ArticleJNCI cancer spectrum2021
Metrics for Evaluating Polygenic Risk Scores.
Article in JNCI cancer spectrum, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Polygenic Prediction of Type 2 Diabetes in Africa.Diabetes care · 2022Pooled it
- Angiographic Burden of Coronary Atherosclerosis Partially Mediates the Association Between ASCVD Risk Factors and Outcomes.Circulation. Genomic and precision medicine · 2026Article
- Sharing approaches in predictive genomics across animals, plants and humans.Nature genetics · 2026Review
- Validity of European-centric cardiometabolic polygenic scores in multi-ancestry populations.European journal of human genetics : EJHG · 2024Article
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
There is growing interest in the use of polygenic risk scores based on genetic variants to predict cancer incidence. The type of metric used to evaluate the predictive performance of polygenic risk scores plays a crucial role in their interpretation. I compare 3 metrics for this evaluation: the area under the receiver operating characteristic curve (AUC), the probability of cancer in a high-risk subset divided by the prevalence of cancer in the population, which I call the subset relative risk (SRR), and the minimum test tradeoff, which is the minimum number of genetic variant ascertainments (one per person) for each correct prediction of cancer to yield a positive expected clinical utility. I show that SRR is a relabeling of AUC. I recommend the minimum test tradeoff for the evaluation of polygenic risk scores because, unlike AUC and SRR, it is directly related to the expected clinical utility.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.