Underreporting of family history of colon cancer: correlates and implications

Cancer Epidemiol Biomarkers Prev. 1999 Jul;8(7):635-9.

Abstract

Scientific advances in cancer genetics, risk counseling, and management of high-risk individuals require information about familial cancer history. Because some people may not report, or may be unaware of, cancer in their families, it is important to examine the extent of underreporting of family history. We mailed a survey to first-degree relatives of patients with histologically confirmed diagnoses of colorectal cancer (CRC) before age 60 (n = 426, 77% response rate). Analyses examined the extent of underreporting of family history and its predictors (demographics, cancer characteristics, knowledge, and communication) and correlates (cancer worry, perceived risk). Logistic regression analysis was performed using generalized estimating equations to account for family clusters. Despite confirmed diagnosis of CRC in a parent or sibling, 25.4% of respondents reported having no first-degree relative with colon cancer. In multivariate models, the most significant predictor of awareness of a relative's CRC was the stage-at-diagnosis; also, males and those with low knowledge about colon cancer were significantly less aware. Awareness of a relative's CRC was associated with higher cancer worry and risk perception, and being a college graduate contributed independently to increased risk perception. Sole dependence on mailed self-administered questionnaires may lead to substantial underreporting of familial colon cancers, especially those that are in situ or localized.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Bias
  • Colorectal Neoplasms / epidemiology*
  • Colorectal Neoplasms / prevention & control
  • Female
  • Genetic Testing*
  • Hawaii
  • Health Knowledge, Attitudes, Practice
  • Humans
  • Male
  • Medical History Taking / statistics & numerical data*
  • Middle Aged
  • Registries / statistics & numerical data
  • Risk