Screening tests and diagnostic Flashcards
Validity
the ability to distinguish who has and who doesn’t have a disease
The test need to be:
sensitive : to be able to identify people who have the disease
specific: that it does not identify people as having the disease when in actual fact they don’t
Screening tests can be divided into two:
- dichotomous results
- continuous variables
Tests with dichotomous results
Only has one of two possible results: negative or positive
To know how good the test is at identifying diseased individuals, calculate sensitivity and specificity
If a test does not correctly identify the disease status of people this is referred to as false negative or false positive
Tests of continuous variable
Examine blood pressure
There is no positive or negative result
There is a cut off level above which a test result is considered positive and below which is considered negative
NB to correctly establish cut of level to prevent incorrectly classifying people as having the disease when they don’t
There is no perfect cut-off level, objective is to determine the most beneficial cut-off level.
If cut-off level is too high or too low then false negative and false positive will result
Use of multiple screening tests
sequential- two stage
less expensive, invasive and more comfy test dine first
second test will be more sensitive and specific
simultaneous- two tests are done at the same time and
results are used to calculate net sensitivity and specificty
Compare simultaneous and sequential testing
What to take into account
2 sequential tests are used, those who test positive on first test are brought in for second test. Loss in net sensitivity and net gain in specificity compared to test done alone
2 simultaneous tests used, net gain in sensitivity and net loss in specificity compared to test done alone
The choice of which testing to perform depends on whether test is for
screening or diagnostic purposes
Predictive value of test
How true is it that a person has or doesn’t have disease/ accurate
positive predictive value formula
no. of true positive (have disease)/ total no. who tested positive ( true positive and false positive)
negative predictive value formula
no. of true negative ( do not have disease)/ total no. who tested negative( true negative and false negative)
Positive predictive value is affected by
prevalence of disease in population
specificity of test being used
Relationship between positive predictive value and disease prevalence
higher the prevalence the higher the positive predictive value
this means screening the programme is beneficial and economical if it is directed at high risk target populations
Relationship between the positive predictive value and specificity
increase in specificity of a test will result in an increase in the positive predictive value
Reliability of tests
If tests results are not reliable and cannot be reproduced, the value and usefulness of test are minimal
