Modelling Stroke in the Laboratory - Separating Fact from Artefact The impact of sources of bias in animal models of neurological disease, and what we should do about it Malcolm Macleod Senior Lecturer, Centre for Clinical Brain Sciences University of Edinburgh
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Modelling Stroke in the Laboratory - Separating Fact from Artefact The impact of sources of bias in animal models of neurological disease, and what we.
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Modelling Stroke in the Laboratory - Separating Fact
from ArtefactThe impact of sources of bias in animal
models of neurological disease, and what we should do about it
Malcolm MacleodSenior Lecturer, Centre for Clinical Brain Sciences
University of Edinburgh
1026
1026 interventions in experimental stroke
O’C
olli
ns
et
al A
nn N
euro
l 2006
1026603
1026 interventions in experimental stroke
Tested in focal ischaemia
O’C
olli
ns
et
al A
nn N
euro
l 2006
1026883374
1026 interventions in experimental stroke
Effective in focal ischaemia
O’C
olli
ns
et
al A
nn N
euro
l 2006
1026883550
97 18
1026 interventions in experimental stroke
Tested in clinical trial
O’C
olli
ns
et
al A
nn N
euro
l 2006
1026883550
97 171 3
1026 interventions in experimental stroke
Effective in clinical trial
O’C
olli
ns
et
al A
nn N
euro
l 2006
Where are we going wrong?
• Are animal experiments falsely positive?
• Have clinical trials tested the
conditions of maximum efficacy?
… and what, if anything, does this
mean for models of other diseases?
Back
gro
und
Control half dose full dose
Infa
rct V
olum
e
0
50
100
150
200
250
300
10-120 M 10-60 M
Animal data in stroke• There are huge
amounts of often confusing data
• Systematic review can help to make sense of it
• If you select extreme bits of the evidence you can “prove” either harm or substantial benefit
• However, if you have a precise and highly significant overall effect, then it is probably real
Hypothermia101 publications277 experiments
3353 animals
Bett
er
Wors
e
van d
er
Worp
et
al B
rain
2007
-100
0
100
200
Potential sources of bias in animal studies
• Internal validity
– Low sample size
• External validity– Publication bias – Are the models we use good models?
• Co-morbidities
Problem Solution
Selection Bias Randomisation
Performance Bias Allocation Concealment
Detection Bias Blinded outcome assessment
Attrition bias Reporting drop-outs/ ITT analysis
Cro
ssle
y e
t al, S
troke
200
8
Internal Validity NXY-059
Macl
eod
et
al, S
troke
2008
9 publications29 experiments
408 animalsImproved outcome by 44% (35-53%)
Internal ValidityHypothermia
van d
er
Worp
et
al B
rain
2007
Randomisation
Yes No
Blinded outcome
assessment
Yes No
101 publications277 experiments
3353 animalsImproved outcome by 44% (35-53%)
Internal Validity Stem Cell based therapies
• Infarct Volume
• Neurobehavioural score:
Jen L
ees,
un
publis
hed
54 publications127 experiments
2012 animalsImproved outcome by 29% (25-33%)
72 publications111 experiments
1876 animalsImproved outcome by 34% (30-39%)
RandomisationStem Cell based therapies
Jen L
ees,
un
publis
hed
Blinded outcome assessmentStem Cell based therapies
Jen L
ees,
un
publis
hed
What does this mean?Modelling the efficacy of tPA
“Standard”HealthyMale Rat
No randomisationHalothane anaesthesiaQuantify infarct volume
with TTC
25%
“Co-morbid”Hypertensive
Male Rat
No randomisationHalothane anaesthesiaQuantify infarct volume