title: Potential Role of Community-Based Healthcare System Data in Research on Survivors of Adolescent and Young Adult Cancer.
abstract: We sought to examine issues of generalizability in research on adolescent and young adult (AYA) cancer survivorship that relies on using community-based healthcare delivery system data.
  
  
  
  Individuals aged 15 to 39 diagnosed with cancer between 1992 and 2006 were identified using data from community-based healthcare systems in California and Seattle. Loss to follow-up was defined as the first disenrollment (the end) of membership in the healthcare systems after cancer. Censoring occurred at death or study end (2009). We used Kaplan-Meier analysis to quantify follow-up, and multiple Cox regression to examine the association of follow-up loss with demographic and cancer characteristics.
  
  
  
  Of 6828 eligible AYAs, most (93%) were aged between 20 and 39 years at diagnosis; 62% were female and 39% were non-White. Solid tumors accounted for 81% of diagnoses. The majority (89%) of patients continued to be members of the healthcare systems and available for follow-up 1 year after diagnosis. Approximately 60% remained enrolled 5 years after diagnosis. Loss to follow-up was associated with younger age at diagnosis, male gender, and African American or Hispanic race/ethnicity.
  
  
  
  Data from community-based healthcare delivery systems offer an efficient way to identify large and diverse samples of AYA-onset cancer survivors. Differential loss to follow-up can threaten the generalizability of results from these studies and should be assessed quantitatively. Healthcare system data offer an alternative to studies requiring direct contact with participants.
authors.affiliation: Division of Public Health Sciences, Wake Forest School of Medicine , Winston-Salem, North Carolina.
authors.forename: Ann M
authors.initials: AM
authors.lastname: Geiger
authors.forename: Sharon M
authors.initials: SM
authors.lastname: Castellino
authors.forename: Janet A
authors.initials: JA
authors.lastname: Tooze
authors.forename: Andrea
authors.initials: A
authors.lastname: Altschuler
authors.forename: Stacy
authors.initials: S
authors.lastname: Month
authors.forename: Ann C
authors.initials: AC
authors.lastname: Mertens
authors.forename: Larissa
authors.initials: L
authors.lastname: Nekhlyudov
authors.forename: Sarah M
authors.initials: SM
authors.lastname: Greene
keywords: bias; epidemiologic methods; healthcare research; survivorship