This document discusses various methods used to define diagnostic test results as normal or abnormal. It describes qualitative and quantitative tests, and issues with defining normals based on cultural opinions, percentiles, or presence of risk factors. Common statistical approaches like normal distribution curves and their limitations are explained. The document also covers predictive value, using multiple tests, and receiver operating characteristic curves to evaluate diagnostic tests.

1. Dr. Amany R.Aboseoud
Prof. of Community Medicine

2. Why we need diagnostic tests?
To differentiate between healthy and
diseased persons
What are the types of diagnostic tests?
Qualitative : +ve / -ve as presence of
abnormality or fracture
 Quantitative: the cut-off level above or
below which we consider disease. (positivity
criterion, critical value, referent value)

3. Cultural, (subjective
opinion)
percentiles
Presence of risk
factors
Therapeutic method Predictive value
Normal distribution
curve

4. o Not scientific, depends on culture and beliefs of
citizens.
o Depends on subjective opinion of people: as,
disfigurement, old age, obesity etc..
o In some countries, wasting of children is normal while
cachexia is abnormal
o In rural areas of Egypt in the thirties, presence of blood
in urine was normal(because bilharsiasis was very
common)

5.  Any value below or above: mean +/- 1.96 SD
is considered abnormal provided that there is population mean &
SD values (obtained by examination of large group of normal
individuals).
 Advantage: It is simple method
 Disadvantages:
 If the diagnostic test results do not fit Gaussian distribution, so
normals not constitutes 95%
 Normal persons in the test under study may be abnormal in other
tests (no 100% normals)
 Individual readings may change within the normal range which
denotes pathology(SBP from 90 to 110)
 Abnormal to that range may be normal in other subgroup(normal
height for a rural group may be short in another urban subgroup)

6.  The same as normal distribution but depending on 5 or
3 percentile values as the lowest permissible limits for
normal. 95 or 97 percentile values as the highest
permissible limits.
 Simple method
 Disadvantages: same as NDC

7.  To define who will take treatment and who will be
under survillance. Treatment of hypertension is
considered if BP >12080 which was in the past 14090
 Needs many experimental studies to know the benefit
of early treatment or changing the cut-off level.

8.  To categorize individuals into diseased or not according
to the risk factors they have
 Individuals with +ve family history of diabetes, obese,
live sedentary life (all are risk factors for developing
diabetes) can be put in one group against those who
have no risk factors.
 Smoking is a risk factor for cancer lung. But not all
cancer cases are smokers or not all smokers develop
cancer lung so smoking can not be diagnostic test.

9.  The most clinically applied method
 There must be gold standard to assess the predictive
value of the diagnostic test (knowing patients &
healthy)
 Make 2 x 2 table to calculate sensitivity, specificity and
predictive values of test
 Predictive value can be done for risk factors, new test
for diagnosis or choosing a cut-off level
 Changes done in these values depend on the aim of test
and its use in detection of normal or diseased persons

10. Disadvantages:
 Sometimes there is no gold standard
 The gold standard available is worse than the new test
so the validity will be misleading
 There is relation between predictive value of test and
the prevalence of disease. The higher the prevalence
the higher will be the PVP (if sensitivity & specificity
are the same for that test). Use back calculation method
to know the PVP for a test in another population who
has lower prevalence rate of the disease.

11. Measures that should be taken in selection of a new test:
 1- to compare its results to a gold standard
 2- to be blind testing (investigator does not know that
this result if for patient or healthy)
 3- to be reliable (repeat the test 3 times and take the
mean value.
 4- standardize the measuring scale before testing
(apparatus or ruler)
 5- take accurate reading (not approximate)
 6-test large samples with different reading scales

12.  For being more accurate use more than one test for
diagnosis (to overcome low sensitivity, predictive
values).
 1- Parallel testing: to order more than one test from a
blood sample (as in check up, emergency test). Any test
positive means a disease. (Sensitivity increases) used if
tests are cheap, no serious condition if false positive
 2- Serial testing: if the initial test is +ve do next and so
on (Low sensitivity). Used in no emergency, expensive
or risky tests. Begin with the most specific test

13.  If 2 tests were performed for diagnosis of heart disease
 Sensitivity of parallel tests= 15+20+60=95100
 Sensitivity of series tests=60/100
 Specificity of parallel=60/100
 Specificity of series=20+15+60=95/100
Test result serial parallel +ve cases -ve cases
T1+ve,T2 -ve -ve +ve 15 20
T1-ve,T2+ve -ve +ve 20 15
T1+ve,T2+ve +ve +ve 60 5
T1-ve,T2-ve -ve -ve 5 60
Total 100 100

14.  It is graphic presentation of the relation between
sensitivity & specificity of diagnostic test.
Uses:
 1- Choose the best cut-off level for a test
 2- Comparison between two tests

15.  specificity
 Sensitivity
 The best cut-off level is that close to upper left corner