Discussion of methodological approaches, as well as their strengths and limitations, for conducting patient oriented research.

1. 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

2. 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

3. 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

4. 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

5. Study Designs in Epidemiology
1. Clinical Trial
2. Cohort
3. Case-control
4. Cross-sectional/ecologic
5. Case series
6. Case reports
Analytic
Descriptive

6. 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

7. Study Designs in Epidemiology
1. Clinical Trial
2. Cohort
3. Case-control
4. Cross-sectional/ecologic
5. Case series
6. Case reports
Analytic
Descriptive

8. Population based studies: Unifying
theory for analytical studies
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o allocation
process
Exposed
Unexposed
study time
Endofobservationperiod
♦ = Study outcome
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Study population
↑Confounding & Selection Bias ↑ ↑ Information Bias ↑Error Sources:

9. 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

10. 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

11. Case-Control
Disease
Present Absent
(case) (control)
Present A B
(exposed)
Absent C D
(unexposed)
CohortStudy
Factor
Odds ratio = AD/BC
Relative risk A/A+B
C/C+D

12. Types of Associations
• None (independent events)
• Spurious
– Chance (random variation)
– Bias (systematic variation)
• Indirect (confounding)
• Causal

13. Types of Associations
• None (independent events)
• Spurious
– Chance (random variation)
– Bias (systematic variation)
• Indirect (confounding)
• Causal

14. 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!

15. Types of Associations
• None (independent events)
• Spurious
– Chance (random variation)
– Bias (systematic variation)
• Indirect (confounding)
• Causal

16. 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

17. Types of Associations
• None (independent events)
• Spurious
– Chance (random variation)
– Bias (systematic variation)
• Indirect (confounding)
• Causal

18. 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

19. Types of Associations
• None (independent events)
• Spurious
– Chance (random variation)
– Bias (systematic variation)
• Indirect (confounding)
• Causal

20. Criteria for Causation
• Strength of association (OR, RR)
• Biologic credibility
• Consistency with other studies
• Time sequence
• Dose response
• Study design

21. What percent of observational studies of
treatment effect are confirmed by RCTs
1. 10%
2. 25%
3. 50%
4. 75%

22. 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

23. 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

24. 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

25. 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

26. 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

27. 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

28. 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!