Yes,
the post-test probability of a POSITIVE test = PPV
BUT! the post-test probability of a NEGATIVE test IS NOT EQUAL TO NPV, but
equal to (1-NPV)
Dr. Atle Klovning, GP
www.NettDoktor.no
> From: "Dr Alan Hassey" <[log in to unmask]>
> Reply-To: "Dr Alan Hassey" <[log in to unmask]>
> Date: Mon, 12 Jun 2000 18:52:19 +0100
> To: <[log in to unmask]>
> Subject: Tests
>
> Are positive predictive value & post test probability (PTP) the same?
>
> PPV = proportion of positive tests that have the test condition =
> sens x prev/sens x prev + (1-spec) x (1 - prev)
>
> sens = sensitivity
> spec = specificity
> prev = prevalence
>
> post test probability (PTP) = pre-test probability X LR
>
> LR+ = likelihood ratio = odds that the test will be +ve in a patient with
> the test condition
> LR+ = sens / (1 - spec)
>
> I'm playing with methods of validating electronic patient records (EPRs).
> Others have used sens/PPV as measures of completeness & accuracy of
> recording. I decided to use a Bayesian approach & measure pre-test
> probability as = prevalence of the test condition & calculate LR+ from a 2x2
> table where the Read Code functions as a "test" for the actual (true/valid)
> presence or absence of the test condition
>
> Thus
>
> Condition present condition absent
> Read code present true + false +
> Read code absent false - true -
>
> Thus for our diabetic data the results are;
>
> true + 282 false + 2
> false - 5 true - 13302
>
> prev = 2.1%
> sens = 98.3%
> spec = 100%
> LR+ = 6537
> LR- = 0.017
> PPV = 99.3%
> PTP = 99.3%
>
> I'm probably just being dense, but calculating PPV & PTP gives the same
> result. I just hadn't realised they were the same (unless I've screwed up my
> calculations....)
>
> Comments welcome ;-)
> ===
> Dr Alan Hassey (mailto:[log in to unmask])
> RCGP Health Informatics Grp & JCG
>
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