Title: Experimental Studies
1Experimental Studies
- Two primary categories of experimental studies
- General difference is the unit of observation
- Community intervention trials
- Focus is groups or community outcome
- For evaluating large scale efficacy of new
programs/policies - Ex Fluoridation Trial, Stanford Five-City Trial
- Clinical trials
- Focus is on individuals
- More rigidly controlled than community trial
2Experimental Studies
- Types of clinical trials
- Drug trials
- Treatment trials
- Example Aspirin trial
- Prevention trials
- Example HDFP (high BP detection and follow-up
trial) - Behavioral intervention trials
- Vaccine trials
- Hep-A Vaccine Trial in Monroe, NY
- Surgical trials
- Example Radical mastectomy vs. lumpectomy
3Experimental Studies
- General features inherent to methodology
- prospective
- control group
- Intervention (drug, vaccine, surgical technique,
etc.) - investigator controls/ manipulates conditions
studied (hence an experiment) - assignment of exposure
4Experimental Studies
- From Modern Epidemiology, 2nd Ed.
- Epidemiologic experimentation reduces variation
by extraneous factors in comparison with the
study factors
5Efficacy vs Effectiveness
- Efficacy can the treatment work under ideal
conditions - more good than harm among those who receive it
- established by restricting study to patients who
will follow medical advice
6Efficacy vs Effectiveness
- Effectiveness can the treatment work under
normal (ordinary) conditions - more good than harm
- established by offering treatment to patients and
allowing them to decide to accept or reject - if treatment ineffective, could be due to lack of
efficacy, acceptance, or compliance
7Efficacy vs Effectiveness
- Compliance - the extent to which patients follow
medical advice - intervenes between an efficacious treatment and
an effective one - not just willful neglect of advice
- failure to understanding instructions, failure to
keep prescription filled, money, and insurance
coverage - limit effectiveness regardless of efficacy
8Strength of Evidence
- Weak Strong
- Case reports Randomized
- Case series trials
Observational studies
9Study Design
- Randomized trials
- Randomized control study
- Cross-over trial
- Withdrawal study
- Factorial design study
- Group allocation study
- Large simple trial
- Multi-center trial
10Study Design
- Non-randomized trials
- Concurrent non-randomized trial
- Historical control trial (nonconcurrent)
- Hybrid study
- Equivalency trial
11Study Design
- Generally, the appropriate study design is
dictated by the research question - Regardless of design, assignment of exposure done
by investigator (hence experiment) - Ethical constraints may limit feasibility or
dictate study design
12Study design
- Origins from non-clinical settings (agricultural,
industrial, laboratory) where investigator has
greatest degree of control over - subjects
- structure of study
- size of study
13Study design
- Clinical trials on humans differ
- greater variability of response to treatments
- ethical constraints
- simultaneous testing of subjects not feasible,
hence longer duration studies
14Study design Phase I, II, III
- Licensing of a product generally requires three
phases - Phase I small group (lt100)
- Vaccine trial demonstration of response safety
- Drug trial establish maximally tolerate dose
(MTD) dose range identification of toxic
effects - Phase II larger group (100-200)
- Vaccine trial assess antibody response and
reactions - Drug trial - efficacy in dose range validate
Phase I - Phase III assess efficacy and effectiveness
15Randomized Control Trials
- Assignment of intervention by randomization
- Comparison of effect among intervention group to
no effect in control group - Equal probability of participants to be assigned
to intervention or control group - Gold standard to which all other trials are
compared
16Randomization
- Simple definition
- each participant has equal probability of
assignment to intervention or control group - random allocation of subjects is the basis for
statistical inference
17Randomization technical considerations
- Comparability assure comparability with respect
to known and unknown risk factors - Bias minimize (or eliminate) bias
- removing control of assignment from investigator
non-discoverable process - guarantees that treatment assignment not based on
patient prognostic factors - Validity quantify errors attributable to chance
18Bias associated with randomization
- Selection bias occurs if method of allocation
is predictable could influence participation if
anticipate treatment assignment - Accidental bias if balance on risk or
prognostic factors is not achieved more a
problem in small studies - Miscellaneous sources of bias
- treatment administration
- outcomes assessment
19Confounding and randomization
- Confounding prevented by randomization
- some argue randomization is unnecessary since can
be controlled for in the analysis - Assumption 1 all important confounders are
known and measured - Assumption 2 statistical models, adjustment
procedure assumptions are correct - better to prevent than control
20Random allocation methods
- Fixed allocation
- Simple
- Blocked
- Stratified
- Adaptive procedures
- Baseline adaptive
- Response adaptive
21Masking (blinding)
- To avoid systematic differences between the
treated and control groups during the course of
the study in factors other than the one under
study - controlling for information bias
- Double-blind
- Patient, care provider, and investigator (person
collecting data) all unaware of treatment
assignment - Single-blind
- Patient unaware of treatment assignment
22Administration
- Randomization and treatment assignments should be
