Interventional Study Designs Flashcards
Interventional study design
experimental; clinical trial; clinical study; experimental study; human study; investigational study
investigator selects interventions
researcher-forced group allocation
Buzz word: randomization
can demonstrate causation
phase 0
- assess drug-target actions and/or pharmacokinetics in single or few doses
- first human use
- healthy or diseased population
- very small sample size (<20)
- very short duration (single dose to just a few days)
- drugs don’t have official name yet
phase 1
- assess safety/tolerance and pharmacokinetics
- first human use or early human use
- healthy or diseased population
- small sample size (20-80)
- short duration (days to weeks)
- studies can start here if permitted
phase 2`
- assess effectiveness of drug
- diseased population (may have narrow inclusion criteria)
- larger sample size (few hundreds)
- short to medium duration (weeks to months)
phase 3
- assess effectiveness
- diseased population (expanded inclusion criteria)
- uses various statistical-perspectives to determine
- larger population (hundred to thousand)
- longer duration (months to year)
- final step before seeking approval from FDA
*can be repeat study of phase 2 but longer with more people
phase 4
- post FDA approval
- assess long-term safety and effectiveness
- diseased population (expand inclusion criteria including comorbidities and other meds)
- larger population (hundreds to tens of thousands)
- variable durations
advantages of interventional studies
can demonstrate causation (cause precedes effect)*
key designs used by FDA for “approval” process*
environment can be highly controlled
disadvantages of interventional studies
costly
complexity
ethical considerations (risk vs benefit)
external validity*
pragmatic interventional studies
have flexibility to treat patients like they would in regular clinic; flexibility described in methods section
more practical/pragmatic application of real life patient management
e. g. change dosage based on side effects
goal: not effectiveness of drug, but determining what is the most effective pattern of treatment management of the disease with drug
simple interventional study
divides (randomizes) subjects exclusively into 2 or more groups
single randomization process
used to test a single hypothesis
factorial interventional study
divides (randomizes) subjects into 2 or more groups and then further sub-divides (randomizes) each of the group into 2 or more additional sub-groups
used to test multiple hypotheses*
improves efficiency for answering clinical questions*; increases sample size and complexity; may restrict generalizability
parallel interventional study
no switching of interventional groups after initial randomization
simple and factorial studies can be parallel
groups simultaneously and exclusively managed
cross-over (self-control) interventional study
groups serve as their own control by crossing over from one intervention group to another during study
allows for smaller total sample size because each patient contributes additional data
hangover effect
effects of tx 1 carrying over to tx 2
need wash-out period between crossing over events
lead-in/run-in phase
beginning of study, set patients to baseline; all participants blindly given one or more placebos for initial therapy to determine new baseline
wash-out phase
reset to baseline during study, between group switches
disadvantages of cross-over studies
only suitable for long-term disease conditions which are not curable or which treatment provided short-term relief
duration of study for each subject is longer (due to switching groups and wash-out periods)
treatment-by-period interaction*: differences in effects of treatments during different time periods (disease state gets worse because of natural progression of disease as length of study increases)
complexity in data analysis
patient-oriented Endpoints (POEM’s)
- most clinically relevant
- patient language
- e.g. death, stroke, hospitalization, etc.
disease-oriented endpoints (DOE’s)
- more number based
- surrogate markers
- e.g. BP, cholesterol
group allocation
- non-random
- random
non-random:
- subjects don’t have an equal probability of being selected or assigned to each intervention group (e.g. convenience sampling/non-probabilistic allocation; quasi-systematic)
- e.g. patients attending morning clinic assigned to group 1 and patients attending afternoon clinic assigned to group 2
random:
- subjects have equal probability of being assigned to each intervention group
- e.g. random-number generating programs
randomization
Purpose: to make groups as equal as possible; based on known and unknown important factors (confounders)
-equality of groups not guaranteed, but number in groups can be guaranteed
simple randomization
equal probability for allocation within one of the study groups
blocked randomization
- ensure balance within each intervention group
- when researchers want to assure that all groups are equal in size
e.g. still probabilistic but blocked off so every nth patient, groups are examined to see if randomization has been equal
stratified randomization
ensure balance with known confounding variables
e.g. gender, age, disease severity, comorbidities
masking: single-blind
study subjects not informed which intervention (treatment) group they are in, but investigators know
masking: double-blind
investigators and study subjects are not informed which intervention (treatment) group subjects are in
post-study survey’s can be used to assess adequacy of blinding
masking: open-label (unmasked/unblinded)
study subjects and researchers know what intervention is being received
masking: placebo
inactive treatments made to look identical in all aspects to the active treatments
dosage form, dosing frequency, monitoring, etc is all identical
also double-dummy studies exist: more than 1 placebo used
placebo-effect
improvement in condition by power of suggestion of being “treated” (improvement can be as large as 30-50%)
hawthorne-effect
study subjects change their behavior solely due to awareness of being studied/observed
post-hoc sub-group analysis
data analysis after study has completed
not accepted as appropriate when NOT prospectively planned because can be viewed as “data-dredging” or “fishing” for acceptable data which reduces power of study and increases risk of type II error
is accepted if performed for hypothesis generation and development of future studies
sample size determination
add in anticipated drop-out or loss to follow-up rates
intent(ion) to treat: way to manage drop-outs/lost-to-follow-ups
include subject’s data in analysis anyway; using data like the subject had intended to finish the study (most conservative decision because the last assessment is being used as final assessment)
benefits of intention to treat data analysis
- maintain group allocation (preserves randomization process) (sample size in groups are maintained)
- preserves baseline characteristics and group balance at baseline which controls for known and unknown confounders
- maintains statistical power (original sample size)
per-protocol/efficacy-analysis: way to manage drop-outs/lost-to-follow-ups
- ignoring those who drop-out; include only those who were compliant and completed the study
- compliance must be pre-defined (customarily set at 80-90% compliance)
- can reduce generalizability
as-treated: way to manage drop-outs/lost-to-follow-ups
- ignores group assignments
- allows subjects to switch groups and be evaluated in group they moved to, end in, or stay in most
assessing adherence (compliance)
- drug levels (multiple useful sites)
- pill counts at each visit
- bottle counter-tops
methods of improving adherence (compliance)
- frequent follow-up visits/communications
- treatment alarms/notifications
- medication blister packs or dosage containers
systematic reviews
summary report about previous individual studies
used in both interventional and observational studies
meta-analyses
taking individual data from past studies and combining them into a new jumbo study population and rerunning new stats to obtain new data
used in both interventional and observation studies
