Prediction Models for Lynch Syndrome View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2018

AUTHORS

Fay Kastrinos , Gregory Idos , Giovanni Parmigiani

ABSTRACT

Numerous strategies are currently available for the identification of individuals and families with Lynch syndrome that have evolved considerably over time. Prediction models for Lynch syndrome can quantify an individual’s risk of carrying a germline mismatch repair gene mutation and help clinicians decide who should be referred for further genetic risk assessment and/or genetic testing. In this chapter, we review the main prediction models developed for the identification of individuals at risk for Lynch syndrome with a focus on their specific features, performance measures as assessed by several validation studies, comparison with other clinical and molecular strategies for the diagnosis of Lynch syndrome, and their implementation and potential uses in clinical practice. We also introduce a new prediction model that provides prospective cancer risk estimates for individuals with MMR gene mutations based on comprehensive literature reviews. Lastly, we address the future considerations related to the use of clinical prediction models, including the impact of next-generation DNA sequencing technologies and the increased uptake of simultaneous testing of multiple genes (multigene panel testing) associated with inherited cancer susceptibility. More... »

PAGES

281-303

Book

TITLE

Hereditary Colorectal Cancer

ISBN

978-3-319-74258-8
978-3-319-74259-5

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-74259-5_19

DOI

http://dx.doi.org/10.1007/978-3-319-74259-5_19

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1103815111


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