An Investigation into Outlier Elimination and Calculation Methods in the Determination of Reference Intervals using Serum Immunoglobulin A as a Model Data Collection

Abstract

Background: Reference intervals are essential to interpret diagnostic tests, but their determination has become controversial. Methods: In this paper parametric, non-parametric and robust reference intervals with Tukey and block elimination are calculated from a dataset of over 32,000 serum immunoglobulin A (IgA) measurements. Results: The outlier elimination method was significantly more determinative of the reference intervals than the calculation method. The Tukey elimination procedure consistently eliminated significantly more values than the block method of Dixon and Reed across all age ranges. If Tukey elimination was applied, variation between reference intervals produced by the different calculation methods was minimal. Block elimination rarely eliminated values. The non-parametric reference intervals were more sensitive to outliers, which in the IgA context, led to higher and wider reference intervals for the older age groups. There were only minimal differences between robust and parametric reference intervals. Conclusions: This suggests that Tukey elimination should be preferred over the block D/R method for datasets similar to the one used in this study. These are predominantly new observations, as previous literature has focused on the calculation technique and not discussed outlier elimination. This suggests the robust method is not advantageous over the parametric method and therefore due to its complexity is not particularly useful, contrary to CLSI Guidelines.