PGS Publication: PGP000518

Publication Information (EuropePMC)
Title Development and evaluation of a polygenic risk score for lung cancer in never-smoking women: A large-scale prospective Chinese cohort study.
PubMed ID 37846649(Europe PMC)
doi 10.1002/ijc.34765
Publication Date Oct. 17, 2023
Journal Int J Cancer
Author(s) Wei X, Sun D, Gao J, Zhang J, Zhu M, Yu C, Ma Z, Fu Y, Ji C, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Jin G, Chen Z, Hu Z, Li L, Shen H, Lv J, Ma H.
Released in PGS Catalog: Dec. 15, 2023

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:
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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

PGS Developed 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)
PGS004164
(PRS16_LC)
 PGP000518 |
Wei X et al. Int J Cancer (2023)
 Lung cancer in never smokers lung carcinoma,
smoking status measurement		 16
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004164/ScoringFiles/PGS004164.txt.gz
PGS004165
(PRS21_LC)
 PGP000518 |
Wei X et al. Int J Cancer (2023)
 Lung cancer lung carcinoma 21
-
 https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004165/ScoringFiles/PGS004165.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
PPM020096 PGS004165
(PRS21_LC)
 PSS011294|
East Asian Ancestry|
55,266 individuals
 PGP000518 |
Wei X et al. Int J Cancer (2023)
 Reported Trait: Lung cancer in never smokers HR: 1.29 [1.18, 1.41] — — age, education, BMI, COPD history, personal history of cancer, family history of cancer, and the first 10 principal components of ancestry —
PPM020097 PGS004165
(PRS21_LC)
 PSS011294|
East Asian Ancestry|
55,266 individuals
 PGP000518 |
Wei X et al. Int J Cancer (2023)
 Reported Trait: Incident lung cancer in never smokers — — Hazard ratio (HR, high vs low risk): 2.09 [1.56, 2.8] age, first 10 principal components of ancestry, MI, education, COPD history, personal history of cancer and family history of cancer —
PPM020095 PGS004164
(PRS16_LC)
 PSS011294|
East Asian Ancestry|
55,266 individuals
 PGP000518 |
Wei X et al. Int J Cancer (2023)
 Reported Trait: Lung cancer in never smokers HR: 1.28 [1.17, 1.4] — — age, education, BMI, COPD history, personal history of cancer, family history of cancer, and the first 10 principal components of ancestry —

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
PSS011294 — — 55,266 individuals,
0.0 % Male samples
 — East Asian — CKB —