A data-driven evaluation of the size and content of expanded carrier screening panels.

PURPOSE: The American College of Obstetricians and Gynecologists (ACOG) proposed seven criteria for expanded carrier screening (ECS) panel design. To ensure that screening for a condition is sufficiently sensitive to identify carriers and reduce residual risk of noncarriers, one criterion requires a per-condition carrier rate greater than 1 in 100. However, it is unestablished whether this threshold corresponds with a loss in clinical detection. The impact of the proposed panel design criteria on at-risk couple detection warrants data-driven evaluation. METHODS: Carrier rates and at-risk couple rates were calculated in 56,281 patients who underwent a 176-condition ECS and were evaluated for panels satisfying various criteria. Condition-specific clinical detection rates were estimated via simulation. RESULTS: Different interpretations of the 1-in-100 criterion have variable impact: a compliant panel would include between 3 and 38 conditions, identify 11-81% fewer at-risk couples, and detect 36-79% fewer carriers than a 176-condition panel. If the carrier rate threshold must be exceeded in all ethnicities, ECS panels would lack prevalent conditions like cystic fibrosis. Simulations suggest that the clinical detection rate remains >84% for conditions with carrier rates as low as 1 in 1000. CONCLUSION: The 1-in-100 criterion limits at-risk couple detection and should be reconsidered.

Correction: Sequencing as a first-line methodology for cystic fibrosis carrier screening.

The original version of this Article contained an error in Figure 3. Specifically, the result "3 (67%) TOP" should read "2 (67%) TOP." This has now been corrected in both the PDF and HTML versions of the Article.

Sequencing as a first-line methodology for cystic fibrosis carrier screening.

PURPOSE: Medical society guidelines recommend offering genotyping-based cystic fibrosis (CF) carrier screening to pregnant women or women considering pregnancy. We assessed the performance of sequencing-based CF screening relative to genotyping, in terms of analytical validity, clinical validity, clinical impact, and clinical utility. METHODS: Analytical validity was assessed using orthogonal confirmation and reference samples. Clinical validity was evaluated using the CFTR2 database. Clinical impact was assessed using ~100,000 screened patients. Three screening strategies were compared: genotyping 23 guideline-recommended variants ("CF23"), sequencing all coding bases in CFTR ("NGS"), and sequencing with large copy-number variant (CNV) identification ("NGS + CNV"). Clinical utility was determined via self-reported actions of at-risk couples (ARCs). RESULTS: Analytical accuracy of NGS + CNV was 100% for SNVs, indels, and CNVs; interpretive clinical specificity relative to CFTR2 was 99.5%. NGS + CNV detected 58 ARCs, 18 of whom would have gone undetected with CF23 alone. Most ARCs (89% screened preconceptionally, 56% prenatally) altered pregnancy management, and no significant differences were observed between ARCs with or without at least one non-CF23 variant. CONCLUSION: Modern NGS and variant interpretation enable accurate sequencing-based CF screening. Limiting screening to 23 variants does not improve analytical validity, clinical validity, or clinical utility, but does fail to detect approximately 30% (18/58) of ARCs.

Inherited Cancer in the Age of Next-Generation Sequencing.

Next-generation sequencing (NGS) technology has led to the ability to test for multiple cancer susceptibility genes simultaneously without significantly increasing cost or turnaround time. With growing usage of multigene testing for inherited cancer, ongoing education for nurses and other health-care providers about hereditary cancer screening is imperative to ensure appropriate testing candidate identification, test selection, and posttest management. The purpose of this review article is to (1) provide an overview of how NGS works to detect germline mutations, (2) summarize the benefits and limitations of multigene panel testing, (3) describe risk categories of cancer susceptibility genes, and (4) highlight the counseling considerations for patients pursuing multigene testing.