Background: The concept of personalized medicine has received widespread attention in the last decade. However, personalized medicine depends on correct diagnosis and monitoring of patients, for which personalized reference intervals for laboratory tests may be beneficial. In this study, we propose a simple model to generate personalized reference intervals based on historical, previously analyzed results, and data on analytical and within-subject biological variation.
Methods: A model using estimates of analytical and within-subject biological variation and previous test results was developed. We modeled the effect of adding an increasing number of measurement results on the estimation of the personal reference interval. We then used laboratory test results from 784 adult patients (>18 years) considered to be in a steady-state condition to calculate personalized reference intervals for 27 commonly requested clinical chemistry and hematology measurands.
Results: Increasing the number of measurements had little impact on the total variation around the true homeostatic set point and using ≥3 previous measurement results delivered robust personalized reference intervals. The personalized reference intervals of the study participants were different from one another and, as expected, located within the common reference interval. However, in general they made up only a small proportion of the population-based reference interval.
Conclusions: Our study shows that, if using results from patients in steady state, only a few previous test results and reliable estimates of within-subject biological variation are required to calculate personalized reference intervals. This may be highly valuable for diagnosing patients as well as for follow-up and treatment.
Keywords: analytical variation; biological variation; reference interval.
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