term 3 module 4

Question 1

Bayes’ Theorem

Answer 1

• Probability implies that there is an uncertainty. Bayes’ Theorem
  quantifies the uncertainty.
• The purpose of pretest and posttest probabilities is to increase
  certainty to be more confident in the diagnosis.

Question 2

Bayes’ Theorem (cont’d)
* Pretest probability (prior probability)

Answer 2

➢ What we think after initial exam and history
➢ Prevalence of the disorder based on population data
Being able to estimate pretest probability is central to next step!
best initial guess of likelihood

Question 3

Baues theorem cont’d
* Posttest probability (posterior probability)

Answer 3

➢ What we think after diagnostic test
➢ The revised likelihood diagnosis
➢ based on pretest probability & likelihood ratios (LR) via a nomogram

Question 4

Positive Likelihood Ratio (LR+)

Answer 4

𝐋𝐑+ =
𝒔𝒆𝒏𝒔𝒊𝒕𝒊𝒗𝒊𝒕𝒚/𝟏 − 𝒔𝒑𝒆𝒄𝒊𝒇𝒊𝒄𝒊𝒕𝒚 =
T positive rate / F positive rate

Question 5

• Negative Likelihood Ratio (LR-)

Answer 5

𝑳𝑹−
𝟏− 𝒔𝒆𝒏𝒔𝒊𝒕𝒊𝒗𝒊𝒕𝒚/𝒔𝒑𝒆𝒄𝒊𝒇𝒊𝒄𝒊𝒕𝒚 =
F negative rate/T negative rate

Question 6

A good test will have a high positive likelihood ratio and
a ___ negative likelihood ratio.

Answer 6

low

Question 7

Interpretation of Likelihood Ratios

Answer 7

• Values close to 1.0 do NOT provide useful
  information (b/c an LR = 1.0 represents a 50:50
  chance of increasing or decreasing the probability of
  a diagnosis).
• Values below .2 and above 5.0 provide more useful
  information

Question 8

Guidelines for Interpreting LRs

Answer 8

• LR+ > 10 or LR - < 0.1
• Large and conclusive change
• LR+ = 5-10 or LR- = 0.1 - 0.2
• Moderate change
• LR+ = 2-5 or LR- = 0.2 - 0.5
• Small but sometimes important change
• LR+ = 1-2 or LR- = 0.5 -1.0
• Negligible change in pre-test probability

Question 9

Prevalence =
✓ the best guess for pretest probability
✓ a proportion reflecting the No. of existing cases of a
disorder relative to the total population at a given point
in time
P=

Answer 9

P = number of existing cases at a give point/total population at risk

Question 10

Using a Nomogram to determine
posttest probability
A nomogram was developed based on Bayes’
Theorem
whats on L middle and R

Answer 10

• Left: Pretest Probability (41%)
• Middle: LR+ (3.71) and LR– (0.27)
• Right: Posttest Probability (72% and 16%)

Question 11

Receiver Operating Characteristics (ROC) Curves

Answer 11

• For diagnostic purpose, it is Helpful to determine a cutoff
  score (e.g., height loss at 4 cm) along continuous scale to
  determine positive or negative test.
• There is a Trade-off between sensitivity and 1–specificity
• “Signal to noise”
• Coordinates are true positive rate (Y = Sensitivity) against false positive rate (X = 1 - Specificity) at different cutoff points (1 cm, 2 cm, 3 cm …. 6 cm)

Question 12

Area under the curve (AUC)

Answer 12

represents the ability of the test to discriminate between those with and without the test condition.

Question 13

A receiver operating characteristic (ROC) curve for a
perfect test (Sn = Sp = 100%)

Answer 13

basically a filled in square,
sensitivity (true positive) on y axis
1 - specificity (false positives) on x axis

Question 14

on a ROC , whats on x and y axis

Answer 14

sensitivity (true positive) on y axis
1 - specificity (false positives) on x axis

Question 15

if an a a box between y axis true positives (sn) and x axis false positives (1 - specificity) is split in two by the numbers, what does the ROC/AUC symbolize

Answer 15

50 50 chance to get the test right to appropriate rule in / out the diagnosis

Question 16

ROC, Point where curve turns is best cutoff point

Answer 16

✓ Largest difference between true positive and false positive rate (i.e., the difference between sensitivity and (1– specificity), known as the Youden index)
✓ Best cutoff at 4 cm height loss

Question 17

Critical Assessment of Study Credibility, questions to assess the validity of evidence about diagnostic tests

Answer 17

7 questions

Question 18

Assessment of Study Credibility – Diagnostic Tests or
Measures
1. Did the investigators include subjects with all levels or
stages of the condition being evaluated by the index test
(measure)?

Answer 18

• Determines the usefulness of the test (measure) with
  respect to distinguishing between important gradations in
  the diagnosis or impairment
• Investigators’ prerogative re: who to include in study

Question 19

Assessment of study credibility - diagnostic tests or measures
2. Did the investigators evaluate (or provide a
citation for) the reliability of the index diagnostic
test (measure)?

Answer 19

• A necessary precondition for validity; may be
  tested in a separate investigation

Question 20

Critical Assessment of Study Credibility
3. Did the investigators compare results from the
index test to results from a “gold” (reference)
standard comparison diagnostic test (measure)?

Answer 20

• Verifies the test (measure) does what it’s
  supposed to do
• Commonly used gold standards:
  ✓Radiographs
  ✓Surgical exploration
  ✓A test or measure with previously demonstrated
  consistency and usefulness

Question 21

Critical Assessment of Study Credibility
4. Did all subjects undergo both the test (measure)
of interest and the gold standard test (measure)?

Answer 21

• Addresses the issue of bias due to manipulation of
  the sample

Question 22

Critical Assessment of Study Credibility
5. Were the individuals performing and interpreting
each tests results unaware (“masked”, “blinded”) of
the other test’s (measure’s) results?

Answer 22

• Addresses the issue of bias

Question 23

Critical Assessment of Study Credibility
6. Was the time between application of the index test
(measure) and the “gold standard” comparison
diagnostic test (measure) short enough to minimize the
opportunity for change in the subjects’ condition?

Answer 23

Addresses the potential for misclassification
(inaccurate quantification) due to natural changes in
the subjects’ status (e.g., healing)

Question 24

Critical Assessment of Study Credibility
7. Was the study repeated on a new set of subjects?

Answer 24

• Addresses the reproducibility of the results

Question 25

Should You Use this Evidence?

Answer 25

* Is the study high quality (e.g., does the design minimize bias)? * Are the results important enough to use? * Is the test or measure of interest available, practical and safe for application in the clinical setting? * Was your patient or client represented in the study sample? * Can you estimate the pre-test probability of the disorder?

Question 26

Should You Use this Evidence?

Answer 26

Patient’s or client’s values and preferences re: ✓Risk of injury or pain during the test or measure ✓Whether knowing the test results will produce an important benefit ✓Cost – financial, time, personal ✓Confidence in the test & physical therapy ✓Belief in the value of scientific evidence ✓Previous experiences