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Abstract
The inaccessibility of the brain poses a problem for neuroscience. Scientists have traditionally responded by developing biomarkers for brain physiology and disease. The retina is an attractive source of biomarkers since it shares many features with the brain. Some even describe the retina as a ‘window’ to the brain, implying that retinal signs are analogous to brain disease features. However, new analytical methods are needed to show whether or not retinal signs really are equivalent to brain abnormalities, since this requires greater evidence than direct associations between retina and brain. We, therefore propose a new way to think about, and test, how clearly one might see the brain through the retinal window, using cerebral malaria as a case study.
Highlights
The appeal of the retina as a research tool There is a great temptation to describe the retina as a ‘window to the brain’
We summarize some of the more prominent approaches, with the aim of identifying statistical methods to investigate relationships between retina and brain within the context of a particular disease exposure and outcome (Table 1)
Careful attention must be given to the biological context within which retina–brain associations are being tested, since inadequate variable measurement, and the impact of unmeasured confounders could lead to misleading results
Summary
The appeal of the retina as a research tool There is a great temptation to describe the retina as a ‘window to the brain’. These considerations of what it might mean for the retina to be a window to the brain lead to a definition of equivalence that moves some way beyond existing analyses of prospective retinal biomarkers in terms of simple associations with brain variables or outcomes. The criteria of Wu et al [30] make use of data from previous RCTs, while VanderWeele’s questions [16] rely on a priori knowledge of relationships between treatment, surrogate and true outcome This takes us back to considering the importance of the biological context, and the plausibility of analogy between what is measurable (e.g., the surrogate, the model animal), and what we would like to know with certainty but can only infer (e.g., the true end point, human biology). On the other hand, employing information about the biological context to specify a fuller model structure may provide a way to both limit bias and test the goodness of fit for the hypothetical biological paradigm
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