2. Question 1
A new ‘Super test’ claims to have a superb capability to diagnose disease X. Its sensitivity is 99% and specificity is 90%.
Which of the following statement is most correct?
The ‘Super test’ is definitely good as it has high sensitivity and specificity.
The ‘Super test’ is definitely better because its sensitivity is higher than specificity.
Specificity is the probability for a test to show a negative results in those without a particular disease.
The ‘Super test’ is not good as its specificity is below 95%
Legend:
WBC = White Blood Cell
Sens.= Sensitivity
Spec.= Specificity

3. 80 30 20 70 Question 2 Positive Negative Yes WBC count = or > 15K?
Patients with bacteraemia (Blood culture)
Positive Negative 80 30 20 70
Yes
WBC count
= or > 15K? No
The sensitivity of “WBC” in detecting bacteraemia is:
70 / (70+30)
70 / (20+70)
80 / (80+30)
80 / (80+20)
Legend:
WBC = White Blood Cell
Sens.= Sensitivity
Spec.= Specificity

4. 60 25 40 75 Question 3 Positive Negative Positive “New Scan” Negative
Renal artery stenosis
Positive Negative 60 25 40 75
Positive
“New Scan”
Negative
The specificity of the “New Scan” is:
75 / (75+25)
75 / (75+40)
60 / (60+40)
60 / (60+25)
Legend:
WBC = White Blood Cell
Sens.= Sensitivity
Spec.= Specificity

5. What is the ‘number needed to treat’ to prevent one leg ulcer? 20 10 5
Question 4
A study randomised diabetic patients into treatment X (placebo) and treatment Y. It reported that leg ulcer occurred in 22% of the patients in the placebo group (treatment X) and 2% of the patients given treatment Y.
What is the ‘number needed to treat’ to prevent one leg ulcer? 20 10 5 15
Legend:
WBC = White Blood Cell
Sens.= Sensitivity
Spec.= Specificity

6. Question 5
A researcher reported that there was significant difference of waist circumference between male and female. The male’s waist circumference is 3cm larger than the female’s and the p-value was 0.12.
Which of the following statements is most correct?
The study was not significant because the absolute difference in waist circumference was only 3 cm.
(B) The study was significant because the p-value is greater than 0.05
(C) P value is the probability that an observed difference occurred by chance.
(D) The study was not significant because the p-value must be smaller than 0.001
Legend:
WBC = White Blood Cell
Sens.= Sensitivity
Spec.= Specificity

7. Positive Predictive Value Negative Predictive Value
Sensitivity
Specificity
Positive Predictive Value
Negative Predictive Value

8. Definition Sensitivity:
The probability of a positive test in those with the disease
Specificity:
The probability of a negative test in those without the disease

9. a b c d Sensitivity Patients with the condition Yes No Positive
Test Result
Negative
Legend:
a = True positive
b = False positive
c = False negative
d = True negative
Sensitivity = a / [a + c]

10. a b c d Specificity Patients with the condition Yes No Positive
Test Result
Negative
Legend:
a = True positive
b = False positive
c = False negative
d = True negative
Specificity = d / [b + d]

11. a b c d Positive Predictive Value (PPV) Patients with the condition
PPV is the probability that a positive test is a true positive.
Patients with the condition
Yes No
Positive a b c d
Test Result
Negative
Legend:
a = True positive
b = False positive
c = False negative
d = True negative
Positive predictive value= a / [a + b]

12. a b c d Negative Predictive Value (NPV) Patients with the condition
NPV is the probability that a negative test is a true negative.
Patients with the condition
Yes No
Positive a b c d
Test Result
Negative
Legend:
a = True positive
b = False positive
c = False negative
d = True negative
Negative predictive value= d / [c + d]

13. 55 275 5 177 Patients with bacteraemia (blood culture)
Example 1: Sensitivity
Patients with bacteraemia (blood culture)
Positive Negative
Yes 55
275 5
177
WBC count
= or > 15K? No
Sensitivity = 55/ [55+5] = 0.91
Legend:
WBC = White Blood Cell
Sens.= Sensitivity
Spec.= Specificity
Reference: Bass JW, et al. Antimicrobial treatment of occult bacteremia: a multicenter cooperative study. Pediatric Infect Dis J 1993; 12: 466 – 73.