administered by an independent unit - Larger trials use computerized log-in and
eligibility verification prior to randomization - Regardless of system used, randomization and
subsequent treatment assignment should be done
when participant ready to begin the intervention
23Strengths
- Potentially the most rigorous design for
evaluating the effect of a single controlled
exposure or intervention - When well executed, less subject to issues of
interpretation than non-experimental studies - More reproducible than non-experimental studies
(theoretically)
24Limitations
- Applicable only to certain types of questions, at
a particular stage of knowledge about the problem - Complex planning
- Usually expensive
- Ethical considerations may limit selection of
participants and generality of results - Rigor of the conduct may fall far short of the
intent
25Main Features of Clinical Trials
- Question
- Design
- Randomized
- Blind
- placebo-controlled
- setting
- Study Population
- time, place person, sample size
- inclusive, exclusive criteria
26Main Features of Clinical Trials
- Intervention (independent variable)
- End point, Outcome (dependent variable)
- definition, measurement
- follow-up protocol (data collection)
- Analysis
- description (comparability, adherence)
- effect on outcome variables
- Conclusions (Interpretation)
27Selection of population
- The population consists of those individuals who
meet the eligibility requirements as to - the presence of the condition
- risk of events for treatment evaluation
- free of contraindications to the treatment
- available (including specified consent
procedures) for the duration intended for
observation - They may be selected in regard to likelihood of
compliance with the intervention. - Once the population is selected, individuals are
randomly allocated into treatment groups
28Selection of population
- Comparison of outcomes between treated and
control groups is the essence of a clinical trial - Historical controls may be used in those rare
instances where the natural history of the
disease has been invariant, e.g., tuberculosis
meningitis - Concurrent controls are required for most
questions - Often the control group is given the "best
available treatment" which is evaluated in
relation to the new treatment under evaluation
29Data collection
- Independent variable (treatment)
- Intervention to be investigated, with placebo or
alternative active treatment - Dependent variable (outcome)
- Events or conditions of importance are those to
be affected by the treatment under investigation,
i.e. the end point(s)
30Data collection
- Hard end-points
- Objective measures can be measured
objectively, blood tests, death, etc - Soft end-points
- Subjective measures reported by the observer or
patient (examples degree of disability, pain,
toxicity, etc.) - Often of greater importance to the patient,
largely neglected by researchers - Self-reporting of adverse events more likely to
reveal adverse effects, especially if rare
31Data collection
- Target population is narrowed down considerably
based on pre-determined criteria to ultimately
establish the study population - Has potential of magnifying problems due to loss
to follow-up, competing risks/outcomes over the
course of the study, unexpected treatment changes - To assess this potential effect, data collected
as to comparability of groups at entry, adherence
to the intervention, and status concerning
outcomes as indicated by the occurrence of end
point events or conditions and possible side
effects/toxicity of the intervention
32Data analysis
- Quality control
- addresses reliability of observations, extent of
missing data, departures from design - Description - provides evidence on
- comparability of groups at entry
- adherence to intervention
- frequencies of recognized side effects/toxicity
- end point rates
- All categorized as at entry or otherwise in
accordance with the design
33Data analysis
- Hypothesis testing
- characterization of study participants,
especially as to comparability of groups at entry - direct measures of incidence of end points or
mortality/survival using life tables or survival
analysis - may involve multivariate analysis to adjust for
differences at entry changing status of
participants over time (time-dependent
covariates) - special analytic methods (sequential analysis) to
determine basis for early termination versus
continuation may be employed
34Interpretation of results
- Conclusions are chiefly centered on the validity
of the comparison of groups over the course of
the trial, - the nature and importance of the differences
observed - the relation of benefit to risk
- the generality of findings to others
35Interpretation of results
- In a clinical trial, observed differences in
outcome between the treated and control groups
can be assigned to one or more of the following
categories - Sampling variation (chance)
- Pre-existing differences in factors affecting
outcome (selection bias and confounding) - Differences in the management and evaluation
during the course of the study (information bias) - True effects of the treatment (truth)
36Hepatitis A Vaccine Trialin Healthy Children
- The first double-blind, placebo-controlled trial
in an American community with recurrent outbreaks
of hepatitis A - The study community (Monroe, NY) was
characterized by rapid growth, large families,
and a high seropositive rate (68) for hepatitis
A antibodies among adults gt19 years of age - Following demonstration of protection with a
single dose, booster doses were administered to a
subset of study participants at 6, 12 or 18
months after the primary dose of VAQTA
Werzberger, A. et al. N. Engl. J. Med.
