david sackett symposium: a substitute for randomized...
TRANSCRIPT
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David Sackett Symposium: A Substitute for Randomized Trials
Donald A. Redelmeier University of Toronto
Sunnybrook Hospital
General Internal Medicine
Institute for Clinical Evaluative Sciences
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Conflicts of Interest Disclosure
• Practicing Medicine in Ontario • Canada Research Chairs Program • Canadian Institutes of Health Research • PSI Foundation of Ontario • National Institutes of Health Research • Heart and Stroke Foundation of Ontario • Redelmeier’s own Ego Bias
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Potential Conflicts of Interest
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Background: Joyful Strengths • proof of causality • fabulous agricultural heritage • durable immortality • impressive quality control • simplistic writing • easily published • fabulous marketing • not often refuted • opportunities for more • lucrative grants
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Each Strength has a Rebuttal! • fallible causal inference • forgotten agricultural heritage • transient clinical relevance • vexatious quality control • formulaic writing • slow to get published • simplistic marketing • impediments to replication • restricted access for analyses • exorbitant grants
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Babies and Bathwater
• no methodology is perfect • different tools for the job • no denial of past success
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A New Substitute for an RCT: Exposure Crossover Design
Dow Jones Industrial Average (6 months)
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A Before and After Perspective
Intervention
Outcome }
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Can Pregnancy Cause Venous Clots?
n = 507,262
0
50
100
150
200
250
300
350
400
450
500
Pregnancy Baseline Subsequent
Count
-4 -3 -2 -1 0 +1
Time (years)
Delivery
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Does Pregnancy Prevent Bike Crashes?
n = 507,262
Pregnancy Baseline Subsequent
Count
-4 -3 -2 -1 0 +1
Time (years)
0
5
10
15
20
25
30
35
40
45
50
Delivery
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Can Pregnancy Reduce Depression?
n = 507,262
Pregnancy Baseline Subsequent
Count
-4 -3 -2 -1 0 +1
Time (years)
0
50
100
150
200
250
300
350
400
450
500
Delivery
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0
10
20
30
40
50
Does Kidney Transplantation Increase the Risk of Herpes Infections?
n = 4,905
Induction Baseline Subsequent
Count
-4 -3 -2 -1 0 +1
Time (years)
Transplantation
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Do Physician Warnings Change the Risk of a Road Crash?
n = 100,075
Baseline Induction Subsequent
Count
-4 -3 -2 -1 0 +1
Time (years)
0
50
100
150
200
250
300
350
400
450
500
Warning
NEJM 2012
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Collapsing a Display into a few Numbers
Baseline Rate*
4.76
Subsequent Rate*
2.73
* crashes per 1,000 annually
Relative Risk
0.55
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Different Medical Diagnoses
DIAGNOSIS
Baseline Rate
Subsequent Rate
Relative Risk
95% Conf. Inter.
Alcoholism 7.24 4.91 0.64 0.46 – 0.91
Epilepsy 5.92 3.23 0.53 0.36 – 0.78
Dementia 2.92 0.86 0.31 0.18 – 0.58
Sleep Disorder 6.10 3.85 0.62 0.46 – 0.85
Syncope 5.91 2.95 0.49 0.38 – 0.64
Stroke 3.50 1.15 0.32 0.19 – 0.60
Diabetes 4.49 2.71 0.59 0.43 – 0.82
Depression 8.75 3.60 0.38 0.25 – 0.60
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Different Physician Characteristics
RESPONSIBLE PHYSICIAN
Baseline Rate
Subsequent Rate
Relative Risk
95% Conf. Inter.
Age < 50 years 4.43 2.72 0.60 0.51 - 0.71 Age ≥ 50 years 5.51 2.76 0.48 0.38 - 0.61
Male gender 4.58 2.68 0.56 0.49 - 0.65 Female gender 5.92 3.05 0.51 0.37 - 0.73
General Practice 4.48 2.74 0.56 0.47 - 0.68 Specialty Practice 5.21 2.71 0.54 0.44 - 0.67
Years in Practice < 20 4.51 2.68 0.58 0.48 - 0.69 Years in Practice ≥ 20 5.13 2.80 0.53 0.43 - 0.65
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Summary of Exposure Crossover Design
Allows self matching to control measured and unmeasured individual factors
Requires a durable intervention with a clear starting date
Focuses on outcomes that are recurrent, relapsing, or otherwise repeated
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Limitations of Exposure Crossover Design
• unstable baseline interval • subtle forms of confounding • conglomerate interventions • inadequate sample size • insufficient time duration • potential survivor bias • selection bias of participants
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Strengths of Exposure Crossover Design
• controls unmeasured stable confounders • straightforward basic statistics • intuitive interpretation of findings • simple graphical display of results • low marginal financial costs • no endless logistical hassles • zero need to assign placebos • “Real World” instead of “Disney World”
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Other Self Matching Designs: Not Exposure Crossover Design
• Case Crossover Design (relative risks)
• N-of-1 Trials (brief effects)
• Self Controlled Case Series (single outcome)
• Time Series Analysis (aggregated perspective)
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Name for Graph
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Take Home Message The Exposure Crossover design is a new self-matching approach for testing clinical questions when a randomized trial is not possible.
Self-Matched Studies
Randomized Controlled Trials