The Lone Dissenter


The picture is a photo of Linda Thienpont receiving the Westgard quality award, presented by Jim Westgard. This was a highlight of the Antwerp meeting in which Linda’s contributions to laboratory medicine were recognized.



I was amused to see a photo on the Westgard blog about the Antwerp conference – Quality in the Spotlight. The photo is incidental to the blog content – it shows people holding up green cards with the exception of one person holding up a red card. It’s hard to see the person holding up the red card, but it’s me! So this was voting by the attendees to some questions asked by the convener – Henk Goldschmidt – at the end of the day’s session.

The question to which everyone agreed except me went something like – “should analytical variation always be less than biological variation”

So here’s my reason for dissenting.

The Ricos database for glucose, available on the Westgard website, lists the TAE for glucose at either 5.5% or 6.96%. Yet, the 2013 ISO 15197 performance standard for glucose meters is: TAE (95% of Results) ± 15 mg/dL below 100 mg/dL and ± 15% above 100 mg/dL. Hence, the answer to the question should analytical variation always be less than biological variation is no!

In my one man Milan response paper (subscription required) to the Milan conference, I had a section discussing the merits of biological variation vs. clinician opinion but dropped it in the final version. But this material was in the Antwerp conference – basically I said, I understand the rationale behind biological variation and it makes sense to me but I don’t see how biological variation can trump clinician opinion and glucose meters was the example I used.

I note in passing that Callum Fraser, the guru of biological variation, was in the audience – he presented earlier in the day a fabulous historical overview of biological variation. During his presentation I was nevertheless struck by some of the equations used for biological variation. For example, one of the equations was

CV < ½ CV within-subject biological variation

So why is it exactly 0.5? Why not 0.496 or 0.503? And how can it be 0.5 for all assays? Is there something about the 0.5 that is like pi?


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