Cheng WL, Markus C, Lim CY, Tan RZ, Sethi SK, Loh TP. Calibration Practices in Clinical Mass Spectrometry: Review and Recommendations.
Ann Lab Med 2023;
43:5-18. [PMID:
36045052 PMCID:
PMC9467832 DOI:
10.3343/alm.2023.43.1.5]
[Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 06/30/2022] [Accepted: 08/18/2022] [Indexed: 12/27/2022] Open
Abstract
Background
Calibration is a critical component for the reliability, accuracy, and precision of mass spectrometry measurements. Optimal practice in the construction, evaluation, and implementation of a new calibration curve is often underappreciated. This systematic review examined how calibration practices are applied to liquid chromatography-tandem mass spectrometry measurement procedures.
Methods
The electronic database PubMed was searched from the date of database inception to April 1, 2022. The search terms used were "calibration," "mass spectrometry," and "regression." Twenty-one articles were identified and included in this review, following evaluation of the titles, abstracts, full text, and reference lists of the search results.
Results
The use of matrix-matched calibrators and stable isotope-labeled internal standards helps to mitigate the impact of matrix effects. A higher number of calibration standards or replicate measurements improves the mapping of the detector response and hence the accuracy and precision of the regression model. Constructing a calibration curve with each analytical batch recharacterizes the instrument detector but does not reduce the actual variability. The analytical response and measurand concentrations should be considered when constructing a calibration curve, along with subsequent use of quality controls to confirm assay performance. It is important to assess the linearity of the calibration curve by using actual experimental data and appropriate statistics. The heteroscedasticity of the calibration data should be investigated, and appropriate weighting should be applied during regression modeling.
Conclusions
This review provides an outline and guidance for optimal calibration practices in clinical mass spectrometry laboratories.
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