Survival Bias When Assessing Risk Factors for Age-Related Macular Degeneration: A Tutorial with Application to the Exposure of Smoking

Myra B. McGuinness, Amalia Karahalios, Jessica Kasza, Robyn H. Guymer, Robert P. Finger, Julie A Simpson

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Purpose: We illustrate the effect of survival bias when investigating risk factors for eye disease in elderly populations for whom death is a competing risk. Our investigation focuses on the relationship between smoking and late age-related macular degeneration (AMD) in an observational study impacted by censoring due to death. Methods: Statistical methodology to calculate the survivor average causal effect (SACE) as a sensitivity analysis is described, including example statistical computing code for Stata and R. To demonstrate this method, we examine the causal effect of smoking history at baseline (1990–1994) on the presence of late AMD at the third study wave (2003–2007) using data from the Melbourne Collaborative Cohort Study. Results: Of the 40,506 participants eligible for inclusion, 38,092 (94%) survived until the start of the third study wave, 20,752 (51%) were graded for AMD (60% female, aged 47–85 years, mean 65 ± 8.7 years). Late AMD was detected in 122 participants. Logistic regression showed strong evidence of an increased risk of late AMD for current smokers compared to non-smokers (adjusted naïve odds ratio 2.99, 95% confidence interval, CI, 1.74–5.13). Among participants expected to be alive at the start of follow-up regardless of their smoking status, the estimated SACE odds ratio comparing current smokers to non-smokers was at least 3.42 (95% CI 1.57–5.15). Conclusions: Survival bias can attenuate associations between harmful exposures and diseases of aging. Estimation of the SACE using a sensitivity analysis approach should be considered when conducting epidemiological research within elderly populations.

Original languageEnglish
Number of pages10
JournalOphthalmic Epidemiology
Issue number4
Publication statusPublished - 13 Mar 2017


  • Age-related macular degeneration
  • causal methodology
  • death
  • smoking
  • survival bias

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