Medical Statistics
Joan Morris ([email protected])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