Abstract
Sample Adequacy Control (SAC) has critical analytical, clinical and epidemiological value that increases confidence in a negative test result. The SAC is an integral qPCR assay control, which ensures that all pre-analytical and analytical steps are adequate for accurate testing and reporting. As such, a negative SAC with a negative result on pathogen screen specifies that the result should be reported as inconclusive instead of negative. Despite this, many regulatory approved tests do not incorporate SAC into their assay design. Herein, we emphasize the universal value of SAC and offer for the first time, a simple technical strategy to introduce non-competitive SAC which does not interfere with the limit of detection for the screened pathogen. Integration of SAC can provide key benefits towards identifying, isolating, quarantining and contact tracing infected individuals and in turn can improve worldwide efforts in infection control.
Highlights
Sample adequacy control (SAC) is a “built-in check” to ensure that the sample is suitable and meets the requirements for testing [1–6]
Even assays with the most optimal analytical performance can yield false negative (FN) results: e.g., when sampling is inadequate, or the integrity of the sample is compromised during transportation and/or storage, when the assay is inhibited, or when there is any other pre-analytical manipulation compromising the accuracy of reported results [2,8–11]
Due to the multitude of bacterial genomic nucleic acids, the control-assay reaction could not be placed in the same compartment as the pathogen-specific assay
Summary
Sample adequacy control (SAC) is a “built-in check” to ensure that the sample is suitable and meets the requirements for testing [1–6]. Even assays with the most optimal analytical performance can yield FN results: e.g., when sampling is inadequate (below the minimal quantity of biological material collected), or the integrity of the sample is compromised during transportation and/or storage, when the assay is inhibited, or when there is any other pre-analytical manipulation compromising the accuracy of reported results [2,8–11]. These can be largely mitigated by streamlined and effective testing pipelines, the need for sample adequacy controls become critically essential, as testing volumes increase, when sample types become diverse and when self-sampling strategies become incorporated into testing algorithms. Removing even a small fraction of FN samples will allow for improvement in infection control measures and a more rapid and safer loosening of restrictions and the recommencement of essential, social and economic activities
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