Matrix Effects (and CLSI EP14-A2)

Here’s my problem with matrix effects using an oversimplified and somewhat not real example.

Take a glucose assay. If hemoglobin in a patient sample causes a signal and provides a biased glucose result, the hemoglobin is called an interference.

But if a control were to cause a biased glucose result due to the same amount of hemoglobin in the control, the control would be said to have a matrix effect. (I know that hemoglobin doesn’t interfere that much but I wanted to avoid using compound X.)

Note that the definition of a matrix effect, given in EP14-A2 is synonymous with the definition of an interfering substance. (There is no definition of an interfering substance or its strange ISO cousin “influence quantity” in EP14-A2.) But in the text of EP14-A2, a matrix effect is defined as a material which does not behave as fresh human specimens.

Yet, in the above case, the control is acting identically to a human specimen.

Now I know that what people really mean by matrix effects in controls is that either the processing of the control or something added to the control (such as a preservative) that does not occur in fresh human specimens, and causes interferences.

But the experiment in EP14-A2 does not distinguish between artificial and natural interferences. So it is possible that differences in results between controls and patient specimens are due to substances that occur in human specimens, substances that don’t occur in human specimens or a combination.

Unless a method can distinguish between artificial and natural interferences, the assay is as suspect as the control.


Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s

%d bloggers like this: