Information recovery in cancer families: value for risk estimations

Hassan Roudgari, Lindsey F. Masson, Neva E. Haites

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background Drawing an informative pedigree is fundamental in genetic counselling. It is very common for some parts of pedigrees to remain ambiguous because of the proband's inability to recall the past history of her/his family. Current age, date of birth, date of death and age of diagnosis are the commonest missing information in pedigrees.

Methods The Scottish Social Statistics website, National Statistics website and English language literature were used to model extrapolations. About 172 Grampian families and three high-risk Grampian families with complete information were chosen to evaluate the influence of extrapolations on models' performance. Differences between original data and extrapolated data were assessed by independent samples t-test.

Results Changes made by extrapolations in age- and cancer-related information were not statistically significant (P > 0.05) in comparison with original data, except for average age of diagnosis of breast cancer (P = 0.03). The differences made by extrapolations in estimated probabilities generated by probability assessment models were small and ignorable except that for Tyrer-Cuzick model for Grampian family 3.

Conclusion Extrapolations based on National Health Statistics can scientifically cover missing information in a defined population with minimum effect on performance of probability assessment models.

Original languageEnglish
Pages (from-to)415-443
Number of pages29
JournalFamilial Cancer
Volume6
Issue number4
DOIs
Publication statusPublished - 2007

Keywords

  • breast cancer
  • ovarian cancer
  • prostate cancer
  • pancreatic cancer
  • pedigrees
  • missing information
  • risk/probability assessment model
  • onset breast-cancer
  • ovarian-cancer
  • genetic susceptibility
  • germline mutations
  • pancreatic-cancer
  • prostate-cancer
  • BRCA1
  • models
  • prediction
  • survival

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