327(7)453-457, 1992
37Hepatitis A Vaccine Trial
- Study Participants
- 1,037 healthy children, ages 2-16, who were
seronegative for anti-HAV antibodies were
randomized to receive 25 U/O/0.5 mg/L of VAQTA
(n519) or placebo (n518) before the beginning
of a summer-fall outbreak of hepatitis A
38Hepatitis A Vaccine Trial
- Efficacy
- 100 protection against hepatitis A was
demonstrated in 519 susceptible children (ages
2-16) following a primary dose of VAQTA (plt0.001) - Efficacy was based on clinically confirmed cases
of hepatitis A occurring 50 days or more after
vaccination to exclude children incubating the
infection before vaccination - In fact, no cases of clinically confirmed
hepatitis A were observed in the vaccine group
after day 16, while 34 cases were confirmed in
the placebo group
39Efficacy and Safety of Recombinant Human
Activated Protein C for Severe Sepsis
- Early Release (from online journal) Because of
its possible clinical implications, this article
is being released before its publication date.
The final version of the report will be published
on March 8 (posted February 9) - The New England Journal of Medicine
- Volume 344 March 8, 2001 Number 7
- Original Article
- Gordon R. Bernard, Jean-Louis Vincent,
Pierre-Francois Laterre, Steven P. LaRosa,
Jean-Francois Dhainaut, Angel Lopez-Rodriguez,
Jay S. Steingrub, Gary E. Garber, Jeffrey D.
Helterbrand, E. Wesley Ely, Charles J. Fisher,
Jr., for the Recombinant Human Activated Protein
C Worldwide Evaluation in Severe Sepsis (PROWESS)
Study Group
40Efficacy and Safety of Recombinant Human
Activated Protein C for Severe Sepsis
- Research question
- Does activated protein C (drotrecogin-?
activated) reduce the rate of death from all
causes at 28 days in patients with sever sepsis
and have an acceptable safety profile? - Phase III Trial
- Study Design
- A randomized double-blind placebo controlled
multi-center trial - Outcome
- Mortality (any cause) at 28 days post treatment
- Coordinating Center Vanderbilt
41Efficacy and Safety of Recombinant Human
Activated Protein C for Severe Sepsis
- Methods
- Population
- 1,690 patients with systemic inflammation and
organ failure due to acute infection from 7/1998
through 6/2000 - 164 centers in 11 countries
- Randomization
- Stratified-block at each center on a 11 basis
- assigned to receive either drotrecogin-?
activated _at_ 24 ?g per Kg body weight or placebo
42Efficacy and Safety of Recombinant Human
Activated Protein C for Severe Sepsis
- Methods
- Evaluation
- Followed for 28 days or until death
- Blood samples at days 0, 1-7, 14, and 28
- All measurements performed by a central
laboratory - Statistical analysis
- Stratified based on
- APACHE II Score (Acute Physiology and Chronic
Health Evaluation II) 4 strata - Age 2 strata (lt60 vs 60 yrs)
- Plasma protein C level 4 strata
43Efficacy and Safety of Recombinant Human
Activated Protein C for Severe Sepsis
- Methods
- Statistical analysis (continued)
- Designed to enroll 2,280 patients
- Two planned interim analyses _at_ 760 and 1,520
enrollees - Guidelines to suspend trial if treatment was
significantly better than placebo were determined
a priori - Analysis performed by independent DSMB (data
safety monitoring board)
44Efficacy and Safety of Recombinant Human
Activated Protein C for Severe Sepsis
- Results
- Enrollment suspended at second interim analysis
(data from 1,520 patients) - Efficacy
- Statistically significant higher rate of survival
in treatment group compared to placebo group
(plt0.001 at the ?0.05 level, two-sided test) - 19.4 reduction in Relative Risk of death
- Absolute reduction of 6.1
- Safety
- Incidence of bleeding higher in treatment group
(3.5 vs 2.0) although not statistically
significant (p0.06)
45Efficacy and Safety of Recombinant Human
Activated Protein C for Severe Sepsis
46Efficacy and Safety of Recombinant Human
Activated Protein C for Severe Sepsis
TABLE 1 BASE-LINE CHARACTERISTICS (CONTD)
47Efficacy and Safety of Recombinant Human
Activated Protein C for Severe Sepsis
48Efficacy and Safety of Recombinant Human
Activated Protein C for Severe Sepsis
FIGURE 2 KAPLAN-MEIER ESTIMATES OF SURVIVAL
49Efficacy and Safety of Recombinant Human
Activated Protein C for Severe Sepsis
- Conclusion
- Treatment with drotrecogin-? activated
significantly reduces mortality in patients with
severe sepsis - Treatment may be associated with increased risk
of bleeding - In this population, 1 in 16 patients would be
saved
50Additional References
- Text
- Fundamentals of Clinical Trials, 3rd Ed.,
Friedman, Furberg, DeMets - WWW
- http//www.clinicaltrials.gov
- http//www.fda.gov/cder/