Systematic bias in traumatic brain injury outcome studies because of loss to follow-up

Arch Phys Med Rehabil. 2003 Feb;84(2):153-60. doi: 10.1053/apmr.2003.50093.


Objective: To identify potential sources of selection bias created by subjects lost to follow-up in studies of traumatic brain injury (TBI).

Design: Demographic, premorbid, injury-related, and hospital course characteristics were compared for subjects lost and found for 1- and 2-year postinjury follow-ups by using bivariate tests and logistic regression analysis.

Setting: Three prospective, longitudinal data sets-a single center, a multicenter, and a statewide incidence surveillance system and follow-up registry.

Participants: Adolescents and adults hospitalized with a diagnosis of TBI.

Interventions: Not applicable.

Main outcome measures: Subjects were considered lost when no information was collected from the person with TBI or only limited information could be obtained from a proxy, for any reason, including death, refusal, inability to locate, and inability to interview.

Results: At year 1 follow-up, 58.0% to 58.6% of subjects were found; 39.7% to 42.0% of subjects were found by year 2. Variables most frequently associated with loss to follow-up were cause of injury, blood alcohol level, motor function, hospital payer source, and race and ethnicity.

Conclusions: TBI follow-up studies may experience selective attrition of subjects who (1) are socioeconomically disadvantaged, (2) have a history of substance abuse, and (3) have violent injury etiologies. These phenomena are mitigated for those with more severe motor deficits. Loss to follow-up may be a problem inherent to this population; however, the high rate and its selective nature are problematic for outcome studies.

Publication types

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

MeSH terms

  • Adolescent
  • Adult
  • Bias
  • Brain Injuries / epidemiology*
  • Brain Injuries / rehabilitation*
  • Follow-Up Studies
  • Hospitalization
  • Humans
  • Logistic Models
  • Outcome Assessment, Health Care*
  • Patient Selection
  • Registries
  • Trauma Severity Indices