Response to “Oral Chaperone Therapy Migalastat for the Treatment of Fabry Disease: Potentials and Pitfalls of Real‐World Data”

To the Editor: We thank Dr Körver and colleagues for their interest in our work. We absolutely agree that validity of current amenability criteria arguably might still be subject to discussion. From the clinical viewpoint, the cutoff values of 1.2fold relative and 3% absolute increase in alpha galactosidase activity chosen in the recent multicenter trials might be questionable particularly in patients with polymorphismlike genotypes, such as the benign variant D313Y, presenting with nearnormal wild-type enzyme activity but currently still categorized as amenable. Limitations in knowledge on the genotypedependent absolute and relative changes in enzyme activity in the clinical setting, and the question which cutoff value might be most suitable to forecast therapy success, represent a clinical dilemma for the treating physicians. This was one of the main drivers for execution of the current investigations. Given the exceptional bandwidth of genotypes and phenotypes in Fabry disease, it is not surprising that not only chaperone therapy but also alternative specific treatment options—namely enzyme replacement but also substrate reduction therapy—have shown marked variance in individual patients’ treatment response. However, we disagree with the claim that lysoGb3 represents the ideal biomarker to determine amenability or therapy success, and neither can support the hypothesis that an increase in lysoGb3 in one patient switched from enzyme replacement therapy to migalastat verifies nonamenability in this particular mutation or even patient. Obviously, as also pointed out by Dr Körver et al., laboratory as well as imaging biomarkers, such as left ventricular mass derived by echocardiography, can show substantial variability over time. Importantly, such variance does not necessarily reflect methodological limitations or measurement errors, but at least in part can be explained by varying biological parameters, which often strongly affect numerical data even when extreme care is taken to avoid any technical bias. With regard