Statistical Test for Clinical Diagnostic Screening Tests.

1. Diagnostic Evaluation Statistics
𝑃𝑃𝑉 =
𝑇𝑃
𝑇𝑂+𝐹𝑃
=
𝑎
𝑎+𝑏
𝑁𝑃𝑉 =
𝑇𝑁
𝑇𝑁+𝐹𝑁
=
𝑑
𝑑+𝑐
𝑆𝑒𝑛𝑠𝑡𝑖𝑣𝑖𝑡𝑦 =
𝑇𝑃
𝑇𝑃+𝐹𝑁
=
𝑎
𝑎+𝑐
𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐𝑖𝑡𝑦 =
𝑇𝑁
𝑇𝑁+𝐹𝑃
=
𝑑
𝑑+𝑏
Prevalence=
𝑁𝑜 𝐷𝑖𝑠𝑒𝑎𝑠𝑒𝑑
𝑇𝑜𝑡𝑎𝑙 𝑆𝑎𝑚𝑝𝑙𝑒
=
𝑇𝑃+𝐹𝑁
𝑇𝑃+𝑇𝑁+𝐹𝑃+𝐹𝑁
𝑆𝑒𝑛𝑠𝑡𝑖𝑣𝑖𝑡𝑦 𝑆𝑝𝑒𝑐𝑖𝑓𝑖𝑐𝑖𝑡𝑦 Prevalence PPV NPV
Prevalence PPV NPV
The Diagnostic Process
Test
Result
P
Disease No Disease Total
a = TP b = FP TP+FP = a+b
N
c = FN d = TN FN+TN = c+d
TP+FN = a+c FP+TN = b+d a+b+c+d =
TP+FN+FP+TN

2. Bayes Theorem Fagan Nomogram Natural frequencies
Bayes' theorem converts the results from
your test into the real probability of the
event.
The Fagan Nomogram is a graphical tool
for estimation how much result on a
diagnostic test changes the probability that
a person has a disease.
Natural frequencies represent the joint
frequencies in 2 events such as the number
of patients number who will have a
positive test result with disease and the
Likelihood Ratio Example
Patient has signs
nad symptoms
Differential
Diagnosis
Advice
Diagnostic Test
Interpret and Act
On Test Results
Pre-Test
Probibility
Test
Characteristics
Post-Test
Probibility

3. A new state of the art blood pressure cuff with a SN of 80% and a SP of 95% was developed. Assume that someone's chance of
having blood pressure in the general population who's completely asymptomatic is 20%. Pretest probability = 20% (unless if there
are risk factors, symptoms, etc...)
LR+=0.8/0.05 = 16
LR=-0.2/0.95 = 0.211
Pretest Odds = 0.2/0.8 = 0.25
+ve Posttest Odds = 0.25 x 16=44/5 = 80%
-ve Posttest Odds = 0.25 x 0.211 = 0.0527 0.0527/1.0527 = 0.05 → 5%
Cohen's kappa coefficient is a statistic that is used to measure inter-rater reliability for qualitative
items.

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