Indirect derivation of biological variation data and analytical performance specifications for therapeutic drug monitoring activities

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Chai, Jia Hui
Flatman, Robert
Teis, Benjamin
Sethi, Sunil Kumar
Badrick, Tony
Loh, Tze Ping
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2019
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Abstract

We applied the indirect approach using anonymised data from an Australian and a Singapore laboratory to derive biological variation data for a group of 10 therapeutic drugs routinely monitored. A series of inclusion and exclusion criteria were applied on the data. The within- (CVi) and between-individual (CVg) biological variation data were then derived as previously described. The corresponding index of individuality and analytical performance specifications were also calculated. The biological variation data were overall very similar between the two study sites. Moreover, the biological variation data were also comparable between males and females, as well as whether the data originated from patients who only had two episodes of measurement during the study period or from the last two results from patients who had more than two episodes of measurement during the study period. The results presented in this study contribute towards the biological variation data for therapeutic drugs, which can be used to inform discussions about the setting of harmonised analytical performance specifications for these measurands.

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Pathology

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51

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3

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Clinical sciences

Science & Technology

Life Sciences & Biomedicine

Pathology

Therapeutic drug monitoring

biological variation

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Chai, JH; Flatman, R; Teis, B; Sethi, SK; Badrick, T; Loh, TP, Indirect derivation of biological variation data and analytical performance specifications for therapeutic drug monitoring activities, Pathology, 2019, 51 (3), pp. 281-285

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