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Department of Endocrinology, Austin Health, Melbourne, Australia
Division of Endocrinology, Diabetes and Metabolism, Northwell, Great Neck, New York, USA
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Department of Cardiology, Austin Health, Melbourne Australia
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Olivia Newton-John Cancer Research Institute, Austin Health, Melbourne, Australia
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Department of Endocrinology, Austin Health, Melbourne, Australia
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Department of Endocrinology, Austin Health, Melbourne, Australia
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Purpose
We previously demonstrated that 12 months of aromatase inhibitor (AI) treatment was not associated with a difference in body composition or other markers of cardiometabolic health when compared to controls. Here we report on the pre-planned extension of the study. The pre-specified primary hypothesis was that AI therapy for 24 months would lead to increased visceral adipose tissue (VAT) area when compared to controls.
Methods
We completed a 12-month extension to our prospective 12-month cohort study of 52 women commencing AI treatment (median age 64.5 years) and 52 women with breast pathology not requiring endocrine therapy (63.5 years). Our primary outcome of interest was VAT area. Secondary and exploratory outcomes included other measures of body composition, hepatic steatosis, measures of atherosclerosis and vascular reactivity. Using mixed models and the addition of a fourth time point, we increased the number of study observations by 79 and were able to rigorously determine the treatment effect.
Results
Among study completers (AI = 39, controls = 40), VAT area was comparable between groups over 24 months, the mean-adjusted difference was −1.54 cm2 (95% CI: −14.9; 11.9, P = 0.79). Both groups demonstrated parallel and continuous increases in VAT area over the observation period that did not diverge or change between groups. No statistically significant difference in our secondary and exploratory outcomes was observed between groups.
Conclusions
While these findings provide reassurance that short-to-medium-term exposure to AI therapy is not associated with metabolically adverse changes when compared to controls, risk evolution should be less focussed on the AI-associated effect and more on the general development of cardiovascular risk over time.
