Evaluating Diagnosis Flashcards
What do studies of a diagnostic test usually evaluate the relationship between?
Being positive for standard diagnostic test vs being positive for evaluated screening test
What are the 4 groups in diagnostic test studies
True positive = A
False positive = B
False negative = C
True negative = D
First column for table for diagnostic test studies
Test positive
Test negative
Total
Second column
Disease (gold standard positive)
A
C
A+C
3rd column
No disease (gold standard -ve)
B
D
B+D
4th column
A+B
C+D
A+B+C+D
First row
Diseased, No disease
2nd row
Test positive, A, B, A+B
3rd row
Test negative, C, D, C+D
4th row
Total, A+C, B+D, A+B+C+D
Define sensitivity
Usefulness of a test for truly diseased population
Define specificity
Usefulness of a test of non-diseased population
Calculation for sensitivity
A/A+C
(true positive/total diseased)
Calculation for specificity
D/B+D
(true negative/total non-diseased)
Calculation for accuracy
A+D/A+B+C+D
(true positive + true negative/total population)
Characteristics of a highly sensitive test
Will pick up cases that show even slightest of evidence
Makes more false positives
When is a highly sensitive test preferred?
If diagnosis should not be missed but overdiagnosis is not harmful
Characteristics of highly specific test
Will pick up cases only if definitive evidence noted
Makes more false negatives
When is a highly specific test preferred?
If missing some cases is not bad but wrong labelling can be costly/harmful
Impact of higher cut off on specificity and sensitivity
Low sensitivity
High specificity