Title |
Even modest prediction accuracy of genomic models can have large clinical utility
|
---|---|
Published in |
Frontiers in Genetics, November 2014
|
DOI | 10.3389/fgene.2014.00417 |
Pubmed ID | |
Authors |
Emily J. Dhurandhar, Ana I. Vazquez, George A. Argyropoulos, David B. Allison |
Abstract |
Whole Genome Prediction (WGP) jointly fits thousands of SNPs into a regression model to yield estimates for the contribution of markers to the overall variance of a particular trait, and for their associations with that trait. To date, WGP has offered only modest prediction accuracy, but in some cases even modest prediction accuracy may be useful. We provide an illustration of this using a theoretical simulation that used WGP to predict weight loss after bariatric surgery with moderate accuracy (R (2) = 0.07) to assess the clinical utility of WGP despite these limitations. Prevention of Type 2 Diabetes (T2DM) post-surgery was considered the major outcome. Treating only patients above predefined threshold of predicted weight loss in our simulation, in the realistic context of finite resources for the surgery, significantly reduced lifetime risk of T2DM in the treatable population by selecting those most likely to succeed. Thus, our example illustrates how WGP may be clinically useful in some situations, and even with moderate accuracy, may provide a clear path for turning personalized medicine from theory to reality. |
X Demographics
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 33% |
United Kingdom | 1 | 17% |
Unknown | 3 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 50% |
Scientists | 1 | 17% |
Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 28 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 7 | 25% |
Student > Bachelor | 4 | 14% |
Student > Doctoral Student | 3 | 11% |
Student > Ph. D. Student | 3 | 11% |
Student > Master | 2 | 7% |
Other | 4 | 14% |
Unknown | 5 | 18% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 9 | 32% |
Agricultural and Biological Sciences | 7 | 25% |
Pharmacology, Toxicology and Pharmaceutical Science | 2 | 7% |
Engineering | 2 | 7% |
Economics, Econometrics and Finance | 1 | 4% |
Other | 1 | 4% |
Unknown | 6 | 21% |