Determination of quality control limits for serological infectious disease testing using historical data

作者：Dimech Wayne^*; Vincini Giuseppe; Karakaltsas Marina

来源：Clinical Chemistry and Laboratory Medicine, 2015, 53(2): 329-336.

DOI：10.1515/cclm-2014-0546

• control limits
• infectious diseases
• QConnect
• quality control
• serology

Background: An effective quality control (QC) program requires the establishment of control limits within which the results of the QC sample is expected to fall. Traditionally, the mean plus/minus two standard deviations calculated for a set of QC sample results is used to establish control limits. Allowable total error (TEa) and Westgard rules aid in interpreting QC sample results. Westgard rules assume QC sample results are normally distributed and TEa assumes commutability between the QC sample and patient results. None of these paradigms apply to infectious disease testing.
Methods: Results from the NRL's QC program were extracted and sorted into assay/QC lot number-specific data. Control limits for selected QC samples used to monitor 64 commonly used serological assays were calculated and validated using the within- and between-QC lot variance of data from each of the assay/QC combinations.
Results: No assay/QC combination had more than 10% of results less than the lower control limit or greater than the upper control limit. Of the 423 assay/QC lot combinations, 14 (3.3%) had more than 5% of results less than the lower limit and 48 (11.3%) had more than 5% of results greater than the upper limit calculated for that assay/QC combination.
Conclusions: The control limits, established by this novel method, are based on more than a decade of QC test results from >300 laboratories from 30 countries and provides users of the NRL QC program evidence-based control limits that can be applied in isolation or in conjunction with more traditional methods for establishing control limits.

• 出版日期2015-2