The impact of reporting incidental findings from exome and whole-genome sequencing: predicted frequencies based on modeling

PURPOSE: The American College of Medical Genetics and Genomics released practice guidelines recommending reporting of incidental findings from exome and whole-genome sequencing by massively parallel (next-generation) sequencing for multiple conditions. Policy statements from other agencies are still being developed, and many attempt to take into consideration the predicted increase in workload caused by reporting incidental findings. We describe the effects of changing the sensitivity and the specificity, as well as the implications of varying diagnostic criteria and a priori prevalence, and those of increasing the number of included conditions, on rates of incidental findings. METHODS: We developed a simple mathematical model based on binomial probability for predicting rates of incidental findings. We primed and validated the model using published variant frequencies. RESULTS: The model correctly calculates observed rates of incidental findings. Changing the model's parameters shows that even minor changes in diagnostic criteria or sequencing accuracy cause large variation in rates of incidental findings. CONCLUSION: Our model correctly explains observed rates of incidental findings. Key drivers of rates include diagnostic criteria, variant frequency, disease penetrance, and sequencing and bioinformatics accuracy. Rates of incidental findings are relatively insensitive to even large increases in the number of conditions included.