Quality Control

There are several approaches to laboratory quality control (QC) issues, and the lab collaborator should provide clear, written plans about how QC will be assessed. Some typical techniques include:

 

  • running the assay in duplicate on all or some percentage of randomly selected specimens to see if the results are consistent.
  • placing laboratory-created specimens with known existence or quantity of the marker of interest in a batch of specimens for assay so that laboratory staff do not know which specimens are known positive or negative samples.
  • collecting enough of a particular specimen from non-study participants to allow assay of multiple aliquots; then, including one of these aliquots with each batch of research subject specimens being assayed to determine the reliability of the assay across batches. This approach assumes little delay in assaying of batches; otherwise, it is necessary to consider degradation of specimen from storage (see next item).
  • re-assaying some specimens with each batch over time, e.g., at 6-month intervals, to determine whether there is a degradation of the assay results due to prolonged storage.

What if repeated assays of the same specimen lead to different results?

When duplicates are run or when the researcher decides to have another lab re-run assays and the results are significantly different, it is important to talk with the lab director to get a recommendation on how the results should be interpreted. There may be a clear explanation, or there may be problems with the lab procedures.

What results will the lab report, especially if they are doing duplicate runs (all results, the average, the outliers)?

It is common for a lab to run duplicates of assays on all or a subset of specimens, and there are often cutpoints above which a lab automatically re-runs the assay. Each of these tests yields a new result for the specimen, and it is important to discuss with the lab ahead of time which of these values you will receive. Often labs will report only what they consider to be the final determination after any re-assessments. The project researchers may want to see all values and run their own checks on how discrepant these values are.

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