Diagnostics 1&3

Question 1

Definition of a diagnostic

Answer 1

A characteristic of an illness or phenomenon (e.g symptoms, signs and biomarkers)

Question 2

Why do we do tests?

Answer 2

To include or exclude disease, support management, prognosis, monitoring or measure of general health

Question 3

5 approaches to defining normality

Answer 3

Statistical/Gaussian normality, percentile, risk factor, diagnostic, therapeutic

Question 4

What is Gaussian distribution?

Answer 4

Normal distribution - defining normality by proximity to the mean in the population (bell curve)

Question 5

Percentiles

Answer 5

Defining normality by proximity to the median - useful if mean is effected by data skew

Question 6

Defining normal by diagnosis

Answer 6

Comparing values found in healthy to those found in disease -often overlap though and often levels often raised in sick people without the disease

Question 7

100% sensitivity cut off

Answer 7

Positive result in all cases of disease (can get false positives)

Question 8

100% specificity cut off

Answer 8

Negative in all those without disease (can get false negatives)

Question 9

Compromise cut off

Answer 9

Minimising false positives and negatives

Question 10

Defining normal by therapeutic benefit

Answer 10

Normal if no benefit from treatment - must also consider harm of treatment so look at net benefit - useful if immediate treatment not necessary

Question 11

What is D-Dimer?

Answer 11

Small protein fragment found i blood after a clot. Degradation product of fibrin not found in normal blood

Question 12

Examples of gold standard tests

Answer 12

Histology, imaging and genetics

Question 13

Problems with histology

Answer 13

Interpretation and observer bias

Question 14

Problems with imaging

Answer 14

Interpretation, observer bias and incidental findings

Question 15

Problems with genetic tests

Answer 15

Normal variation, variable penetration and phenocopy (Other genes can cause same phenotype)

Question 16

True positive rate (sensitivity) formula

Answer 16

TP/(TP+FN)

Question 17

True negative rate (specificity) formula

Answer 17

TN/(TN+FP)

Question 18

What is positive predictive value?

Answer 18

How likely they are to have the disease if they get a positive result

Question 19

Positive predictive value formula

Answer 19

TP/(TP+FN)

Question 20

What is negative predictive value?

Answer 20

Chance of not having the disease if they get a negative result

Question 21

Negative predictive value formula

Answer 21

TN/(TN+FN)

Question 22

Best measure of test peformance

Answer 22

Likelihood ratios

Question 23

What is positive likelihood ratio? Normal cut off?

Answer 23

Likelihood of a positive result occurring in disease vs no disease. Normal cut off is 10

Question 24

Positive likelihood ratio formula

Answer 24

sensitivity/(1-specificity)

Question 25

What is negative likelihood ratio? Normal cut off?

Answer 25

The likelihood of a negative result occurring in disease vs no disease. Less than 0.1 is a good test

Question 26

What is an odds ratio in a binary test? Cut offs? Formula?

Answer 26

Odds that a positive result is due to disease vs no disease. 1=useless, more than 1 is useful (TP/FN)/(FP/TN)

Question 27

Receiver operating curves - axis? grandient?

Answer 27

y=sensitivity x=1-specificity - gradient is therefore the positive likelihood ratio at that cut off

Question 28

Roc area =?

Answer 28

Discriminatory power of test

Question 29

How do you determine best cut off from roc curve?

Answer 29

Apex of graph

Question 30

Generic likelihood ratio formula

Answer 30

probability of finding in disease/probability of finding in healthy

Question 31

Bayes theorem

Answer 31

The pre-test probability must be considered alongside the test results to calculate the post test probability

Question 32

Clinical gestalt

Answer 32

Seeing the patient as a whole and using your experience and intuition

Question 33

Does a test have more or less effect on post test probability if pre-test probability is high/low or uncertain?

Answer 33

Uncertain

Question 34

What is the pre-test probability in rare diseases?

Answer 34

Always very low - eg phaeo still being very unlikely even after positive plasma metanephrites

Question 35

Do likelihood ratios apply to apply populations and clinical settings?

Answer 35

No they must be applied to appropriate clinical settings and populations