number need to treat

Number Need to Treat

remember to round it to whole numbers

Clinical questionsAbnormality 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

Cohort study

Cohort study, case control study

Prevalence

Cohort study, case control study

Clinical trial

Clinical trial

Matching the strongest design to clinical question

The Six Ds Outcome of Disease

• Death

• Disease/Illness

• Discomfort

• Disability

• Dissatisfaction

• Destitution

Study & Bias

SampleSample

Selection bias

Conclusion

Measurement, confounding bias

All patients with the condition of interest Internal validity

External validity

Sampling

???

Efficacy vs. Effectiveness

The story of selling bug-killer

Well, if this does not kill every of the bug, I will

give you $1000000000000

000 in return!

I have try it, but it does not work!

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!

Efficacious treatment

Effective treatment

One that has the desired effects among those who receive it

One does more good than harm in those to whom it is offered

Population of patients

with the condition

sample

sample

Population of patients

with the condition

Cross over

Cross over

Drop out

Drop out

Drop out

Drop out

analyze according

to treatment assigned

analyze according

to treatment recieved

Intention to Treat analysis

Per treatment analysis

i.e. effectivness

i.e.

efficacy

Efficacy Trial

Effectiveness Trial

Internal validity

Generalizability

Noncompliance

Less selected patient

Less selected clinician

Costs

Impracticality

Other

Fletcher 3rd

Examination paper 2000/5/30Drug 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.

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 3.5

Drug B vs. Drug A

19%-12%=7%

14.28 2% 50 3.5



NNH LHH = NNH/NNT

Drug A vs. Placebo

7% 14.29 2% 50 3.5

Drug B vs. Placebo

14% 7.14 4% 25 3.5

Drug B vs. Drug A

19%-12%=7%

14.28 2% 50 3.5

Both drug A and B are more effective than placebo, though drug B is more efficacious than drug A

Both drug A and B are more effective than placebo, though drug B is more efficacious than drug A



NNH LHH

Drug A vs. Placebo

7% 14.29 2% 50 3.5

Drug B vs. Placebo

14% 7.14 4% 25 3.5

Drug B vs. Drug A

7% 14.28 2% 50 3.5

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

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

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.

number need to treat

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