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Peter Jüni MD FESCpeter.juni@utoronto.ca
Director, Applied Health Research Centre (AHRC)Li Ka Shing Knowledge Institute
Professor, Department of MedicineUniversity of Toronto
Clinical evidence: separating the wheat from the chaff
Hierarchy of evidence
Hierarchy of evidence
evidenceevidence
evidence
Randomized trial
Meta-analysisNot all meta-analyses
are the same …
Heterogeneity
Jüni et al, Lancet 2004
2
Lindholm et al, Lancet 2005
• Level A– Multiple RCTs or meta-analyses
• Level B– Single RCT or large non-randomised
study• Level C
– Consensus or small studies, retrospective studies or registries
Levels of Evidence
Higgins et al, BMJ 2003
Heterogeneity: I2 Statistic
0% No heterogeneity
25% Low heterogeneity
50% Moderate heterogeneity
75% High heterogeneity
Jüni et al, Lancet 2005
I2=0%I2=0%
Lindholm et al, Lancet 2005
I2=52%I2=52%
Size
Egger et al, BMJ 1998
3
Comparison of meta-analyses with large trials
Requirements for a meta-analysis to be helpful
No or little heterogeneity between trialsAt least one moderately sized trial 50 to 75 events (binary outcome)150 to 200 patients (cont. outcome)
Symmetrical funnel plot
✔
✔
✔
Hierarchy of evidence
evidenceevidence
evidence
Randomized trial
Meta-analysis✔
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Requirements for a meta-analysis to be helpful
No or little heterogeneity between trialsAt least one moderately sized trial 50 to 75 events (binary outcome)150 to 200 patients (cont. outcome)
Symmetrical funnel plot
✗
✗
✗
Hierarchy of evidence
evidenceevidence
evidenceRandomized trialMeta-analysis✗
Observational studies of any help?
Papanikolaou et al, CMAJ 2006
Papanikolaou et al, CMAJ 2006
Relative risk
Confounding factors
Unmeasured ... Imperfectlymeasured ... Unadjusted for ...
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Propensity scores
Consecutive patients with aortic valve replacement
Transcatheter implantation: n= 114
Surgical replacement: n=1008
Piazza et al, EuroIntervention 2009
Crude 4.57 (2.17 to 9.65)4.57 (2.17 to 9.65)
TAVI more beneficial SAVR more beneficial
10.1 0.2 0.5 1 2 5 10
Odds ratio (95% CI)
Piazza et al, EuroIntervention 2009
(n=114) (n=1008)Age, y (SD) 82.8 (5.5) 69.9 (11.4) 12.9 (10.8 to 15.1) < 0.001Female 64 (56.1%) 408 (41.5%) 15.7% (6.1 to 25.3%) 0.001EuroSCORE (SD) 20.1 (13.4) 9.1 (10.2) 11.0 (9.0 to 13.1) < 0.001NYHA class <0.001 I 1 (0.9%) 147 (14.6%) II 14 (12.3%) 403 (40.0%) III 78 (68.4%) 356 (35.3%) IV 21 (18.4%) 102 (10.1%)Previous coronary bypass surgery 28 (24.6%) 42 (4.2%) 20.4% (12.4 to 28.4%) < 0.001LVEF < 0.001 > 50% 67 (58.8%) 834 (82.7%) 30-50% 40 (35.1%) 135 (13.4%) < 30% 7 (6.1%) 39 (3.9%)Atrial fibrillation 22 (19.3%) 90 (8.9%) 10.4% (2.9 to 17.8%) <0.001Cereberovascular disease 20 (17.5%) 50 (5.0) 12.6% (5.5 to 19.7%) < 0.001Peripheral vascular disease 21 (18.4%) 47 (4.7%) 13.8% (6.5 to 21.0%) < 0.001COPD 24 (21.1%) 134 (13.3%) 7.8% (0.0 to 15.5%) 0.024
Pulmonary hypertension 34 (29.8%) 86 (8.5%) 21.3% (12.7 to 29.9%) < 0.001Creatinine, umol/L (SD) 114 (92.9) 98.6 (61.5) 15.7 (3.0 to 28.3) 0.016
PDifferenceTranscatheter implantation
Surgical implantation
Crude
Multivariable
4.57 (2.17 to 9.65)
3.05 (1.09 to 8.51)
4.57 (2.17 to 9.65)
