Evidence About Diagnosis

Question 1

What is pre-test probability?

Answer 1

The probability of a patient having a condition before assessing them (i.e. population prevalence)

Question 2

What is a gold standard test (aka reference diagnostic test, reference standard)?

Answer 2

• The most accurate test available regardless of how invasive, expensive, or time consuming
• May be hindsight, where the correct diagnosis only becomes apparent with time (or post-mortem)

Question 3

What is an index test?

Answer 3

• The test being investigated (diagnostic test of interest)

- More practical than the gold standard

Question 4

What are the types of diagnostic study designs?

Answer 4

• Cohort study
• Cross-sectional studies
• Case-control
• Systematic review of diagnostic accuracy studies

Question 5

What is a cohort study?

Answer 5

• All people with a particular clinical presentation, who present at a particular hospital, undergo both the gold standard and index test
• Stats done to compare how accurate index test was relative to gold standard

Question 6

How can bias be minimised in a cohort study?

Answer 6

• True diagnosis not known until after enrolment
• › Consecutive patients invited to participate in the study
• Gold standard test result is not known when conducting the index test & vice versa

Question 7

What is a cross-sectional study?

Answer 7

A group of people with a particular clinical presentation are recruited, who then undergo both the gold standard and index test (i.e. a snapshot)

Question 8

What is a case-control study?

Answer 8

• People who clearly have the disease & people who clearly don’t, undergo both the gold standard & index test
• Only has to discriminate between extreme cases; doesn’t reflect clinical reality
  ›- Prone to bias

Question 9

What does sensitivity of the index test refer to?

Answer 9

How many people who have the disease are correctly diagnosed with the index test (i.e. person with the disease with a positive test result, true positive)

Question 10

What does specificity of he index test refer to?

Answer 10

How many people who don’t have the disease (who are well) are correctly identified with the index test (i.e. well person with a negative test result, true negative)

Question 11

What does positive predictive value (PPV) refer to?

Answer 11

• The chance a positive index test result will be correct

- PPV will fall as disease prevalence falls

Question 12

What does negative predictive value (NPV) refer to?

Answer 12

• The chance that a negative index test result will be correct
• NPV will rise as disease prevalence falls

Question 13

What do likelihood ratios predict?

Answer 13

• The presence of a diagnosis
• Sensitivity & specificity cannot predict the risk of an abnormality (i.e. they refer to how abnormality predicts test results)

Question 14

What does a positive likelihood ratio refer to?

Answer 14

• Used when a person has a positive index test
• How much more likely is a positive test result in a person with the condition than in a person without it?

= 1 is useless
= >2 helps rule in disease
= >10 extremely good for ruling in disease

Question 15

What does a negative likelihood ratio refer to?

Answer 15

• How much more likely is a negative test result in a person without the condition than in a person with it?
• Used when a person has a negative index test

= 1 is useless
= <0.5 helps rule out disease
= <0.1 extremely good for ruling out disease

Question 16

Which statement is correct?

Test A is highly sensitive (99%) for a condition (& has a high specificity of 80%); this means that …

a. Test A will identify the majority of people who have the condition (99%).
b. It is unlikely that someone with the condition will have a negative result on test A (1%).
c. Someone who does receive a negative result on test A is unlikely to have the condition (80%).
d. Test A is good at ruling out the condition

Answer 16

All statements are correct

Question 17

Which statement is correct?

Sensitivity and specificity …

a) is never affected by the size of the sample
›b) can be described using 95% confidence intervals
›c) can have 95% CI that are unequal sizes
›d) all of the above
›e) b and c are correct

Answer 17

›e) b and c are correct

Question 18

How is the sampling theory affected by sensitivity & specificity?

Answer 18

• If we repeat a diagnostic accuracy study with a new sample the sample will be slightly different
  ›- And the estimate of sensitivity and specificity will be slightly different
• Sensitivity: Sample size = number with condition
• Specificity: Sample size = number without condition

Question 19

When is 95% CI widest?

Answer 19

For proportion (point estimate) = 0.5
Narrows as proportion tends to 0 or 1

Question 20

How are likelihood ratios calculated?

Answer 20

Positive likelihood ratio (PLR) = sensitivity/(1-specificity)

Negative likelihood ratio (NLR) = (1-sensitivity)/specificity

Question 21

What are receiver operating characteristics used for?

Answer 21

Determining a cutoff point for tests on continuous scales (e.g. blood pressure)

Question 22

The odds of the event are 1:3, what is the risk (probability) of the event occurring?

Answer 22

0.25 (25%)

Question 23

An effective treatment has a number needed to treat (NNT) that is -?

Answer 23

Small

Question 24

The risk (probability) of the event is 90%, what are the odds of that event?

Answer 24

0.9/0.1 = 9

Question 25

What are the odds of flipping a coin and landing on tails?

Answer 25

1:1 (1)

Question 26

True or false:
If the 95% confidence interval for the risk ratio of an intervention includes 1, this indicates no statistically significant effect

Answer 26

True

Question 27

What are the odds of rolling a die (singular of dice) and landing on 6?

Answer 27

1:5 (0.2)