A customizable calculation tool for allocation of adrenal vein sampling in primary aldosteronism in diverse populations

Abstract Background Primary aldosteronism(PA) screening is recommended but disease prevalence exceeds the availability of adrenal vein sampling(AVS). Methods An AVS optimal allocation tool for health systems was developed using administrative data and AVS registries from Calgary and Taiwan. Four easily-definable phenotypes of PA based on an elevated aldosterone-renin-ratio (ARR), and the presence/absence of hypokalemia or adrenal mass were identified, representing progressively severe PA and stepwise increasing rates of AVS-defined lateralization. Using supply-and-demand principles, a customizable, web-based tool was developed that considers PA referral volume, PA phenotype prevalence, maximum AVS available/year, AVS success rate, and desired rate of finding unilateral disease. Results The most prevalent phenotype of PA was characterized by an elevated ARR and hypokalemia but no adrenal mass (41.9 [39.9–43.9]%); hypokalemia and adrenal mass accounted for (15.6[14.4-16.9]%) of cases. There was a progressive increase in AVS lateralization rate with increasing severity of phenotype observed in both the Calgary and Taiwan data, ranging from (20-39%) in those with PA without hypokalemia or adrenal mass to (70-90%) in those with hypokalemia and adrenal mass. After accounting for institution-specific lateralization rates and allowing for system-level differences in high- and low-volume PA referrals, and high- and low AVS availability, the customizable AVS allocation tool was able to generate individualized strategies ranging from restrictive (exclusive reservation of AVS for cases with hypokalemia and adrenal mass) to more inclusive strategies (assigning a proportion of AVS allocation to less severe PA cases). Conclusions An AVS allocation tool that uses common, simple, and globally available PA case data may assist in health system AVS program case allocation for maximum equity and wait-list control. GRAPHICAL ABSTRACT