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

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.

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.

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).

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.