Monday, July 4, 2016

Global screening - take 2 - doubling down.

Since my previous post triggered some poor responses (especially by mail) and I am a guy that's always willing to be on the receiving end of a good beating, let's take another angle.The purpose of widespread finger pricking is to avoid late diagnosis and save lives. Definitely a commendable goal. The question here is essentially

"how do we improve the initial diagnosis so we can avoid death by DKA at or near diagnosis time"

That is a valid question, and everyone would like to diminish the mortality/morbidity toll, even if it is not very large.

A few additional numbers

There were roughly 208.000 practicing primary care physicians in the US in 2009-2010 (reference U.S. Department of Health & Human Services)

There were 18.436 under twenty diagnosed with Type 1 diabetes in 2008-2009 (reference Center for Disease Control), roughly 30.000 if one includes adults.

Assuming all diagnosis are made by primary case physicians, which would be a wildly optimistic view and precisely the issue promoters of the "blood test for everyone" idea would like to address, that means that our hypothetical average primary care physician is confronted with a diagnosis situation once every 11.28 years in an under twenty kid and once every 6.93 years for the whole population. If the diagnosis is missed in 50% of the cases, double those numbers.

On average, this means that what was, for you, one of the single most important event of your life is an extremely rare occurrence for the physician you encountered. A GP will probably remember forever the 3 or 4 initial T1D diagnosis he made over his career.

Would additional training help dealing with such a rare event? To be honest, I am not sure.

Assume I am a genius

I've already talked about how hard it would be to diagnose T1D based on a single BG Meter reading. Let's however assume that I am a genius, Theranos style, and that I invent a method that, with a single cheap finger prick is almost perfect at diagnosing Type 1 Diabetes before the patient falls in DKA. I can already imagine how my TED talk would go: a summary of the issue, a couple of dramatic images of immensely cute kids killed or handicapped by severe DKA, the description of how my almost perfect method works, simultaneously dosing all antibodies, blood sugar and eventual other markers of Beta cells demise. I'll conclude my speech with the image of a cute healthy kid walking an open path, symbolizing his bright future, in a nice postcard landscape. Then, I will enjoy the standing ovation.

My perfect test would be the perfect solution to the problem, right?


But things aren't as bright as they seem.

Imagine my test is essentially perfect at finding all Type 1 Diabetics (in other word 100% sensitive) and almost perfect at detecting Type 1 Diabetics in a general population. We'll say that it is 99.9% specific, which means that it will only flag 0.1% of the healthy population as having Type 1 Diabetes.

100% sensitivity and 99.9% specificity are unheard of in the area of biological testing, but hey, I told you we are assuming I am a genius...

Let's now apply this test to the 320.000.000 yearly primary care under twenty visits in the US that we estimated earlier. We can drop the visits by identified type 1 diabetics, they wouldn't do the test anyway and assume that we score 100% detection on the 18.436 unidentified Type 1 Diabetics.

Let's again be generous with numbers and assume that out of these 320.000.000 visits, 20.000.000 are by known T1Ds and that, again 150.000.000 of the remaining visits are clear enough that they don't require any kid of testing (but of course, the GP could be wrong here as well)

My "almost perfect" test would still flag 0.1% of those healthy visits as definitely Type 1 Diabetics (for example because of the presence of similar molecules).

The scoreboard would now look like this.

  • 18.436 T1Ds correctly and immediately diagnosed.
  • 150.000 non T1D patients wrongly identified as T1Ds
One other way of looking at my perfect test would be to say that it is wrong 89% of the time and correct 11% of the time.
If a BG meter was correct 99% of the time, it would miss 184 real Type 1 Diabetics and flag no less than 1.500.000 visits as probable Type 1 Diabetics.

Of course in real life, things don't work that way, and fortunately so. Your MD is not a total idiot. He would put results in context, retest any suspicious results. But that would not prevent a lot of useless double checks and additional procedures carried out on non T1D people.

So much for that bright idea... I am not a genius and, even if I was, it wouldn't work too well.

The narrative "We did a BG meter test, found 450 mg/dL, double checked and saved the life of the kid" is extremely seductive but quite unlikely in practice. The odds are slightly higher than winning a significant payout at a lottery, but not high. And it will come at the cost of a lot of false positives which will also cause worries and distress to the falsely suspect kid, put his family under stress and trigger automatic additional tests (maybe a day off at work?) or investigations that carry their own risks.

Back of the envelopes computations certainly aren't the final word. They certainly do not prove that the system can not be improved. But they can definitely prove that something like a car will not fly to the moon...

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