Further, and coincidentally, a long list
of
Best
Rich
From: Evidence based health
(EBH) [mailto:[log in to unmask]] On Behalf Of
Sent: Sunday, February 13, 2011
4:47 PM
To:
[log in to unmask]
Subject: Re: Question about
screening and denominators
Hello Ash,
I am unfamiliar with said claptrap, but
there are certainly a wide range of guidelines out there, and many ways to
evaluate which should be followed versus ignored. At the national level
though, in the
Best
Rich
Editor, Evidence-based Medicine (EBM)
Professor of Medicine and Epidemiology
·
The
Grade: D Recommendation.
·
The USPSTF found insufficient evidence to recommend for or against
routine screening with ECG, ETT, or EBCT scanning for coronary calcium for
either the presence of severe CAS or the prediction of CHD events in adults at
increased risk for CHD events.
Grade: I Statement.
From: Ash Paul
[mailto:[log in to unmask]]
Sent: Sunday, February 13, 2011
2:14 AM
To:
Subject: Re: Question about
screening and denominators
Dear Richard,
What about the claptrap being promoted by the Screening for
Heart Attack Prevention and Education (SHAPE) Task Force in the
The SHAPE Guideline calls for noninvasive screening of all
asymptomatic men 45–75 years of age and asymptomatic women 55–75
years of age (except those defined as very low risk) to detect and treat those
with subclinical atherosclerosis.
And now the Texas Government has fallen for this hook, line and sinker and
passed into law a measure to provide reimbursement for MI screening.
Is it any wonder that the
Regards,
Ash
Dr Ash
Paul
Medical
Director
NHS
Bedfordshire
MK40 2AW
Tel no:
01234897224
Email: [log in to unmask]
From:
To:
[log in to unmask]
Sent: Sat, 12 February, 2011
21:49:15
Subject: Re: Question about
screening and denominators
Simon,
One of my favorite examples of this issue
was published in the NEJM in 1987, a classic. And still relevant today re HIV
screening. I’ll excerpt below and here is the reference:
N
Engl J Med 1987; 317:238-241July 23, 1987
Bottom line re HIV testing example: 100% sensitive
test, 99.995% specificity. Positive predictive value (chance the patient has
the disease) of test if prevalence is 0.01%=67% (one third with a positive test
don’t have the disease).
Best,
Rich Saitz
Editor, Evidence-based Medicine (EBM)
Professor of Medicine and Epidemiology
What do we know about
the prevalence of HIV infection? Perhaps 50 percent of homosexual men in
Other segments of the
population are at much lower risk. Screening of military recruits has shown
0.16 percent of the men and 0.06 percent of the women to be seropositive.27 When antibody screening of donated blood began in 1985, 1
unit of blood in 2500 had HIV antibody.28 At that rate, the chance of infection from 2 units of
blood donated before antibody screening began would be about 0.08 percent.
Among female blood donors, as noted, the reported prevalence of seropositivity
is 0.01 percent. Some of these donors may have had sexual contact with members
of known high-risk groups; among women without such contact, the prevalence of
infection may be even lower than 0.01 percent.
Test sensitivity is not
the issue here, and to emphasize our concern with the false positive rate, our
analysis makes the best-case assumption that the combination of enzyme
immunoassay and Western blot testing for HIV is 100 percent sensitive,
identifying all persons who are infected. The meaning of positive tests will
depend on the joint false positive rate. Because we lack a gold standard, we do
not know what that rate is now. We cannot know what it will be in a large-scale
screening program. However, we can be fairly sure that without careful quality
control, it will rise.
Bayes' rule allows us
to calculate the probability that a person with positive tests is infected.29Imagine testing 100,000 people, among whom the prevalence of disease
is 0.01 percent. Of the 100,000, 10 are infected; 99,990 are not. A combination
of tests that is 100 percent sensitive will correctly identify all 10 who are
infected. If the joint false positive rate is 0.005 percent, the tests will
yield false positive results in 5 of the 99,990 people who are not infected.
Thus, of the 15 positive results, 10 will come from people who are infected and
5 from people who are not infected, and the probability that infection is
present in a patient with positive tests will be 67 percent.
From: Evidence based
health (EBH) [mailto:[log in to unmask]] On Behalf Of Simon Hatcher
Sent: Wednesday, February 09, 2011
6:22 PM
To:
[log in to unmask]
Subject: Question about screening
and denominators
I had this discussion with a friend over
a beer last night and we couldn't agree on the answer. Here's the scenario:
The incidence of a disease in a
population is 1:1000
There is a test which correctly detects the
disease 95%of the time
If I test positive with the test what is my risk of having
the disease?
Be interested in any thoughts on the "correct"
answer.
Cheers
Simon
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