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Prediction models in Lynch syndrome

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Abstract

Prediction models for the identification of Lynch syndrome have been developed to quantify an individual’s risk of carrying a mismatch repair gene mutation and help clinicians decide for whom further risk assessment and genetic testing is necessary. There are diverse clinical settings in which a healthcare provider has the opportunity to assess an individual for Lynch syndrome. Prediction models offer a potentially feasible and useful strategy to systematically identify at-risk individuals, whether they are affected with colorectal cancer or not, and to help with management of the implications of molecular and germline test results. Given the complexity of diagnostic information currently available to clinicians involved in identifying and caring for patients with Lynch syndrome, prediction models provide a useful and complementary aid in medical decision-making. Systematic implementation of prediction models estimates should be considered in routine clinical care and at various stages of cancer risk assessment and prevention. In this manuscript, we review the main prediction models developed for Lynch syndrome, focus on their specific features and performance assessed in several validation studies, compare the models with other clinical and molecular strategies for the diagnosis of Lynch syndrome, and discuss their potential uses in clinical practice.

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Acknowledgments

This work was supported by the National Cancer Institute: K07 CA151769-02 (FK), R01 CA132829 (SS) and K24 CA113433 (SS). Additional support from the Louis V. Gerstner, Jr. Scholars Program (FK).

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Authors and Affiliations

  1. Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA

    Fay Kastrinos

  2. Division of Digestive and Liver Diseases, Columbia University Medical Center, New York, NY, USA

    Fay Kastrinos

  3. Department of Medical Oncology, Hospital Vall d’Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain

    Judith Balmaña

  4. Population Sciences Division, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA, 02215, USA

    Sapna Syngal

  5. Division of Gastroenterology, Brigham and Women’s Hospital, Boston, MA, USA

    Sapna Syngal

  6. Harvard Medical School, Boston, MA, USA

    Sapna Syngal

  7. Columbia University College of Physicians and Surgeons, New York, NY, USA

    Fay Kastrinos

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  1. Fay Kastrinos
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  2. Judith Balmaña
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  3. Sapna Syngal
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Correspondence to Sapna Syngal.

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Kastrinos, F., Balmaña, J. & Syngal, S. Prediction models in Lynch syndrome. Familial Cancer 12, 217–228 (2013). https://doi.org/10.1007/s10689-013-9632-0

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  • DOI: https://doi.org/10.1007/s10689-013-9632-0

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