refineR: A Novel Algorithm for Reference Interval Estimation from Real-World Data

Ammer T, Schuetzenmeister A, Prokosch HU, Rauh M, Rank CM, Zierk J (2021)

Publication Type: Journal article

Publication year: 2021

Journal

Scientific Reports Nature Publishing Group: Open Access Journals - Option B

Book Volume: 11

Article Number: 16023

Journal Issue: 1

DOI: 10.1038/s41598-021-95301-2

Abstract

Reference intervals are essential for the interpretation of laboratory test results in medicine. We propose a novel indirect approach to estimate reference intervals from real-world data as an alternative to direct methods, which require samples from healthy individuals. The presented refineR algorithm separates the non-pathological distribution from the pathological distribution of observed test results using an inverse approach and identifies the model that best explains the non-pathological distribution. To evaluate its performance, we simulated test results from six common laboratory analytes with a varying location and fraction of pathological test results. Estimated reference intervals were compared to the ground truth, an alternative indirect method (kosmic), and the direct method (N = 120 and N = 400 samples). Overall, refineR achieved the lowest mean percentage error of all methods (2.77%). Analyzing the amount of reference intervals within ± 1 total error deviation from the ground truth, refineR (82.5%) was inferior to the direct method with N = 400 samples (90.1%), but outperformed kosmic (70.8%) and the direct method with N = 120 (67.4%). Additionally, reference intervals estimated from pediatric data were comparable to published direct method studies. In conclusion, the refineR algorithm enables precise estimation of reference intervals from real-world data and represents a viable complement to the direct method.

Authors with CRIS profile

Tatjana Ammer Lehrstuhl für Medizinische Informatik Hans-Ulrich Prokosch Lehrstuhl für Medizinische Informatik Manfred Rauh Department of Paediatrics and Adolescent Medicine Jakob Zierk Department of Paediatrics and Adolescent Medicine

Involved external institutions

Roche Diagnostics GmbH DE Germany (DE)

How to cite

APA:

Ammer, T., Schuetzenmeister, A., Prokosch, H.-U., Rauh, M., Rank, C.M., & Zierk, J. (2021). refineR: A Novel Algorithm for Reference Interval Estimation from Real-World Data. Scientific Reports, 11(1). https://doi.org/10.1038/s41598-021-95301-2

MLA:

Ammer, Tatjana, et al. "refineR: A Novel Algorithm for Reference Interval Estimation from Real-World Data." Scientific Reports 11.1 (2021).

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