Article: Using Sigma metrics to establish analytical product performance requirements and optimize analytical performance of an
2018 Volume 28, Issue 2, Page(s) 20903
Abstract: Introduction: Establishing analytical performance requirements for in vitro diagnostic (IVD) assays is a challenging process. Manufacturers try to optimize analytical performance by choosing amongst many combinations of different product performance ... ...
Abstract | Introduction: Establishing analytical performance requirements for in vitro diagnostic (IVD) assays is a challenging process. Manufacturers try to optimize analytical performance by choosing amongst many combinations of different product performance characteristics. Sigma metrics and method decision charts can be helpful aids in choosing appropriate analytical performance requirements. The objective of this research was to demonstrate the use of Sigma metrics and method decision charts to help establish analytical performance requirements and to optimize analytical performance at medical decision concentrations for an IVD assay. Materials and methods: A range of possible Sigma metrics were determined using three sources for total allowable error (TEa) and hypothetical total PSA assay results. Method decision charts were created for each TEa source and used to identify the maximum precision and bias that the assay could have to maintain sigma level performance of at least 3. Results: To achieve a sigma performance level of at least 3 for a hypothetical total PSA assay, the maximum allowable coefficient of variation ranged from 5.0% to 11.2% depending on the TEa source. To achieve a sigma performance level of at least 6, the maximum allowable coefficient of variation ranged from 2.5% to 5.6% depending on the TEa source. Conclusions: Using Sigma metrics and method decision charts when establishing analytical performance requirements can help manufacturers choose product requirements that will optimize IVD assay product performance. |
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MeSH term(s) | Bias ; Clinical Chemistry Tests ; Diagnosis ; Humans ; Prostate-Specific Antigen/analysis ; Research Design ; Total Quality Management |
Chemical Substances | Prostate-Specific Antigen (EC 3.4.21.77) |
Language | English |
Publishing date | 2018-06-30 |
Publishing country | Croatia |
Document type | Journal Article |
ZDB-ID | 1208725-7 |
ISSN | 1846-7482 ; 1330-0962 |
ISSN (online) | 1846-7482 |
ISSN | 1330-0962 |
DOI | 10.11613/BM.2018.020903 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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