Abstract
PATIENTS AND METHODS
Between 2005 and 2014, 4,622 participants from the prospective population-based Rotterdam Study who were free of cancer, dementia, and stroke, underwent brain MRI and were subsequently followed for incident cancer until January 1st, 2015. We investigated the association between brain MRI measurements, including cerebral small vessel disease, volumes of global brain tissue, lobes, and subcortical structures, and global white matter microstructure, and the risk of non-CNS cancer using Cox proportional hazards models. Age was used as time scale. Models were corrected for e.g. sex, intracranial volume, educational level, body mass index, hypertension, diabetes mellitus, smoking status, alcohol use, and depression sum-score.
CONCLUSION
We did not observe associations between small vessel disease, brain tissue volumes, and global white matter microstructure, and subsequent cancer risk in an unselected population. These findings deviate from previous studies indicating brain abnormalities among patients shortly after cancer diagnosis.
RESULTS
During a median (interquartile range) follow-up of 7.0 years (4.9-8.1), 353 participants were diagnosed with non-CNS cancer. Results indicated that persons who develop cancer do not have more brain abnormalities before clinical manifestation of the disease than persons who remain free of cancer. The largest effect estimates were found for the relation between presence of lacunar infarcts and the risk of cancer (hazard ratio [HR] 95% confidence interval [CI] = 1.39 [0.97-1.98]) and for total brain volume (HR [95%CI] per standard deviation increase in total brain volume = 0.76 [0.55-1.04]).
PURPOSE
Many studies have shown that patients with non-central nervous system (CNS) cancer can have brain abnormalities, such as reduced gray matter volume and cerebral microbleeds. These abnormalities can sometimes be present even before start of treatment, suggesting a potential detrimental effect of non-CNS cancer itself on the brain. In these previous studies, psychological factors associated with a cancer diagnosis and selection bias may have influenced results. To overcome these limitations, we investigated brain structure with magnetic resonance imaging (MRI) prior to cancer diagnosis.