Dan Morgan Profile picture
21 Dec, 20 tweets, 12 min read
We set out to identify the sensitivity & specificity of common tests for #COVID19 along w/ @dan_diekema , @Anthony98947615 w/ @CDCgov support

A simple enough task, right?

I’ve seen tweets by @DrSidMukherjee @drjohnm @BenMazer @PaulSaxMD @BradSpellberg and others interested
1/n
Looking for comments/criticism

What are we missing? No industry adverts please!

Important papers?
2/n
The @US_FDA has a test comparison site that is incomprehensible to me… but @ASMicrobiology types tell me it reports on analytical sensitivity and LoD for tests
3/n
First, terms:
As a clinician, I want to know if a patient does or doesn’t have #covid19.
I’m less concerned by internal laboratory QA unless it translates
We wanted what has been called CLINICAL or diagnostic sensitivity/ specificity NOT analytical sen/sp.
4/n
Described in 1997:
Clinical “diagnostic sensitivity is defined by the percentage of persons who have the disorder of interest who have positive results on the assay”

And more recently early in COVID by @akesselheim

nejm.org/doi/full/10.10…

5/n
Another note, PCR has largely been the laboratory gold standard.

So, most reports are for sen/sp relative to PCR—not to a clinical gold standard.

We adjusted reported results to reflect:
e.g. PCR Sen 90% x Antigen Sen of 50% = overall antigen Sen of 45%

6/n
Finally, we are NOT talking about being infectious for #covid19.
That is another topic with even LESS data I hope to share soon.
Suffice to say, many people with #COVID19 disease are NOT infectious, especially after a week or 10 days, but some tests still +, esp PCR

7/n
PCR—the gold standard
Clinical sensitivity ~ 90% on day 4 of symptoms w/ common instruments
sciencedirect.com/science/articl…

dx.plos.org/10.1371/journa…

jcm.asm.org/content/58/8/e…

academic.oup.com/ofid/article-a…

8/n
-earlier reports of lower PCR sensitivity had atypical gold standard or were not reporting optimal sampling on day 4

-Sensitivity IS lower before/ after day 4 of symptoms per acpjournals.org/doi/10.7326/M2…

9/n
Reasons for PCR false-negatives (10% false – rate)

lack of virus in sampling site
inadequate sampling
lack of instrument optimization or variation between instruments

10/n
PCR Clinical Specificity ~99%
this was hard!
Scant data, authors suggest between 95%-99.5%

bmj.com/content/369/bm…
gov.uk/government/pub…
cdc.gov/csels/dls/locs…
m.koreaherald.com/view.php?ud=20…
jcm.asm.org/content/58/8/e…

11/n
Reasons for PCR false-positives (~1% false + rate)
-past infection with residual RNA
-differences in testing between instruments
-glitches in instrument reading of Ct/Cq values
-lack of laboratory optimization normally required by the FDA
-contamination
12/n
Next, the Point of Care NAAT tests
Limited information published and in some ways very similar to lab based PCR
Abbott IDNow seems less sensitivity/more specific than Cepheid Xpert Xpress/Roche Cobas

13/n
POC NAAT tests
—Abbott IDNow
Clinical Sensitivity 54% / Clinical specificity 97.5%
(final numbers after adjustment for comparison to PCR)

Misses high CT value PCR + which are often NON-infectious. But no data vs. cell culture
cochranelibrary.com/cdsr/doi/10.10…
amazing work @deeksj

14/n
We estimated
Cepheid Xpert Xpress /Roche

Overall
Clinical sensitivity 90%
Clinical Specificity 95%

jcm.asm.org/content/58/8/e…
pubmed.ncbi.nlm.nih.gov/32417674/

(and other refs for IDNow)

16/n
Last, but not least...

Antigen tests! The great promise.

I would say useful but not great.

Overall
Clinical sensitivity 45%
Clinical specificity 97%

cochranelibrary.com/cdsr/doi/10.10…
sciencedirect.com/science/articl…
sciencedirect.com/science/articl…

17/n
Antigen tests better detect live virus but VERY limited data vs. cell culture @michaelmina_lab

And newer antigen tests will likely be better (but need clinical data, not just lab comparisons)
19/n
So, in conclusion, a group of @IDSAInfo docs, epidemiologists and @ASMicrobiology estimated the following CLINICAL Sensitivity & specificity for #COVID19 diagnostic tests

--feedback welcome

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More from @dr_dmorgan

15 Sep
Catch yourself when you say “risks vs. benefits” because you aren’t making a fair comparison.

In @JAMA_current ja.ma/336Lj4Y
& podcast ja.ma/2FAGKI2

@eliowa @drjohnm @d_spiegel @zeynep @VPrasadMDMPH

Why we say it and what we think is better below...
This building block of clinical decisions biases by framing uncertain harm vs. certain benefits and nudges towards treatment

Written with
@DKorenstein @ldscherer
(Over 2 years, i'm embarrassed to admit)
Clearly, the words physicians use have
a critical function in this communication

Referring to harms as “risks” emphasizes that
the unfavorable outcome may or may not happen,
whereas there is no parallel language that highlights
the equally probabilistic nature of “benefits.”
Read 8 tweets

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