TSH continuous reference intervals by indirect methods: A Comparisons to Partitioned Reference Intervals

To establish continuous reference intervals for TSH by data mining, using quantile regression with restricted cubic splines model. TSH results (n=13,333) were collected for a four years period (between March 2015 and February 2020). After an exclusion step, TSH results (n=8838) were used to derive c...

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Bibliographic Details
Published in:Clinical biochemistry 2020-11, Vol.85, p.53-56
Main Author: Mokhtar, Khelil Mohamed
Format: Article
Language:English
Subjects:
Abbott ARCHITECT i1000sr
Adolescent
Adult
Age Factors
Aged
Aged, 80 and over
Algeria
Bhattacharya analysis
Blood Chemical Analysis - standards
Female
Humans
Indirect continuous reference intervals
Male
Middle Aged
Quantile regression with restricted cubic splines
Reference Values
Regression Analysis
Thyrotropin - blood
Thyrotropin stimulating hormone (TSH)
Young Adult
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Summary:To establish continuous reference intervals for TSH by data mining, using quantile regression with restricted cubic splines model. TSH results (n=13,333) were collected for a four years period (between March 2015 and February 2020). After an exclusion step, TSH results (n=8838) were used to derive continuous reference intervals (i.e. 2.5th and 97.5th percentiles) spanning 18–90 years of age, using quantile regression with restricted cubic splines (RCS) model, then compared to age-partitioned reference intervals generated by Bhattacharya analysis. Despite similar reference intervals to the Bhattacharya analysis, continuous reference intervals appeared to give a more accurate and consistent estimation of the upper reference limits (i.e.97.5thpercentiles) with complex age-related variations in serum TSH concentrations. Our results suggest that quantile regression with RCS model appears to be a very useful tool available for clinical laboratories to establish local continuous TSH reference intervals.
ISSN:0009-9120
1873-2933
DOI:10.1016/j.clinbiochem.2020.08.003