Predictors of participation in clinical and psychosocial follow-up of the kConFab breast cancer family cohort

Fam Cancer. 2005;4(2):105-13. doi: 10.1007/s10689-004-6129-x.

Abstract

Introduction: Prospective collection of epidemiological, psychosocial and outcome data in large breast cancer family cohorts should provide less biased data than retrospective studies regarding penetrance of breast cancer and modifiers of genetic risk.

Methods: The Kathleen Cuningham Foundation for Research into Breast Cancer (kConFab) recently commenced 3-yearly follow-up on over 750 families with multiple cases of breast cancer. Clinical follow-up was by mailed self-report questionnaire to all participants, while psychosocial follow-up was only of unaffected women and consisted of two components: a mailed questionnaire and an interview regarding stressful life events.

Results: To date, 1928 of 2748 (70%) participants returned the clinical follow-up questionnaire (10% opted out, 16% were non-responders, and 4% were not contactable). Of the unaffected females who returned the clinical follow-up questionnaire, 91% participated in the psychosocial follow-up. In multivariate analyses, sex, personal cancer status, marital status, age and educational status were independent predictors of response to the clinical follow-up questionnaire, and number of female children, age, and family history of breast cancer were independent predictors of response to the psychosocial follow-up.

Conclusions: A first round of 3-yearly clinical and psychosocial follow-up using a mailed questionnaire was feasible in this cohort. High response rates were achieved by employing intensive tracing and reminder strategies. The predictors of response for the clinical and psychosocial follow-up components of this study should be considered in designing similar follow-up strategies for other family cancer cohorts.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Breast Neoplasms / genetics*
  • Cohort Studies*
  • Female
  • Forecasting
  • Genetic Predisposition to Disease
  • Humans
  • Middle Aged
  • Multivariate Analysis
  • Patient Compliance*
  • Pedigree
  • Research Design
  • Risk Factors
  • Surveys and Questionnaires