Purpose Genomic microarrays can detect copy number variants not detectable by conventional cytogenetics. This technology is diffusing rapidly into prenatal settings even though the clinical implications of many copy number variants are currently unknown. We conducted a qualitative pilot study to explore the experiences of women receiving abnormal results from prenatal microarray testing performed in a research setting. Methods Participants were a subset of women participating in a multicenter prospective study “Prenatal Cytogenetic Diagnosis by Array-based Copy Number Analysis”. Telephone interviews were conducted with 23 women receiving abnormal prenatal microarray results. Results We found that five key elements dominated the experiences of women who had received abnormal prenatal microarray results: an offer too good to pass up, blindsided by the results, uncertainty and unquantifiable risks, need for support, and toxic knowledge. Conclusion As prenatal microarray testing is increasingly utilized, uncertain findings will be common resulting in greater need for careful pre and post test counseling, and more education of, and resources for providers so they can adequately support the women who are undergoing testing.

The evidence-based review (EBR) process has been widely used to develop standards for medical decision-making and to explore complex clinical questions. This approach can be applied to genetic tests, such as chromosomal microarrays, in order to assist in the clinical interpretation of certain copy number variants (CNVs), particularly those that are rare, and guide array design for optimal clinical utility. To address these issues, the International Standards for Cytogenomic Arrays Consortium has established an EBR Work Group charged with building a framework to systematically assess the potential clinical relevance of CNVs throughout the genome. This group has developed a rating system enumerating the evidence supporting or refuting dosage sensitivity for individual genes and regions that considers the following criteria: number of causative mutations reported; patterns of inheritance; consistency of phenotype; evidence from large-scale case-control studies; mutational mechanisms; data from public genome variation databases; and expert consensus opinion. The system is designed to be dynamic in nature, with regions being reevaluated periodically to incorporate emerging evidence. The evidence collected will be displayed within a publically available database, and can be used in part to inform clinical laboratory CNV interpretations as well as to guide array design.

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