1. Evidence-Based Medicine
Diagnostic Studies
Mindy Smith and Henry Barry

2. Objectives Formulate precise question Understand test characteristics
Sensitivity and specificity
Predictive values
Likelihood ratios
Critically appraise article

3. Sensitivity & Specificity
true positive rate
P(T+)|D+
Specificity
true negative rate
P(T-)|D-

4. 2x2 table Se = a/(a+c) Sp = d/(b+d)
Both are constant characteristics of the test

5. Practice case
500 patients with IBS and 500 normal volunteers have standing stool velocities.
400 IBS patients have abnormal SSV and 150 normal volunteers have abnormal SSV.

6. Practice 2x2
Se = ?
Sp = ?

7. Practice 2x2
500
500
Se = 0.8
Sp = 0.7

8. Conundrums Requirement:
to calculate sensitivity and specificity, you have to know beforehand who is diseased and disease-free
We order diagnostic tests because we DON’T know if the patient is diseased!

9. What does all that mean?
To interpret the results of a test, you have to know how likely the disease is in the first place
pre-test probability
disease prevalence
positive and negative predictive value are dependent upon pre-test probability

10. Selecting tests
Ruling in disease
Ruling out disease

11. Rules of thumb SpPIn SnNOut
a very Specific test, when Positive, rules In disease
SnNOut
a very Sensitive test, when Negative, rules Out disease

12. Critical Appraisal
What are the ONLY things we ever need to know? (hint, three questions)
are the results valid?
what are the results?
can you apply them?

13. Critical Appraisal: Validity
Are the results valid?
independent, blind comparison to gold standard
spectrum of severity
reference used in all patients

14. Critical Appraisal: Results
What are the results?
Sensitivity/specificity
Likelihood ratios

15. Critical Appraisal: Applicability
Available, affordable, accurate and precise
Can you estimate pre-test probability?
Will post-test probabilities affect your management?
Do the consequences of the test help your patient?

16. Likelihood ratio LR+ LR-
(probability of positive test in diseased subjects)/(probability of positive test in non-diseased subjects)
se/(1-sp) or True positives/False Positives
LR-
(probability of negative test in diseased subjects)/(probability of negative test in non-diseased subjects)
(1-se)/sp or False negatives/true negatives

17. LR 2x2 Table
LR+ = ((a/(a+c))/((b/(b+d))
LR- = ((c/(a+c))/((d/(b+d))

18. Working with Likelihood Ratios
Pretest probability = 10%
LR+ = 11
What is the post-test probability?

19. An easier way

20. An easier way

21. Summary
Post-test probability of disease is a function of pre-test probability
Reverend Bayes
Sensitivity and specificity have limited clinical utility
SpPIn and SnNOut
Likelihood ratios have more clinical utility

22. Teaching Points
Very sensitive tests rule out disease when negative (SnNOut)
Very specific tests rule in disease when positive (SpPIn)

23. More Teaching Points
Key validity issues: independent and blind comparison to a gold standard, spectrum of illness severity
Post-test probability depends upon the pre-test probability of disease
Likelihood ratios tell by how much a given test will increase or decrease pre-test probability