14. 55 275 5 177 Patients with bacteraemia (blood culture)
Example 1: Specificity
Patients with bacteraemia (blood culture)
Positive Negative
Yes 55
275 5
177
WBC count
= or > 15K? No
Specificity = 177/ [ ] = 0.39
Legend:
WBC = White Blood Cell
Sens.= Sensitivity
Spec.= Specificity
Reference: Bass JW, et al. Antimicrobial treatment of occult bacteremia: a multicenter cooperative study. Pediatric Infect Dis J 1993; 12: 466 – 73.

15. 55 275 5 177 Example 1 (continued) Positive Predictive Value (PPV)
PPV is the probability that a positive test is a true positive.
Patients with bacteraemia (Blood culture)
Positive Negative 55
275 5
177
Yes
WBC count
= or > 15K No
Legend:
WBC = White Blood Cell
Sens.= Sensitivity
Spec.= Specificity
Positive Predictive Value: 55 / [ ] = 0.17

16. 55 275 5 177 Example 1 (continued) Negative Predictive Value (NPV)
NPV is the probability that a negative test is a true negative.
Patients with bacteraemia (Blood culture)
Positive Negative 55
275 5
177
Yes
WBC count
= or > 15K No
Legend:
WBC = White Blood Cell
Sens.= Sensitivity
Spec.= Specificity
Negative Predictive Value: 177 / [ ] = 0.97

17. Example 2 Consider HIV screening in the general population
Imagine Western blot has a sensitivity of 99.99% but a specificity of 95%
Say in a city of 100,000 has an HIV incidence of 1/10,000
What will be the true & false positives as a result of screening the city?

18. Example 2 (continue) TP FP FN TN HIV Yes No Positive HIV Screening
With that HIV incidence of 1/10,000 we may expect 10 people have HIV in that city of 100,000 people. Number of estimated HIV patient= x 1/ = 10.
HIV
Yes No TP FP FN TN
TP= True Positive
FP= False Positive
TN= True Negative
FN= False Negative
Positive
HIV Screening
Negative
Total 10
99,990

19. Example 2 (continue) 10 FP TN HIV Yes No Positive HIV Screening
With a sensitivity of 99.99%, the True Positive= 99.99/100 x 10 =9.999 which is rounded to 10.
HIV
Yes No 10 FP TN
TP= True Positive
FP= False Positive
TN= True Negative
FN= False Negative
Positive
HIV Screening
Negative
Total 10
99,990

20. Example 2 (continue) 10 94,990 HIV Yes No Positive HIV Screening
With a specificity of 95%, the True Negative= 95/100 * ( )
= 95/100 * 99990
= 94990
HIV
Yes No 10
94,990
TP= True Positive
FP= False Positive
TN= True Negative
FN= False Negative
5,000
Positive
HIV Screening
Negative
Total 10
99,990

21. Example 2 (continue) 10 98,990 HIV Yes No Positive HIV Screening
If the specificity of Western Blot improves to 99%, the True Negative will
be = 99/100 * = 98990; and the False Positive = = 1000
HIV
Yes No 10
98,990
TP= True Positive
FP= False Positive
TN= True Negative
FN= False Negative
1,000
Positive
HIV Screening
Negative
Total 10
99,990

22. Example 2(continued)
In the above example, the false positive reduces from 5000 to 1000 by improving the specificity of the test!
Higher specificity will decrease the number of false positive especially in a disease of low incidence.

23. Revisit Question 1
A new ‘Super test’ claims to have a superb capability to diagnose disease X. Its sensitivity is 99% and specificity is 90%.
Which of the following statement is most correct?
The ‘Super test’ is definitely good as it has high sensitivity and specificity.
The ‘Super test’ is definitely better because its sensitivity is higher than specificity.
Specificity is the probability for a test to show a negative results in those without a particular disease.
The ‘Super test’ is not good as its specificity is below 95%
Legend:
WBC = White Blood Cell
Sens.= Sensitivity
Spec.= Specificity

24. 80 30 20 70 Revisit Question 2 Positive Negative Yes WBC count
Patients with bacteraemia (Blood culture)
Positive Negative 80 30 20 70
Yes
WBC count
= or > 15K? No
The sensitivity of “WBC” in detecting bacteraemia is:
70 / (70+30)
70 / (20+70)
80 / (80+30)
80 / (80+20)
Legend:
WBC = White Blood Cell
Sens.= Sensitivity
Spec.= Specificity

25. 60 25 40 75 Revisit Question 3 Positive “New Scan” Negative
Renal artery stenosis
Positive Negative 60 25 40 75
Positive
“New Scan”
Negative
The specificity of the “New Scan” is:
75 / (75+25)
75 / (75+40)
60 / (60+40)
60 / (60+25)
Legend:
WBC = White Blood Cell
Sens.= Sensitivity
Spec.= Specificity

26. Absolute Risk Reduction
Relative Risk
Absolute Risk Reduction
Number needed to treat

27. Relative Risk (RR)
RR: ratio of the risk of the outcome in the treatment group compared with the control group. RR is usually reported in a prospective study.
The equivocal value (cut-off value) for RR is “1”.
Example 3:
The Diabetes Control and Complication Trial investigated the effect of intensive diabetes therapy on the development and progression of neuropathy. The study reported that neuropathy occurred in 9.6% of the patients randomized to control-group and 2.8% of the patients randomized to intensive therapy.
RR= [0.028 / 0.096] = 0.29
The RR is less than 1 which means that treatment reduces the risk of neuropathy.

28. Example 3 (continued)
Absolute Risk Reduction (ARR): The absolute difference in the rates between the treatment and control groups.
Number needed to treat (NNT): The number of people who need to be treated to achieve one good outcome or prevent one adverse event.
ARR= – = 0.068
NNT= 1/ = 15
15 diabetic patients need to be treated by the ‘intensive therapy’ to prevent one neuropathy.
Reference: The effect of intensive diabetes therapy on the development and progression of neuropathy. Annals of Internal Medicine 1995; 122:561-8

29. What is the ‘number needed to treat’ to prevent one leg ulcer? 20 10 5
Revisit Question 4
A study randomised diabetic patients into treatment X (placebo) and treatment Y. It reported that leg ulcer occurred in 22% of the patients in the placebo group (treatment X) and 2% of the patients given treatment Y.
What is the ‘number needed to treat’ to prevent one leg ulcer? 20 10 5 15
Legend:
WBC = White Blood Cell
Sens.= Sensitivity
Spec.= Specificity

30. Example 4
The absolute risk for DVT in women aged 50-60yr is 1 in 10,000.
Studies show Oral Combined HRT for 5 years has a relative risk (RR) of 2.
In a cohort of 10,000 women aged 50-60yr, how many additional cases would be found in the HRT group? Which of the following is most correct?
(A) 1
(B) 2
(C) 4
(D) 6
(E) 8

31. Example 4
The absolute risk for DVT in women aged 50-60yr is 1 in 10,000.
Studies show Oral Combined HRT for 5 years has a relative risk (RR) of 2.
=> hrt/ [1/10000] =2
=> hrt = 2 x [1/10000]
==> hrt = 2/ 10000
Hence, in a cohort of 10,000 women aged 50-60yr who take oral combined HRT for 5 years, 2 may have the risk of DVT. Additional case: 2-1 = 1.

32. Example 4
The absolute risk for DVT in women aged 50-60yr is 1 in 10,000 [or 0.1 in 1000]
Studies show Oral Combined HRT for 5 years has a relative risk (RR) of 2.
In a cohort of 10,000 women aged 50-60yr who take oral combined HRT for 5 years (RR=2), additional case of DVT is 2 - 1= 1 So The most correct answer:
(A) 1
(B) 2
(C) 4
(D) 6
(E) 8

33. P-value
Confidence interval

34. An analogy for confidence interval (CI):
Passing mark for an examination is set at 65 marks
Student A scores 85 marks (95% CI 75marks – 95 marks)
Student B scores 78 marks (95%CI 60 marks – 96 marks)
Student A performs better than student B
When we are making comparison, look at the confidence intervals. 65 65

35. P value, confidence interval
Example 5:
In a case control study to investigate the potential association between lung cancer and smoking
Group 1: people with lung cancer
Group 2: people without lung cancer
The smoking history of both groups are compared.
The Null Hypothesis: there is no significant difference between the groups and their smoking history
The Alternative Hypothesis: there is significant difference between the groups and their smoking history
Legend:
df = Degree of Freedom
OR = Odds Ratio
CI = Confidence Interval