3.05 (1.09 to 8.51)
TAVI more beneficial SAVR more beneficial
10.1 0.2 0.5 1 2 5 10
Odds ratio (95% CI)
Piazza et al, EuroIntervention 2009
0
5
10
15
20
Pro
babi
lity
dens
ity
0 0.2 0.4 0.6 0.8 1
Propensity score
TAVI
SAVR
Piazza et al, EuroIntervention 2009
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Crude
Multivariable
PS adjusted
PS adjusted, multivariable
PS matched
IPT weighted
IPT weighted, multivariable
4.57 (2.17 to 9.65)
3.05 (1.09 to 8.51)
3.02 (1.01 to 9.04)
2.76 (0.88 to 8.69)
3.38 (0.90 to 12.7)
0.60 (0.11 to 3.36)
1.25 (0.42 to 3.72)
4.57 (2.17 to 9.65)
3.05 (1.09 to 8.51)
3.02 (1.01 to 9.04)
2.76 (0.88 to 8.69)
0.60 (0.11 to 3.36)
1.25 (0.42 to 3.72)
TAVI more beneficial SAVR more beneficial
10.1 0.2 0.5 1 2 5 10
Odds ratio (95% CI)
Piazza et al, EuroIntervention 2009
0
5
10
15
20
Pro
babi
lity
dens
ity
0 0.2 0.4 0.6 0.8 1
Propensity score
TAVI
SAVR
Piazza et al, EuroIntervention 2009
0
5
10
15
20
Pro
babi
lity
dens
ity
0 0.2 0.4 0.6 0.8 1
Propensity score
PS ≤ 0.325 PS > 0.325
TAVI
SAVR
Piazza et al, EuroIntervention 2009
As good (or bad) as multivariable adjustment
Da Costa et al, EuroIntervention 2014
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Observational studies
Not to reliably estimate treatment effects
in the absence of RCTs …
Vandenbroucke & Psaty, JAMA 2008
To understand the full spectrum of adverse effects — those that occur late, that werenot known beforehand, and that are rarebut nevertheless serious — and to be able
to investigate the true incidence of knownadverse effects in circumstances ofactual prescribing, well-designed observational studies will always be
necessary.
To understand the full spectrum of adverse effects — those that occur late, that werenot known beforehand, and that are rarebut nevertheless serious — and to be able
to investigate the true incidence of knownadverse effects in circumstances ofactual prescribing, well-designed observational studies will always be
necessary.Daemen et al, Lancet 2007
8
Incidence of stent thrombosis with DES
Daemen et al, Lancet 2007
NNH & NNT
Myocardial infarction, versus
control: NNH ~610
Ulcer complications, versus
naproxen: NNT ~130
Ray et al, Lancet 2002
Major cardiovascular disease 42%
Peptic ulcer or 3%gastrointestinal bleeding
Baseline Risk and NNT/NNH
0
200
400
600
800
1000
1 10 100 500
Events per 1000 PY
Num
ber
need
ed t
o ha
rm
Extrapolation to routine settings: rofecoxib & myocardial infarction
0
10
20
30
Eve
nts
per
1000
PY
x 2.24 x 2.24
Trials Routine
NNH610 NNH70
ControlRofecoxib
Jüni et al, Lancet 2005
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Advantages of (properlyconducted & large) randomised trials
No confounding
No fishing
A drug simply cannot be declared “safe”without measuring the balance of benefits
and risks in a randomized controlled trialover an appropriate period of time in a large population representing those who will use
the treatment in practice.
A drug simply cannot be declared “safe”without measuring the balance of benefits
and risks in a randomized controlled trialover an appropriate period of time in a large population representing those who will use
the treatment in practice.
Califf, JAMA 2005
Thank you
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