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

ABSTRACT

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.

KEYWORDS:

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

Acknowledgments

The authors are grateful to Prof. Graham Giles and the Cancer Council Victoria for kindly providing data from the Melbourne Collaborative Cohort Study to use as an illustrative example in this tutorial paper. Vital status was ascertained through the Victorian Cancer Registry and the Australian Institute of Health and Welfare, including the National Death Index.

Declaration of interest

The authors report no conflicts of interest. The authors alone are responsible for the writing and content of this article.

Funding

Cohort recruitment was funded by VicHealth and Cancer Council Victoria. Further Melbourne Collaborative Cohort Study funding: the National Health & Medical Research Council of Australia (NHMRC) Program Grant 209057, Capacity Building Grant 251533 and Enabling Grant 396414. The ophthalmic component was funded by the Ophthalmic Research Institute of Australia; American Health Assistance Foundation (M2008-082), Jack Brockhoff Foundation, John Reid Charitable Trust, Perpetual Trustees. M. McGuinness is funded by an Australian Postgraduate Award and a studentship courtesy of Victorian Centre for Biostatistics (NHMRC: Centre of Research Excellence grant 1035261). J. Simpson is funded by a National Health and Medical Research Council (NHMRC) Senior Research Fellowship 1104975, and R. Guymer by a NHMRC Principal Research Fellowship 1103013. This work was supported by infrastructure from the Cancer Council of Victoria. CERA receives operational infrastructure support from the Victorian government. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Supplemental materials

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Additional information

Funding

Cohort recruitment was funded by VicHealth and Cancer Council Victoria. Further Melbourne Collaborative Cohort Study funding: the National Health & Medical Research Council of Australia (NHMRC) Program Grant 209057, Capacity Building Grant 251533 and Enabling Grant 396414. The ophthalmic component was funded by the Ophthalmic Research Institute of Australia; American Health Assistance Foundation (M2008-082), Jack Brockhoff Foundation, John Reid Charitable Trust, Perpetual Trustees. M. McGuinness is funded by an Australian Postgraduate Award and a studentship courtesy of Victorian Centre for Biostatistics (NHMRC: Centre of Research Excellence grant 1035261). J. Simpson is funded by a National Health and Medical Research Council (NHMRC) Senior Research Fellowship 1104975, and R. Guymer by a NHMRC Principal Research Fellowship 1103013. This work was supported by infrastructure from the Cancer Council of Victoria. CERA receives operational infrastructure support from the Victorian government. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.