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Familial colorectal cancer syndromes: an overview of clinical management

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Abstract

Familial colorectal cancer syndromes pose a complex challenge to the treating clinician. Once a syndrome is recognized, genetic testing is often required to confirm the clinical suspicion. Management from that point is usually based on disease-specific guideline recommendations targeting risk reduction for the patient and their relatives through surgery, surveillance and chemoprophylaxis. The aim of this paper is to provide an up-to-date summary of the most common familial syndromes and their medical and surgical management, with specific emphasis on evidence-based interventions that improve patient outcome, and to present the information in a manner that is easily readable and clinically relevant to the treating clinician.

Financial & competing interests disclosure

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending or royalties.

No writing assistance was utilized in the production of this manuscript.

Key issues
  • Twenty percent of colorectal cancer patients have a hereditary form of the disease, and 5% have a specific known mutation.

  • These patients pose a complex challenge to the treating clinician.

  • Specific genetic testing is often required to confirm the clinical suspicion.

  • A classification system based on polyp type (or lack thereof) is proposed as a memory aid.

  • Management after identification is based on disease-specific guideline recommendations targeting risk reduction for the patient and their relatives.

  • These recommendations need to be individualized to achieve the best outcome.

  • Management is best undertaken in the setting of a specialized familial cancer clinic.

  • Future advances in personalized genomics will improve risk prediction algorithms and result in individualized management plans.

Notes

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