1. remember to round it to whole numbers
Number Need to Treat
In therapy studies, treat ment effects from binary outcomes, such as “positive” or “negative”, can be present in various ways (e.g., relative risk reduction, absolute risk reduction, number needed to treat) [1 ]. LAUPACIS et al introduced the concept of number needed to treat as an alternative approach to summarizing the effect of treatment [2 ]. The number needed to treat is defining as “the number of patients who need to be treat ed to prevent one additional adverse even” [3 , 4 ]. When the experimental treatment increases the risk of an undesirable outcome/event the number needed to harm can be compute. The number needed to harm has the same mathematical expression as number needed to treat [1, 5 ]
remember to round it to whole numbers

2. Clinical questions Matching the strongest design to clinical question
Abnormality
Is the patient sick or well?
Diagnosis
How accurate are tests used to diagnose disease?
Frequency
How often does a disease occur?
Risk
What factors are associated with an increased risk of disease?
Prognosis
What are the consequences of having a disease?
Treatment
How does treatment change the course of disease?
Prevention
Does early detection and treatment improve the course of disease?
Cause
What cause the disease?
Cost
How much will care for an illness cost?
Prevalence
Prevalence
Cohort study, case control study
Cohort study
Clinical trial
Clinical trial
What is the difference between risk and Hazard?
A hazard is a substance, agent, or physical situation with a potential for harm in terms of injury or ill health, damage to property, damage to the environment, or a combination of these.
It is a noun.
Risk relates to the likelihood of the harm or undesired event occuring, and the consequence of its occurrence. It is a function of both exposure to the harzard and the likelihood of harm from the hazard.
It is a probability.
Oxford textbook of public health p1047
Cohort study, case control study

3. The Six Ds Outcome of Disease
Death
Disease/Illness
Discomfort
Disability
Dissatisfaction
Destitution

4. Study & Bias

5. All patients with the condition of interest
Internal validity
Sampling
Sample
Sample
Selection bias
Measurement, confounding bias
???
External validity
Conclusion

6. Efficacy vs. Effectiveness

7. The story of selling bug-killer
Well, if this does not kill every of the bug, I will give you $ in return!

8. I have try it, but it does not work!

9. Oh! I have forgotten to told you, you have to put the drug into every bug’s mouth! If it does not kill it, don’t hesistate to come back!

10. Efficacious treatment
One that has the desired effects among those who receive it
Effective treatment
One does more good than harm in those to whom it is offered

11. Intention to Treat analysis analyze according to treatment assigned
Drop out
analyze according to treatment assigned
i.e. effectivness
Population of patients with the condition
sample
Cross over
Drop out
Drop out
analyze according to treatment recieved
i.e.
efficacy
Population of patients with the condition
Cross over
sample
Per treatment analysis
Drop out

12. Efficacy Trial Internal validity Generalizability Effectiveness Trial
Noncompliance
Less selected patient
Less selected clinician
Costs
Impracticality
Other
Internal validity
Generalizability
Effectiveness Trial
Fletcher 3rd

13. Examination paper 2000/5/30
Drug A
Drug B
Placebo
% patients with reduction in number of complications
12%
19% 5%
% patients with side effects 4% 6% 2%
A randomised clinical trial was carried out with sample size of 500 patients to determine whether drug A or B is better at reducing the number of complications in a particular disease. Both drugs were compared to placebo.

14. B1a: Calculate the NNT ARR (treatment effect) NNT ARI (side effect)
NNH
LHH=NNH /NNT
Drug A vs. Placebo
12%- 5%=7%
14.29 2% 50
3.5
Drug B vs. Placebo
19%- 5%=14%
7.14 4% 25
Drug B vs. Drug A
19%- 12%=7%
14.28
ARR = ABI = Absolute benefit increase
ARI = Absolute risk increase
LHH: Likelihood to be helped versus harmed

15. B1a: Calculate the NNT
ARR (treatment effect)
NNT
ARI (side effect)
NNH
LHH = NNH/NNT
Drug A vs. Placebo 7%
14.29 2% 50
3.5
Drug B vs. Placebo
14%
7.14 4% 25
Drug B vs. Drug A
19%- 12%=7%
14.28
Both drug A and B are more effective than placebo, though drug B is more efficacious than drug A

16. B1a: Calculate the NNT
ARR (treatment effect)
NNT
ARI (side effect)
NNH
LHH
Drug A vs. Placebo 7%
14.29 2% 50
3.5
Drug B vs. Placebo
14%
7.14 4% 25
Drug B vs. Drug A
14.28
Drug B is also more effective than drug B as patient more likely to be helped than harmed when they use drug B rather than drug A
We have to treat more people to show the benefit of drug B over drug A than that of placebo

17. B1c: Potential benefits for using NNT
Impact of treatment is related to the baseline risk of the adverse outcome it is designed to prevent
easier to derive risk-benefit analysis before making clinical decision.
easier to interpret than relative risk, odds ration and relative risk reduction and thus easier to communicate with colleagues, nurses and general public.
it is a measure of therapuetic effort required to obtain one beneficial event. Consequently, it is useful in comparing utility of treatments when we have comparable trials with comparable outcomes in comparable patients.
it is a measure of therapeutic effort required to obtain one beneficial event.

18. Study