36. = [Smoking/Non-smoking]cancer/ [Smoking/Non-smoking]noncancer
Example 5 (continued)
The odds ratio O.R.
= [Smoking/Non-smoking]cancer/ [Smoking/Non-smoking]noncancer
= [12/5]/ [4/9]
= 5.4
Odds ratio is usually reported in a retrospective study or case-control study.
The equivocal value(cut-off value) for odds ratio is “1”.
Legend:
df = Degree of Freedom
OR = Odds Ratio
CI = Confidence Interval

37. The odds ratio =5.4, p=0.03, 95% confidence interval 1.2-- 26
Example 5 (continued)
The odds ratio =5.4, p=0.03, 95% confidence interval
What is your interpretation of the above results?
People who have lung cancer are 5.4 times more likely to have been smokers
The above finding is significant as the confidence interval does not include the value of 1.0
P value is the probability that an observed difference occurred by chance.
All of the above
Legend:
df = Degree of Freedom
OR = Odds Ratio
CI = Confidence Interval

38. Confidence Interval: Another example
If the odds ratio equal 1: equivocal i.e. there is no
significant association between smoking and lung cancer.
Study A: Odds Ratio for smoker to have lung cancer is 6 and the 95% confidence interval for the odds ratio is between 3 and 10
Study B: Odds Ratio for smoker to have lung cancer is 2 and the 95% confidence interval for the odds ratio is between 0.5 and 3.5

39. Confidence Interval: Another example
Study A Odds Ratio: 6 (95% CI 3 – 10)
Study B Odds Ratio: 2 (95%CI 0.5 – 3.5)
Results from Study A is more significant
Hence, when we read a research report, we should not just read the single value of odds ratio but we should read the confidence interval for the odds ratio too. 1 1

40. Revisit Question 5
A researcher reported that there was significant difference of waist circumference between male and female. The male’s waist circumference is 3cm larger than the female’s and the p-value was 0.12.
Which of the following statements is most correct?
The study was not significant because the absolute difference in waist circumference was only 3 cm.
(B) The study was significant because the p-value is greater than 0.05
(C) P value is the probability that an observed difference occurred by chance.
(D) The study was not significant because the p-value must be smaller than 0.001
Legend:
WBC = White Blood Cell
Sens.= Sensitivity
Spec.= Specificity

41. How did you go in the Quiz?
Questions?

42. An example of exam question
A new screening blood test for Beeper Phobia Disorder (BPD) was developed which detects the presence of the Beeper Phobia gene. The surgical residents at Bedpan University Hospital were screened for BPD with this new test to determine how well it identifies early cases of this dreaded disease which, if left untreated, can result in permanent mental impairment. The goal is to be able treat BPD while the residents are still asymptomatic before they are in danger of mutilating their beepers.
The results were obtained and are displayed in next slide.
Legend:
df = Degree of Freedom
OR = Odds Ratio
CI = Confidence Interval

43. (+) BPD (-) BPD Total (+) Test 90 30 120 (-) Test 10 70 80 100 200
An example of exam question (continue)
(+) BPD
(-) BPD
Total
(+) Test 90 30
120
(-) Test 10 70 80
100
200
Legend:
df = Degree of Freedom
OR = Odds Ratio
CI = Confidence Interval
What is the sensitivity of the screening test for BPD?
A. 88%
B. 70%
C. 50%
D. 90%
E. 75%

44. EBM in OSCE
You may have an OSCE station in which you are given a research paper for critical appraisal. EBM is usually integrated in the study.
Read the abstract (objectives/ hypothesis, methods, results, conclusion)
Is the objective/hypothesis clinically relevant / valid?
Methods:
Randomised controlled trial (RCT)? Retrospective? Prospective?
.Sampling method (randomised, systematic, convenience...)? Sample size?
Representative samples? Bias?
Double-blinded? Single-blinded?
Pilot run?
Ethics approval? Will the researchers publish the paper if the results are not supportive of their hypothesis?
Drop out rate? Reasons for drop out? Adverse events?

45. EBM in OSCE - continue Continue.. Results, Analysis & Discussion:
Apply your knowledge of ‘p value’, ‘confidence interval’, ‘NNT’
Are the results supportive of their hypothesis? Applicable to your patients? (compare the profile of the sample/population with the profile of your patient)
The approach/finding of the study: educational to you +/- your patients?
Sponsor for the study: conflict of interest?
Reference: RACGP Curriculum “Critical Thinking and Research”,
Dr Andrew Moreton’s Mock OSCE DVD.

46. Thank You