Post on 14-Feb-2017
Clinical Trials, Epidemiology,
and Biostatistics in Skin
Disease
Joel M. Gelfand, MD, MSCE
Professor of Dermatology and Epidemiology
Vice Chair for Clinical Research
Medical Director, Clinical Studies Unit
Director, Psoriasis and Phototherapy Treatment Center
University of Pennsylvania Perelman School of Medicine
Disclosure and funding statement
• Investigator and/or consultant for Amgen, Abbvie, Jansen, Merck (DSMB),
Pfizer, Lilly, Celgene, Coherus (DSMB), Novartis, Sanofi, Valeant, and
Astrazenaca
• Patent – Resiquimod for CTCL
• This presentation is the sole work of Dr. Gelfand
Definition
• Epidemiology is the study of the distribution and determinants of health and disease in populations
• Clinical epidemiology extends the principles of
epidemiology to the critical evaluation of diagnostic and
therapeutic modalities in clinical practice
• Pharmacoepidemiology: The study of drug effects in
large populations of patients
• Epidemiology is the basic science underlying much of
public health, preventative medicine, and individual
patient care decisions
Study Design Issues:
Get help early!• Well formulated study
question
• Define exposure,
outcomes, confounding
factors
• Minimize selection and
information bias
• Plan for statistical error
• Analysis plan
To call in the statistician after
the experiment is done may
be no more than asking him
to perform a post-mortem
examination: he may be able
to say what the experiment
died of.-RA Fisher
Study Designs in Epidemiology
1. Clinical Trial
2. Cohort
3. Case-control
4. Cross-sectional/ecologic
5. Case series
6. Case reports
Analytic
Descriptive
Cross-sectional studies
• Definition – The status of an individual with respect to the presence or absence of both exposure and disease is assessed at the same point in time
• Use – to establish prevalence and hypothesis generation
• Limitation – can not establish temporal relationship
• Example – beta carotene and cancer
Study Designs in Epidemiology
1. Clinical Trial
2. Cohort
3. Case-control
4. Cross-sectional/ecologic
5. Case series
6. Case reports
Analytic
Descriptive
Population based studies: Unifying
theory for analytical studies
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Exposed
Unexposed
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♦ = Study outcome
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Study population
↑Confounding & Selection Bias ↑ ↑ Information Bias ↑Error Sources:
Case- Control Studies
• Definition – A study comparing diseased patients to non disease patients, looking for differences in risk factors.
• Use – the study of multiple risk factors for a single disease, especially for rare diseases
• Limitation – bias in exposure data
• Example – Doll and Hill 1950, smoking and lung cancer
Cohort Study
• Definition – A study which selects subjects
on the basis of the presence or absence of
exposure to a factor of interest and follows
them to determine their outcome
• Use – To study multiple outcomes from an
exposure
• Limitation – Prolonged, Costly
• Example – PUVA cohort study
Case-Control
DiseasePresent Absent(case) (control)
Present A B(exposed)
Absent C D(unexposed)C
oh
ort
Stu
dy
Facto
r
Odds ratio = AD/BCRelative risk A/A+B
C/C+D
Types of Associations
• None (independent events)
• Spurious
– Chance (random variation)
– Bias (systematic variation)
• Indirect (confounding)
• Causal
Types of Associations
• None (independent events)
• Spurious
– Chance (random variation)
– Bias (systematic variation)
• Indirect (confounding)
• Causal
Biostatistics
Key Principles
• Methods allow one to estimate the probability that the observation is due to chance (P value)
• Assumes that you have drawn a random unbiased sample from the population you wish to study.
• It addresses the variability inherent in drawing samples from populations.
Key Questions
• Type of data
• Distribution of data
• Inferential techniques
• Multivariable techniques
• Type 1 (alpha error) and
Type 2 (beta error/power)
• Don’t over rely on P
values!
Types of Associations
• None (independent events)
• Spurious
– Chance (random variation)
– Bias (systematic variation)
• Indirect (confounding)
• Causal
Bias
• Definition – A systematic error in collecting or interpreting data
• Selection bias – A distortion in the estimate of effect resulting from the manner in which subjects are selected for the study
• Information bias - A distortion in the estimate of effect due to measurement error or misclassification of subjects on one or more variables– Recall bias
Types of Associations
• None (independent events)
• Spurious
– Chance (random variation)
– Bias (systematic variation)
• Indirect (confounding)
• Causal
Confounding
• Definition – An observed association (or
lack of association) that is due to a mixing
of effects between exposure, the outcome,
and a third factor.
E D
F
A confounder is associated
with the exposure of interest,
and independent of that
exposure, is a risk factor for
the disease
Types of Associations
• None (independent events)
• Spurious
– Chance (random variation)
– Bias (systematic variation)
• Indirect (confounding)
• Causal
Criteria for Causation
• Strength of association (OR, RR)
• Biologic credibility
• Consistency with other studies
• Time sequence
• Dose response
• Study design
What percent of observational studies of
treatment effect are confirmed by RCTs
1. 10%
2. 25%
3. 50%
4. 75%
Probability of observational studies
being confirmed by RCTs
1. 10%
2. 25%
3. 50%
4. 75%
Confirmation rate of
preclinical research
Confirmation rate of
observational research
Begley CG and Ellis LM Nature 2012:483:531-533
Ioannidis JPA et al JAMA 2001:286;821-830
Clinical Trial
• Definition - The investigator determines
which patients receive an exposure and
then follows the patients for the outcome
• Use- Gold standard to establish causality
• Limitations – generalizability, ethical
issues
• Example – polio vaccine trials (1950) RCT
of >1 million school age children
Ethical Issues
• A conflict exists between the role of
physician (commitment entirely to patient)
and investigator (commitment to
research).
• Concept of Equipoise – the benefit of a
treatment relative to placebo is unknown
Ethical Issues and the IRB
• 1999 Jesse Gelsinger who had ornithine
transcarbamylase (OTC) deficiency, a rare
but controllable metabolic disorder, dies is
a phase I gene therapy trial at PENN.
• June 2001 Ellen Roche, a 24 year old
healthy woman dies in study at Hopkins’
• Multiple FDA letter’s censuring/banning
investigators
Lessons (re)learned from
Efalizumab• 2003 FDA approved Efalizumab
– 2764 patients treated, 218 treated > 1 year
• 2009 Withdrawn– 46,000 patients treated
– 3000 treated for ≥ 2 years
– 3 confirmed and one suspected case of PML spontaneously reported
• Estimated risk of PML in efalizumab treated
patients:
– Overall: 1 in 15,000 per year
– Patients treated > 2 years: 1 in 1000
– Likely an underestimate due to incomplete reporting
Perspective
“All scientific work is incomplete, whether it be observational or experimental. All scientific work is liable to be upset or modified by advancing knowledge. That does not confer upon us the freedom to ignore the knowledge we already have, or to postpone the action that it appears to demand at a given time”
- Sir Austin Bradford Hill
Resources
• JAMA Evidence: http://jamaevidence.mhmedical.com/book.aspx?bookID=847
• Cohrane reviews: http://www.cochrane.org/
• American Dermatoepidemiology Network (ADEN) http://www.adenet.us/
• Hennekens and Buring. Epidemiology in Medicine. Little, Brown and Company. Boston. 1987
• Barzilai, et al. Dermatoepidemiology.J Am Acad Dermatol. 2005 Apr;52(4):559-73
for dermatoepidemiology!