- Study Reveals Troubling Statistics
- Concerns Over False Positives
- Experts Question Genetic Testing Utility
A major study found that genetic tests that purport to predict the risk of diseases like cancer and heart disease miss nine out of ten cases.
An examination of polygenic risk scores, which estimate an individual’s susceptibility to health conditions based on genetic variations, revealed that they “performed inadequately” in case identification.
A false positive rate of one in twenty was also observed, wherein an individual was erroneously diagnosed with a disease, resulting in concern and the possibility of unwarranted testing and treatment.
Physicians cautioned that negative results may misleadingly reassure patients.
Frequently, people hail commercially available tests as a paradigm shift in the prognosis and prevention of prevalent illnesses.
However, according to an analysis of 926 polygenic risk scores for 310 diseases conducted by researchers from University College London. Only 11% of those who ultimately developed the disease were identified on average.
Medical professionals detected only 10 percent of actual instances of breast cancer and 12 percent of cases of coronary artery disease, the primary cause of myocardial infarction and cerebrovascular accidents.
Concurrently, they erroneously predicted that 5% of the population would contract a disease when in fact this did not occur; this error could have far-reaching consequences for the health service.
The tests, if utilised extensively, such as in a nationwide screening initiative, would generate a greater number of false positives than genuine positives, according to experts.
The study’s leader, Professor Aroon Hingorani of the UCL Institute of Cardiovascular Science, stated that substantial claims have been made regarding the medical potential of polygenic risk scores.
He stated, “Our research indicates that this is not justified.”
“When held to the same standards as other medical tests, polygenic risk scores performed inadequately for prediction and screening of a variety of common diseases,” we discovered.
“Based on the evidence we’ve reviewed, we cannot justify the use of these screening tests.”
“In many of these conditions, such as heart disease, where safe and effective preventative treatments like lifestyle modifications, lifestyle choices, in addition to blood pressure-lowering medications and statins are available, we could achieve more by implementing them more broadly.” Researchers also compared polygenic risk scores to standard screening approaches.
They determined that several thousand individuals would require a polygenic risk score in addition to conventional risk factors in order to receive statin prescription guidance and prevent an additional myocardial infarction or stroke.
It would be simpler and more effective to prevent heart attacks and strokes without the need for genetic testing, according to them, to prescribe statins based solely on age.
Including these risk scores in the initial screening process to determine mammogram priority would fail to detect the majority of women who subsequently develop the disease.
Additionally, it would produce a substantial number of false positives, which would place additional strain on healthcare systems, as demonstrated in the research published in BMJ Medicine.
Co-author Professor Sir Nicholas Wald, affiliated with the UCL Institute of Health Informatics, expressed that although there have been proposals to implement polygenic risk scores in the early stages for aiding in the prevention of heart disease and breast cancer, our analysis of such cases revealed that they added complexity and cost with minimal health benefits.
According to Dr. Jasmine Gratton of the UCL Institute of Cardiovascular Science, the prevalence of polygenic risk scores has increased since they became available for online purchase by both patients and businesses.
She stated, “Genotyping is now inexpensive, performed only once, and is applicable to all diseases; it is also appealing because an individual’s genotype remains constant.”
She further stated, “However, these features are irrelevant if the test is not useful.
However, Professor Michael Inouye and Assistant Professor Sam Lambert of Cambridge University, the main authors of the PGS Catalogue under study, defended the testing.
They stated that the system has ‘potential utility in a variety of clinical use cases’ and that they used it ‘in a more flexible manner’ in other research.
They stated, “The current paper takes a generally limited view of the applications of polygenic scores.”
