Evidence for diagnosis

Question 1

What should be considered when assessing diagnostic tests?

Answer 1

1. Can we find evidence that evaluates the accuracy of the tests?
2. Is the evidence about the accuracy of a diagnostic test VALID?
3. Does this valid evidence show the test can DISTINGUISH patients with and
   without the disease?
4. Can we APPLY this valid and accurate test to our patients?

Question 2

Describe Gaussian

Answer 2

This assumes normality of the test results and a normal result is define on the basis of statistical properties (mean and SD). It assumes all ‘abnormal’ results occur at the same frequency.

Question 3

Define ‘diagnostic’ in the context of assessing diagnostic tests

Answer 3

the range of results beyond which the disease becomes highly likely.

Question 4

Define ‘therapeutic’ in the context of treatment

Answer 4

the range of results beyond which treatment does more harm than good.

Question 5

Define accuracy

Answer 5

the ability of a test to give a true measure of the substance being measured. The result doesn’t always have to be close to the true vale to be accurate but if repeat tests are run, then the average of the results should be close to the true value.

Question 6

Define precision.

Answer 6

This relates to how consistent the results of the test are. A test that always gives the same result for a sample is said to be precise, though it may not be accurate if the measured value is consistently incorrect.

Question 7

How can diagnostic tests be evaluated? 2

Answer 7

Accuracy and precision

Question 8

What does validity of the results evaluating a diagnostic test’s measurement performance include? 3

Answer 8

Measurement, representative, ascertainment (of the reference standard - was this independently ascertained to the test results?)

Question 9

Define sensitivity (diagnostic tests)

Answer 9

This is the proportion of patients with the disease that

are test positive, i.e. how many of the diseased patients does the test detect.

Question 10

Define specificity (diagnostic tests)

Answer 10

This is the proportion of disease NEGATIVE patients that the test correctly identifies as negative.

Question 11

What is meant by SnNout?

Answer 11

If the Sensitivity is high, then a Negative test allows us to rule OUT a disease.

Question 12

What is meant by SpPin?

Answer 12

if the Specificity in high, then a Positive test allows us to rule IN the disease.

Question 13

What do positive and negative predictive values reflect?

Answer 13

These reflect the relevance of a test to a patient
or group of patients to which we are applying the test. They refer to the probability that a patient has or does not have a disease given the test is positive or negative.

Question 14

Define positive predictive value

Answer 14

Probability that the animal actually has disease given it

is test positive. That is, of all test positive animals the proportion that have the disease.

Question 15

Define negative predictive value

Answer 15

Probability that given a test is negative that the patient does not have the disease.

Question 16

Define LR+

Answer 16

The likelihood ratio for a positive test. The LR + indicates how many times more likely is the test positive result in a patient with disease compared to one without disease.

Question 17

What does LR+ = 15 mean?

Answer 17

E.g. LR+ = 15, the positive test result is 15 times more likely in a diseased than non-diseased patient.

Question 18

What is the equation for LR+?

Answer 18

LR + = (Probability of +test in diseased) / (probability of +test in absence of disease)

OR

LR+ = Sensitivity / (1 – Specificity)

Question 19

Define LR-

Answer 19

= how many times more likely is the test negative result in a patient with the disease compared to one without the disease

Question 20

Equation for LR -?

Answer 20

(LR -) = (Probability of - test in diseased)/(probability of - test without disease).

OR

LR - = = (1- Sensitivity) / Specificity

Question 21

With cutpoints, what will increasing the cutpoint do?

Answer 21

increase specificity

decrease sensitivity

Question 22

With cutpoints, what will decreasing the cutpoint do?

Answer 22

decrease specificity

increase sensitivity

Question 23

What should you consider when choosing a cutpoint for a continous scale?

Answer 23

whether false positives or false negatives are more important for the test and condition under evaluation.

Question 24

What can be used to assess the cutpoints?

Answer 24

Graphical methods - including ROC curves.

Question 25

Define ROC (curve)

Answer 25

Receiver Operating Characteristic Curves.

Question 26

What does a ROC curve plot?

Answer 26

This is a plot of sensitivity versus (1 – specificity), calculated on a number of cutpoints to select the optimal cutoff to distinguish diseased from non-diseased.

Question 27

How does a ROC curve work?

Answer 27

The top left corner represents 100% sensitivity and
specificity, and the nearest point on the curve to that point indicates the cutpoint with the maximum sensitivity and specificity.

Question 28

What is series interpretation when multiple tests are performed?

Answer 28

In series interpretation, only animals positive for the both tests are considered test positive.

Question 29

How does series interpretation of multiple tests affect specificity and sensitivity?

Answer 29

Series interpretation increases specificity but decreases sensitivity.

Question 30

What is parallel interpretation when multiple tests are performed?

Answer 30

With parallel interpretation of tests, animals that test positive for one or both tests are considered test positive.

Question 31

How does parallel interpretation of multiple tests affect specificity and sensitivity?

Answer 31

Parallel tests increase sensitivity whilst decreasing specificity.

Question 32

What are screening tests used for?

Answer 32

used to screen a population for test positives

Question 33

Properties - screening tests

Answer 33

should be easy to apply, cheap and need to have high sensitivity and good specificity.

Question 34

How can you avoid misinterpreting diagnostic tests?

Answer 34

A systematic approach to evaluating evidence on diagnostic tests will allow veterinarians to get the maximum benefit from them.