Reference Intervals Revisited: A Novel Model for Population-Based Reference Intervals, Using a Small Sample Size and Biological Variation Data

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Abstract
Background: Conventional population-based reference intervals (popRIs) are established on the ranking of single measurement results from at least 120 reference individuals. In this study, we aimed to explore a new model for popRIs, utilizing biological variation (BV) data to define the reference interval (RI) limits and compared BV-based popRI from different sample sizes with previously published conventional popRIs from the same population. Methods: The model is based on defining the population set point (PSP) from single-measurement results of a group of reference individuals and using the total variation around the PSP, derived from the combination of BV and analytical variation, to define the RI limits. Using data from 143 reference individuals for 48 clinical chemistry and hematology measurands, BV-based popRIs were calculated for different sample sizes (n = 16, n = 30, and n = 120) and considered acceptable if they covered 90% of the population. In addition, simulation studies were performed to estimate the minimum number of required reference individuals. Results: The median ratio of the BV-based to conventional RI ranges was 0.98. The BV-based popRIs calculated from the different samples were similar, and most met the coverage criterion. For 25 measurands ≤16 reference individuals and for 23 measurands >16 reference individuals were required to estimate the PSP. Conclusions: The BV-based popRI model delivered robust RIs for most of the included measurands. This new model requires a smaller group of reference individuals than the conventional popRI model and can be implemented if reliable BV data are available.

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