Medical Statistics

Joan Morris (j.k.morris@qmul.ac.uk)Professor of Medical Statistics

Goldsmiths Lecture 2014

Aims

• To give a brief description of some different areas of medical statistics

– Folic acid and Neural Tube Defects

– Screening for Heart Disease

Folic Acid and Neural Tube Defects

Can folic acid reduce neural tube defects (e.g. spina bifida)?

• MRC Vitamin trial - randomised controlled trial

Randomised Controlled Trial

• A clinical trial is an experiment in which a

treatment is administered to humans in order to

evaluate its efficacy and safety

• Controlled = a comparison group

• Randomised = allocated to groups on basis of

chance e.g. tossing a coin (ensures fair

comparison)

Can folic acid reduce neural tube defects (e.g. spina bifida)?

• MRC Vitamin trial - randomised controlled trial

• Large: 1817 women who had had a previous NTD, 33 centres, 7 countries

Folic Acid vs Placebo forNeural Tube Defects

Lancet 1991 

 

  

 

    Neural Tube Defects

    Yes No Total

Folic Acid

Yes 6 587 593

No 21 581 602

Risk of NTD in treated group =Risk of NTD in control group =

Relative Risk of NTD in treated group compared to control group =

1%3.5%

1%/3.5% = 0.29

Folic Acid vs Placebo forNeural Tube Defects

RR = 0.29

95% Confidence Interval : 0.10 to 0.76

P = 0.008

Can folic acid reduce neural tube defects (e.g. spina bifida)?

• Results : Women who did not receive folic acid were 3 times more likely to have a second NTD pregnancy

• Impact : Women are advised to take folic acid PRIOR to becoming pregnant

Statisticians Involvement

• Planning the study – how large

• Analysing the results

• Stopping the study early (Independent Data Monitoring Committee)

What Dose ?

• Women in MRC trial had had a previous NTD pregnancy and were given 4mg folic acid per day

• Current recommendation is 0.4mg folic acid per day

Dose Folic Acid

Serum Folate Level

Risk of NTD pregnancy

?

Dose Folic Acid

Serum Folate Level

Risk of NTD pregnancy

01

23

45

67

8N

TD

pre

vale

nce

per

10

00 b

irths

0 2 4 6 8 10Plasma folate (ng/ml)

Folic Acid and NTD Dose Response

Folic Acid and NTD Dose Response01

23

45

67

8N

TD

pre

vale

nce

per

10

00 b

irths

0 2 4 6 8 10Plasma folate (ng/ml)

Interpretation

• The same proportional increase in serum folate has the same proportional reduction in NTD

• All women benefit from taking folic acid. There is not a threshold effect

Conclusions

Women planning a pregnancy should take 5mg folic acid tablets daily, instead of the 0.4mg dose presently recommended

(THE LANCET • Vol 358 • December 15, 2001)

MRC Trial

Fortification (0.2mg/day)

Use of Statistics in Screening

Screening is the identification, among apparently healthy individuals, of those who are sufficiently at risk from a specific disorder to benefit from a subsequent diagnostic test, procedure or direct preventive action.

Screening for Heart Disease

Relative odds of major IHD event by fifths of the distribution of haemostatic and lipid markers for all men (•——•) and for men free of IHD at baseline examination ( ––– ).∘ ∘

Yarnell J et al. Eur Heart J 2004;25:1049-1056

The European Society of Cardiology

AffectedUnaffected

Biomarker : ZZ

AffectedUnaffected

Screen negative Screen positive

Biomarker : ZZ

Screen negative Screen positive

Biomarker : ZZ

False positives

False negatives

Risk Factor

Unaffected Affected

Good test

Screening for a medical disorder

Risk Factor

Unaffected Affected

Poor test

Screening for a medical disorder

Is Cholesterol any good for screening ?

2

4

6

8

.2 .4 .6 .8fol

AffectedUnaffected

Risk screen

converterhttp://

www.wolfson.qmul.ac.uk/rsc/

Detection Rate

False Positive Rate

4.2mm Hg

7.5mm Hg

• Are there any good screening tests ?

Antenatal screening for Down’s syndrome

Quadruple test markers

0.25 0.5 1 2 4 8 16

Maternal serum total hCG (MoM)

0.25 0.5 1 2 4 8 16

Maternal serum inhibin-A (MoM)

Total hCG Inhibin-A

0.25 0.5 1 2 4 8 16

Maternal serum AFP (MoM)

0.25 0.5 1 2 4 8 16

Maternal serum uE3 (MoM)

AFP uE3

Down’s syndrome

Unaffected Down’s syndrome

Unaffected

Down’s syndrome

Down’s syndrome

Unaffected Unaffected

01:108 1:106 1:104 1:102 1:1 102:1 104:1

Down’s syndrome

Unaffected

Distribution of risk in Down’s syndrome and unaffected pregnancies using AFP, uE3, total hCG and inhibin-A

measured at 14-20 weeks (+ maternal age)

Risk of a Down’s syndrome pregnancy at term

Method : Monte Carlo Simulation

•Generate a population of 500,000 people aged 0-89 years. [Use Office for National Statistics Population Data for England and Wales]

•Assign risk factors (eg diabetes, smoking, blood pressure) [Use Health of the Nation Survey]

•Calculate a persons risk [Use Framingham risk equations]

•Assign deaths according to people’s risks

Conclusion

• Age is as good at predicting heart disease as measuring conventional risk factors

• Therefore treatment should be offered on the basis of age

Treatment to Prevent Heart Disease

• Blood Pressure Lowering Drugs– What dose– Which drug

Several studies looking at the same thing

• Each study may be relatively inconclusive because of too much uncertainty (too small)

• Meta-analysis : statistical method of combining and presenting results from several studies

• Can indicate more robust results

Blood pressure reduction (mmHg)

Major influence for prescription of combination therapy as first line of action

1 Drug

Standard dose

3 Drugs

Half standard dose

1 Drug

Standard dose

3 Drugs

Half standard dose

7 mm Hg

20 mm Hg 10%

4%

Reduction in blood pressure People reporting side effects

BMJ 2009;338:b1665

• A reduction in blood pressure of 20mm Hg halves the risk of a CHD event or stroke regardless of the person’s original blood pressure or their level of cardiovascular risk .

• This means that everyone at sufficient cardiovascular risk will benefit from a reduction in blood pressure, even if they don’t have a high blood pressure. For example all people with diabetes should be offered treatment.

BMJ 2009;338:b1665

Involvement of Statistician

• Study design for clinical trial

• Analysing data from clinical trial

• Meta analysis from several trials

• Monte Carlo simulation using results above

Conclusion

As much about collection, interpretation and presentation as calculation

Making sense out of uncertainty