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J Clin Oncol. 2004 Dec 15;22(24):4934-43.

Refining the Amsterdam Criteria and Bethesda Guidelines: testing algorithms for the prediction of mismatch repair mutation status in the familial cancer clinic.

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  • 1Molecular and Population Genetics Laboratory, London Institute, Cancer Research UK, 44 Lincoln's Inn Fields, London WC2A 3PX, United Kingdom.

Erratum in

  • J Clin Oncol. 2005 May 20;23(15):3652.

Abstract

PURPOSE:

Hereditary nonpolyposis colon cancer (HNPCC) is a Mendelian dominant syndrome of bowel, endometrial, and other cancers and results from germline mutations in mismatch repair (MMR) genes. HNPCC is now best diagnosed on molecular grounds using MMR mutation screening, aided by microsatellite instability (MSI) and immunohistochemistry in tumors. Selection of families for molecular investigation of HNPCC is usually based on suboptimal methods (Amsterdam Criteria or Bethesda Guidelines), but these can be improved using additional clinical data (mean ages of affected persons and presence of endometrial cancer) in a quantitative model.

METHODS:

We have verified the performance of the Wijnen model and have shown that it remains valid when HNPCC is diagnosed using mutation screening, MSI, and immunohistochemistry. We have also set up and verified our own models (Amsterdam-plus and Alternative), which perform at least as well as the Wijnen model.

RESULTS:

The Amsterdam-plus model improves on the Amsterdam Criteria by using five extra variables (numbers of colorectal and endometrial cancers in the family, number of patients with five or more adenomas, number with more than one primary cancer of the colorectum or endometrium, and mean age of presentation) and performs better than the Wijnen model. The Alternative model avoids the need to evaluate the Amsterdam Criteria and performs nearly as well as the other models.

CONCLUSION:

We believe that a quantitative model, such as the Amsterdam-plus model, should be the first choice for selecting families or patients for evaluation of HNPCC using molecular tests. We present an algorithm for this process.

PMID:
15611508
[PubMed - indexed for MEDLINE]
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