Reclassification of clinically-detected sequence variants: Framework for genetic clinicians and clinical scientists by CanVIG-UK (Cancer Variant Interpretation Group UK)
Lucy Loong, Alice Garrett, Sophie Allen, Subin Choi, Miranda Durkie, Alison Callaway, James Drummond, George J. Burghel, Rachel Robinson, Beth Torr, Ian Berry, Andrew J. Wallace, Diana M. Eccles, Sian Ellard, Emma L. Baple, D. Gareth Evans, Emma R. Woodward, Anjana Kulkarni, Fiona Lalloo, Marc Tischkowitz, Anneke Lucassen, Helen Hanson, Clare Turnbull
Abstract
PURPOSE: Variant classifications may change over time, driven by emergence of fresh or contradictory evidence or evolution in weighing or combination of evidence items. For variant classifications above the actionability threshold, which is classification of likely pathogenic or pathogenic, clinical actions may be irreversible, such as risk-reducing surgery or prenatal interventions. Variant reclassification up or down across the actionability threshold can therefore have significant clinical consequences. Laboratory approaches to variant reinterpretation and reclassification vary widely. METHODS: Cancer Variant Interpretation Group UK is a multidisciplinary network of clinical scientists and genetic clinicians from across the 24 Molecular Diagnostic Laboratories and Clinical Genetics Services of the United Kingdom (NHS) and Republic of Ireland. We undertook surveys, polls, and national meetings of Cancer Variant Interpretation Group UK to evaluate opinions about clinical and laboratory management regarding variant reclassification. RESULTS: We generated a consensus framework on variant reclassification applicable to cancer susceptibility genes and other clinical areas, which provides explicit recommendations for clinical and laboratory management of variant reclassification scenarios on the basis of the nature of the new evidence, the magnitude of evidence shift, and the final classification score. CONCLUSION: In this framework, clinical and laboratory resources are targeted for maximal clinical effect and minimal patient harm, as appropriate to all resource-constrained health care settings.