With the growing use of genetic testing in medicine, the question of when genetic findings should be reinterpreted in light of new data has become inescapable. The generation of population and disease-specific data, development of computational tools, and new understandings of the relationship of specific genes to disorders can all trigger changes in variant classification that may have important implications for patients and the clinicians caring for them. This is a particular concern for patients from groups underrepresented in current reference datasets, since they have higher rates of uncertain findings. Here we identify the challenges to implementing a systematic approach to variant reinterpretation and propose solutions. In particular, we address (a) the infrastructure needed to support implementation of systematic variant reinterpretation, (b) the issues around obtaining consent from patients for reinterpretation, (c) the process for triggering reinterpretation, (d) pathways for the flow of reinterpreted data, (e) considerations for how to cover the costs of reinterpretation, and (f) practical issues related to implementation of processes and policies that address these issues, including the importance of a fixed duration during which there is an expectation that variants will be reinterpreted.

PURPOSE: The use of patient race in medicine is controversial for its potential either to exacerbate or address health disparities. Polygenic risk scores (PRS) have emerged as a tool for risk stratification models used in preventive medicine. We examined whether PRS results impact primary care physician (PCP) medical decision-making and whether that impact varies by patient race. METHODS: Using an online survey with a randomized experimental design among PCPs in a national database, we ascertained decision-making around atherosclerotic cardiovascular disease prevention and prostate cancer screening for case scenario patients who were clinically identical except for randomized reported race. RESULTS: Across 369 PCPs (email open rate 10.8%, partial completion rate 93.7%), recommendations varied with PRS results in expected directions (low-risk results, no available PRS results, and high-risk results). Still, physicians randomized to scenarios with Black patients were more likely to recommend statin therapy than those randomized to scenarios with White patients (OR 1.74, 95% CI 1.16, 2.59, p=0.007), despite otherwise identical clinical profiles and independent of PRS results. Similarly, physicians were more likely to recommend prostate cancer screening for Black patients compared with White patients (OR 1.58, 95% CI 1.06, 2.35, p=0.025), despite otherwise identical clinical and genetic profiles. CONCLUSION: Despite advances in precision risk stratification, physicians will likely continue to use patient race implicitly or explicitly in medical decision-making.

PURPOSE: The success of genomic medicine hinges on implementation of genetic knowledge in clinical settings. In novel subspecialties, it requires that clinicians refer patients to genetic evaluation or testing, but referral is likely to be impacted by genetic knowledge. METHODS: An online survey was administered to self-identified nephrologists working in the U.S.. Nephrologists' demographic characteristics, genetic education, confidence in clinical genetics, genetic knowledge, and referral rates of patients to genetic evaluation were collected. RESULTS: 201 nephrologists completed the survey. All reported treating patients with genetic forms of kidney disease, but 37% have referred less than 5 patients to genetic evaluation. A third had limited basic genetic knowledge. Most nephrologists (85%) reported concerns regarding future health insurance eligibility as a barrier to referral to genetic testing. Most adult nephrologists reported insufficient genetic education during residency (65%) and fellowship training (52%). Lower rating of genetic education and lower knowledge in recognizing signs of genetic kidney diseases were significantly associated with lower number of patients referred to genetic evaluation (p-value<0.001). Most nephrologists reported that improving their genetic knowledge is important for them (>55%). CONCLUSIONS: There is a need to enhance nephrologists' genetic education to increase genetic testing utilization in nephrology.

PURPOSE: To evaluate the cost-effectiveness of population-based expanded reproductive carrier screening (RCS) for a 300 recessive genes panel from health service and societal perspectives. METHODS: A microsimulation model (PreConMod) was developed using 2016 Australian Census data as the base population. Epidemiological, health and indirect cost data were based on literature review. The study assessed the incremental-cost-effectiveness-ratio (ICER) of expanded RCS compared with (i) no population screening (ii) three-condition screening for cystic fibrosis, spinal muscular atrophy, and fragile X syndrome in a single birth cohort. Averted affected births and health service savings with expanded RCS were projected to year 2061. Both one-way and probability sensitivity analyses were conducted to assess the uncertainty of the parameter inputs. RESULTS: Expanded RCS was cost-saving compared with no population screening and cost-effective compared to the three-condition screening (ICER of $6,287 per QALY gained) at an uptake rate of 50% for RCS, 59% for IVF and preimplantation genetic testing, 90% for prenatal diagnosis testing and 50% for elective termination of affected pregnancies and a cost of A$595 per couple screened. Our model predicts that expanded RCS would avert one-third of affected births in a single birth cohort and reduce lifetime health service spending by A$632.0 million. Expanded RCS was estimated to be cost saving from the societal perspective. CONCLUSION: Expanded RCS is cost-effective from the health service and societal perspectives. Expanded RCS is projected to avert significantly more affected births and result in health service saving beyond those expected from three-condition screening or no population screening.