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Nevin Manimala Statistics

Quality control validation for a veterinary laboratory network of six Sysmex XT-2000iV hematology analyzers

Vet Clin Pathol. 2022 Aug 3. doi: 10.1111/vcp.13163. Online ahead of print.

ABSTRACT

BACKGROUND: Quality control (QC) validation is an important step in the laboratory harmonization process. This includes the application of statistical QC requirements, procedures, and control rules to identify and maintain ongoing stable analytical performance. This provides confidence in the production of patient results that are suitable for clinical interpretation across a network of veterinary laboratories.

OBJECTIVES: To determine that a higher probability of error detection (Ped ) and lower probability of false rejection (Pfr ) using a simple control rule and one level of quality control material (QCM) could be achieved using observed analytical performance than by using the manufacturer’s acceptable ranges for QCM on the Sysmex XT-2000iV hematology analyzers for veterinary use. We also determined whether Westgard Sigma Rules could be sufficient to monitor and maintain a sufficiently high level of analytical performance to support harmonization.

METHODS: EZRules3 was used to investigate candidate QC rules and determine the Ped and Pfr of manufacturer’s acceptable limits and also analyzer-specific observed analytical performance for each of the six Sysmex analyzers within our laboratory system using the American Society of Veterinary Clinical Pathology (ASVCP)-recommended or internal expert opinion quality goals (expressed as total allowable error, TEa ) as the quality requirement. The internal expert quality goals were generated by consensus of the Quality, Education, Planning, and Implementation (QEPI) group comprised of five clinical pathologists and seven laboratory technicians and managers. Sigma metrics, which are a useful monitoring tool and can be used in conjunction with Westgard Sigma Rules, were also calculated.

RESULTS: The QC validation using the manufacturer’s acceptable limits for analyzer 1 showed only 3/10 measurands reached acceptable Ped for veterinary laboratories (>0.85). For QC validation based on observed analyzer performance, the Ped was >0.94 using a 1-2.5s QC rule for the majority of observations (57/60) across the group of analyzers at the recommended TEa . We found little variation in Pfr between manufacturer acceptable limits and individual analyzer observed performance as this is a characteristic of the rule used, not the analyzer performance.

CONCLUSIONS: An improved probability of error detection and probability of false rejection using a 1-2.5s QC rule for individual analyzer QC was achieved compared with the use of the manufacturers’ acceptable limits for hematology in veterinary laboratories. A validated QC rule (1-2.5s) in conjunction with sigma metrics (>5.5), desirable bias, and desirable CV based on biologic variation was successful to evaluate stable analytical performance supporting continued harmonization across the network of analyzers.

PMID:35922888 | DOI:10.1111/vcp.13163

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