The Westgard Rules

What's New: October 2016

Posted by Sten Westgard, MS

Here's what's new on Westgard Web...

Still bothered by Bias

One of the perennial debates about quality is what to do about bias. Metrologists would prefer that it didn't exist. They want to stamp it out whenever and wherever it is found. It's a laudable mission, but what if the methods on the marketplace are currently unable to be standardized, harmonized, and/or calibrated so that the bias is pushed to zero?  A recent Clinical Chemistry study found unacceptably large biases in 4 out of 5 common immunoassays: cobalamin, folate, ferritin, TSH, and Free T4. 

When methods have major bias, are Sigma-metrics more forgiving?

---

AB...C. And Bias exists with Cortisol, too

Yet another study in Clinical Chemistry took a deep dive into the bias present in different patient cohorts for common Cortisol methods. When there are significant differences in males, females, (pregnant and non-pregnant), laboratories and clinicians need to make sure they don't make one judgment on a method when there are multiple dimensions to consider.

If Bias is Bad for females, but okay for males, should we accept the method? (Isn't that biased?)
 

 

---

INVITRO Labs achieves Sigma Verification

The first laboratory in Russia, INVITRO Labs headquartered in Moscow, achieved verification of their chemistry performance in early October.



INVITRO Laboratories Sigma Verification of Performance
 

---

Guizhou Provincial People's Hospital achieves Sigma Verification

In mid-October, the first hospital in China was able to receive their verification of Sigma performance. Located in Guiyang City of Guizhou Province, this hospital commenced work earlier this year and finished their training and verification in short order.



Guizhou Provincial People's Hospital Sigma Verification of Performance

 

Q & A: The basis of bias%?

Posted by Sten Westgard, MS

One of our members sent in a question about bias. This time, for once, it wasn't about finding the right source for bias (such as a peer group mean, or a reference method mean, etc.). This was much more basic: how do we calculate bias?

If we express the difference between the target mean and the observed lab mean as a bias, what is the denominator? Is it the target mean or the lab mean?

Perhaps it's helpful if we get more specific

 

Target mean	Observed mean	Unit Bias	Bias% of Target	Bias% of Observed
100	150	50	50%	33.3%
100	200	100	100%	50%
100	250	150	150%	60%
100	300	200	200%	66.6%
100	350	250	250%	71.4%

You can see that as the observed mean gets farther away from the target mean, the difference between the bias% using the target mean in the denominator gets larger and larger from the bias% using the observed mean in the denominator.

So in practice, we prefer to use the target mean as the denominator in the calculation of bias%. Since that's what we're comparing against, we're making a presumption, at least a small one, that this is the value we should be hitting, so any bias is in context, reference to, that target.

In practice, we also rarely see biases get so large. For most of the analytes we deal with, a bias of even 30% becomes untenable, regardless of how it's calculated. When we have very small biases, the differences in calculated bias% from target and observed mean are often insignificant.

Nevertheless, this phenomenon has led some to recommend keeping the bias in units and to make any calculations for Sigma-metrics based on units, not percentage based calculations. When carefully handled, however, the calculations come out the same.

Keep those questions coming!

Theranos Bleeds out...

Posted by Sten Westgard, MS

Well the horn is off the unicorn. (A unicorn, in Silicon Valley parlance, is a startup with a billion dollar valuation). In the wake of a presentation at the AACC/ASCLS annual conference that was almost universally panned, Theranos continued its downward slide, until in October it pulled the plug on its direct laboratory testing business. Now it is "refocusing" on developing its new MiniLab, a smaller POC device that seems far less revolutionary than the lofty claims once put forth. If Theranos is just another POC device company, it's overvalued.

For some analytical analysis of the first performance claimed by the MiniLab, check out this LinkedIn post (subscription required).

Also, I recommend this article from WSJ: Dubious test results from Theranos hurt patients, and some didn't get corrected results for months https://lnkd.in/bu9er7N If you read carefully, you might see someone familiar get quoted...

Belated Pictures from Philadelphia

Posted by Sten Westgard, MS

It's overdue, but here are a few pictures of the AACC/ACSLS conference in Philadelphia.

Dr. Nils Persons from Siemens and I taught the Mehod Verification and Validation workshops again this year, continuing in a nearly 40 year tradition. The longest-running training provided by AACC, and this year it was full of topical discussions of companies like Theranos.

A class of CLS students from Neumann University, courtesy of Dr. Patricia Fallest-Strobl

 

Director of Wellness Selenda Warden certainly made us feel better when she stopped by the booth.

Thanks to all who visited. Hope to see you in San Diego next year.

New chapter: finding and fixing the error of our testing ways

Posted by Sten Westgard, MS

I'm a bit late in calling attention to this, but the latest edition of Contemporary Practice in Clinical Chemistry has a chapter on method validation and verification that I co-authored along with Dr. Dave Koch, the Past President of AACC.

For a short one chapter discussion of method validation and verification, this is the current best choice.

This is one of those thoroughly comprehensive textbooks and for AACC members it's available at a substantial discount.

https://www.aacc.org/store/books/11100/contemporary-practice-in-clinical-chemistry-3rd-edition