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ObjectiveTo provide an overview of the evidence on prevalence and outcomes of incidental imaging findings. DeSiGNUmbrella review of systematic reviews. Data SOurceSSearches of MEDLINE, EMBASE up to August 2017; screening of references in included papers. eliGibility criteria Criteria included systematic reviews and meta-analyses of observational studies that gave a prevalence of incidental abnormalities ("incidentalomas"). An incidental imaging finding was defined as an imaging abnormality in a healthy, asymptomatic patient or an imaging abnormality in a symptomatic patient, where the abnormality was not apparently related to the patient's symptoms. Primary studies that measured the prevalence of incidentalomas in patients with a history of malignancy were also considered in sensitivity analyses. reSultS 20 systematic reviews (240 primary studies) were identified from 7098 references from the database search. Fifteen systematic reviews provided data to quantify the prevalence of incidentalomas, whereas 18 provided data to quantify the outcomes of incidentalomas (13 provided both). The prevalence of incidentalomas varied substantially between imaging tests; it was less than 5% for chest computed tomography for incidental pulmonary embolism in patients with and without cancer and whole body positron emission tomography (PET) or PET/computed tomography (for patients with and without cancer). Conversely, incidentalomas occurred in more than a third of images in cardiac magnetic resonance imaging (MRI), chest computed tomography (for incidentalomas of thorax, abdomen, spine, or heart), and computed tomography colonoscopy (for extracolonic incidentalomas). Intermediate rates occurred with MRI of the spine (22%) and brain (22%). The rate of malignancy in incidentalomas varied substantially between organs; the prevalence of malignancy was less than 5% in incidentalomas of the brain, parotid, and adrenal gland. Extra-colonic, prostatic, and colonic incidentalomas were malignant between 10% and 20% of the time, whereas renal, thyroid, and ovarian incidentalomas were malignant around a quarter of the time. Breast incidentalomas had the highest percentage of malignancy (42%, 95% confidence interval 31% to 54%). Many assessments had high between-study heterogeneity (15 of 20 metaanalyses with I 2 >50%).cONcluSiONS There is large variability across different imaging techniques both in the prevalence of incidentalomas and in the prevalence of malignancy for specific organs. This umbrella review will aid clinicians and patients weigh up the pros and cons of requesting imaging scans and will help with management decisions after an incidentaloma diagnosis. Our results can underpin the creation of guidelines to assist these decisions.

Background - There is considerable interest in whether genetic data can be used to improve standard cardiovascular disease risk calculators, as the latter are routinely used in clinical practice to manage preventative treatment. Methods - Using the UK Biobank (UKB) resource, we developed our own polygenic risk score (PRS) for coronary artery disease (CAD). We used an additional 60,000 UKB individuals to develop an integrated risk tool (IRT) that combined our PRS with established risk tools (either the American Heart Association/American College of Cardiology's Pooled Cohort Equations (PCE) or UK's QRISK3), and we tested our IRT in an additional, independent, set of 186,451 UKB individuals. Results - The novel CAD PRS shows superior predictive power for CAD events, compared to other published PRSs and is largely uncorrelated with PCE and QRISK3. When combined with PCE into an integrated risk tool, it has superior predictive accuracy. Overall, 10.4% of incident CAD cases were misclassified as low risk by PCE and correctly classified as high risk by the IRT, compared to 4.4% misclassified by the IRT and correctly classified by PCE. The overall net reclassification improvement for the IRT was 5.9% (95% CI 4.7-7.0). When individuals were stratified into age-by-sex subgroups the improvement was larger for all subgroups (range 8.3%-15.4%), with best performance in 40-54yo men (15.4%, 95% CI 11.6-19.3). Comparable results were found using a different risk tool (QRISK3), and also a broader definition of cardiovascular disease. Use of the IRT is estimated to avoid up to 12,000 deaths in the USA over a 5-year period. Conclusions - An integrated risk tool that includes polygenic risk outperforms current risk stratification tools and offers greater opportunity for early interventions. Given the plummeting costs of genetic tests, future iterations of CAD risk tools would be enhanced with the addition of a person's polygenic risk.

Cardiovascular disease is the leading contributor to years lost due to disability or premature death among adults. Current efforts focus on risk prediction and risk factor mitigation‚ which have been recognized for the past half-century. However, despite advances, risk prediction remains imprecise with persistently high rates of incident cardiovascular disease. Genetic characterization has been proposed as an approach to enable earlier and potentially tailored prevention. Rare mendelian pathogenic variants predisposing to cardiometabolic conditions have long been known to contribute to disease risk in some families. However, twin and familial aggregation studies imply that diverse cardiovascular conditions are heritable in the general population. Significant technological and methodological advances since the Human Genome Project are facilitating population-based comprehensive genetic profiling at decreasing costs. Genome-wide association studies from such endeavors continue to elucidate causal mechanisms for cardiovascular diseases. Systematic cataloging for cardiovascular risk alleles also enabled the development of polygenic risk scores. Genetic profiling is becoming widespread in large-scale research, including in health care–associated biobanks, randomized controlled trials, and direct-to-consumer profiling in tens of millions of people. Thus, individuals and their physicians are increasingly presented with polygenic risk scores for cardiovascular conditions in clinical encounters. In this scientific statement, we review the contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases. We selected 5 cardiometabolic diseases (coronary artery disease, hypercholesterolemia, type 2 diabetes, atrial fibrillation, and venous thromboembolic disease) and response to drug therapy and offer provisional guidance to health care professionals, researchers, policymakers, and patients.