PGS Publication: PGP000389

Publication Information (EuropePMC)
Title PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients.
PubMed ID 36271417(Europe PMC)
doi 10.1186/s13058-022-01567-3
Publication Date Oct. 21, 2022
Journal Breast Cancer Res
Author(s) Giardiello D, Hooning MJ, Hauptmann M, Keeman R, Heemskerk-Gerritsen BAM, Becher H, Blomqvist C, Bojesen SE, Bolla MK, Camp NJ, Czene K, Devilee P, Eccles DM, Fasching PA, Figueroa JD, Flyger H, García-Closas M, Haiman CA, Hamann U, Hopper JL, Jakubowska A, Leeuwen FE, Lindblom A, Lubiński J, Margolin S, Martinez ME, Nevanlinna H, Nevelsteen I, Pelders S, Pharoah PDP, Siesling S, Southey MC, van der Hout AH, van Hest LP, Chang-Claude J, Hall P, Easton DF, Steyerberg EW, Schmidt MK.
Released in PGS Catalog: Nov. 7, 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
GWAS
Dev
Eval
 Scoring File (FTP Link)
PGS000004
(PRS313_BC)
 PGP000002 |
Mavaddat N et al. Am J Hum Genet (2018)
 Breast cancer breast carcinoma 313
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000004/ScoringFiles/PGS000004.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
PPM015579 PGS000004
(PRS313_BC)
 PSS009990|
Multi-ancestry (including European)|
207,510 individuals
 PGP000389 |
Giardiello D et al. Breast Cancer Res (2022)
|Ext.		 Reported Trait: Contralateral breast cancer — — Subdistributional hazard ratio (sHR, 75th vs. 25th quartile): 1.35 [1.31, 1.39] PredictCBC-2.0A Calculated with PredictCBC-2.0A

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
PSS009990 — — 207,510 individuals,
0.0 % Male samples
 — European, Asian unspecified European and Asian 20 cohorts
  • ABCFS
  • ,ABCS
  • ,BBCC
  • ,BREOGAN
  • ,CGPS
  • ,EMC
  • ,HEBCS
  • ,HEBON
  • ,KARBAC
  • ,KARMA
  • ,LMBC
  • ,MARIE
  • ,MEC
  • ,ORIGO
  • ,PBCS
  • ,POSH
  • ,SEARCH
  • ,SKKDKFZS
  • ,SZBCS
  • ,pKARMA
 BOSOM, NKR, UBCS