The effect of sample size on polygenic hazard models for prostate cancer
Roshan A. Karunamuni,
Chun C. Fan,
Rosalind A. Eeles,
Douglas F. Easton,
Ali Amin Al Olama,
Sara Benlloch Garcia,
Teuvo LJ Tammela,
Børge G Nordestgaard,
Tim J. Key,
Ruth C. Travis,
David E Neal,
Jenny L. Donovan,
Freddie C. Hamdy,
Paul DP Pharoah,
Stephen N Thibodeau,
Shannon K. McDonnell,
Daniel J Schaid,
Adam S. Kibel,
Jong Y. Park,
Thomas A Sellers,
Judith A. Clements,
Australian Prostate Cancer BioResource (APCB),
Manuel R. Teixeira,
Ian G. Mills,
Ole A Andreassen,
Anders M. Dale,
Tyler M Seibert,
The PRACTICAL Consortium
Posted 21 Jun 2019
bioRxiv DOI: 10.1101/679092 (published DOI: 10.1038/s41431-020-0664-2)
Posted 21 Jun 2019
We aimed to determine the effect of sample size on performance of polygenic hazard score (PHS) models in predicting the age at onset of prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training (34,444 samples) and testing (6,417 samples) sets. Two PHS model-building strategies were investigated. Established-SNP model considered 65 SNPs that had been associated with prostate cancer in the literature. A stepwise SNP selection was used to develop Discovery-SNP models. The performance of each PHS model was calculated for random sizes of the training set (1 to 30 thousand). The performance of a representative Established-SNP model was estimated for random sizes of the testing set (0.5 to 6 thousand). Mean HR98/50 (hazard ratio of top 2% to the average in the test set) of the Established-SNP model increased from 1.73[95%CI: 1.69-1.77] to 2.41[2.40-2.43] when the number of training samples was increased from 1 to 30 thousand. The corresponding HR98/50 of the Discovery-SNP model increased from 1.05[0.93-1.18] to 2.19[2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 and 6 thousand observations were 1.78[1.70-1.85] and 1.73[1.71-1.76], respectively. We estimate that a study population of 20 to 30 thousand men is required to develop Discovery-SNP PHS models for prostate cancer. The required sample size could be reduced to 10 thousand samples, if a set of SNPs associated with the disease has already been established.
- Downloaded 214 times
- Download rankings, all-time:
- Site-wide: 75,001 out of 100,737
- In genetics: 3,969 out of 5,016
- Year to date:
- Site-wide: 78,984 out of 100,737
- Since beginning of last month:
- Site-wide: None out of 100,737
Downloads over time
Distribution of downloads per paper, site-wide
- 20 Oct 2020: Support for sorting preprints using Twitter activity has been removed, at least temporarily, until a new source of social media activity data becomes available.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!