestry| 4,533 individuals |
PGP000430 | Pagadala MS et al. BMC Cancer (2022) |
Reported Trait: Prostate cancer | — | AUROC: 0.66 [0.65, 0.68] | — | genetics, age and family history | — |
|
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 |
|---|---|---|---|---|---|---|---|---|
| PSS010114 | — | — | 4,533 individuals, 100.0 % Male samples |
— | African unspecified | — | ELLIPSE | — |