Cancer Risk Analysis in Families with Hereditary Nonpolyposis Colorectal Cancer

M Kokuer, R N Naguib, Peter Jancovic, H Banfield Younghusband, RC Green

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Colorectal cancer (CRC) is one of the most common fatal cancers in developed countries and represents a significant public-health issue. About 3%-5% of patients with CRC have hereditary nonpolyposis colorectal cancer (HNPCC). Cancer morbidity and mortality can be reduced if early and intensive screening is pursued. However, despite advances in screening, population-wide genetic screening for HNPCC is not currently considered feasible due to its complexity and expense. If the risk of a family having HNPCC can be identified/assessed, then only the high-risk fraction of the population would undergo intensive screening. This identification is currently performed by a genetic counselor/physician who makes the decision based on some predefined criteria. Here, we report on a system to identify. the risk of a family having HNPCC based on its history. We compare artificial neural networks and statistical approaches for assessing the risk of a family having HNPCC and discuss the experimental results obtained by these two approaches.
Original languageEnglish
Pages (from-to)581-587
Number of pages7
JournalIEEE Transactions on Information Technology in Biomedicine
Volume10
Issue number3
DOIs
Publication statusPublished - 1 Jul 2006

Keywords

  • principal component analysis (PCA)
  • pedigree analysis
  • logistic regression (LR)
  • cancer risk assessment
  • hereditary nonpolyposis colorectal cancer (HNPCC)
  • artificial neural networks (ANNs)
  • self-organizing maps (SOM)

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