Time-dependent study entries and exposures in cohort studies can easily be sources of different and avoidable types of bias

J Clin Epidemiol. 2012 Nov;65(11):1171-80. doi: 10.1016/j.jclinepi.2012.04.008.


Objectives: To display and discuss the reasons and consequences of length and time-dependent bias. They might occur in presence of a time-dependent study entry or a time-dependent exposure which might change from unexposed to exposed.

Study design and setting: Recalling the popular study of Oscar nominees and using a real-data example from hospital epidemiology, we give innovative and easy-to-understand graphical presentations of how these biases corrupt the analyses via distorted time-at-risk. Cumulative hazard plots and Cox proportional hazards models were used. We are building bridges to medical disciplines such as critical care medicine, hepatology, pharmaco-epidemiology, transplantation medicine, neurology, gynecology and cardiology.

Results: In presence of time-dependent bias, the hazard ratio (comparing exposed with unexposed) is artificially underestimated. The length bias leads to an artificial underestimation of the overall hazard. When both biases coexist it can lead to different directions of biased hazard ratios.

Conclusion: Since length and time-dependent bias might occur in several medical disciplines, we conclude that understanding and awareness are the best prevention of survival bias.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Abortion, Spontaneous / epidemiology
  • Alzheimer Disease / mortality
  • Cohort Studies*
  • Coronary Disease / epidemiology
  • Cross Infection / epidemiology
  • Data Interpretation, Statistical*
  • Diabetes Mellitus / epidemiology
  • Female
  • Heart Transplantation / mortality
  • Humans
  • Length of Stay / statistics & numerical data
  • Liver Cirrhosis / mortality
  • Pregnancy
  • Proportional Hazards Models
  • Selection Bias*
  • Survival Analysis*
  • Time Factors