R epeated measurements of systolic blood pressure (SBP) and diastolic blood pressure (DBP) frequently show a highly linear relationship. This phenomenon was observed in the Framingham study over a 14-year period using office blood pressure (BP) measurement, in-home BP monitoring over a few weeks, 24-h ambulatory blood pressure measurement (ABPM) and beat-by-beat BP monitoring over a few minutes. The standard statistical measures of this linear relationship are the regression slope and the SBP-DBP correlation coefficient r. The currently used slope-related measures are (a) the regression slope obtained by treating the DBP as an independent variable, hereafter called the S-D slope, after Gavish et al., 1 and (b) one minus the regression slope, calculated by treating the SBP as the independent variable, called the Arterial Stiffness Index (ASI), after Li et al. 2 However, the determination of sloperelated measures using standard regression leads to artifactual dependence on r; that is, the slope becomes dependent on the degree of data scattering. The reason for this is that the SBP and the DBP are measured simultaneously, and neither variable can be described as 'dependent' or 'independent' . This problem is eliminated by using 'symmetric regression' , which handles both variables in a symmetrical way. 1,3 Figure 1 demonstrates why this issue becomes important when attempting to estimate slope-related measures.