Lecture 8: interventional studies Flashcards
how are interventional studies divided up (in increasing evidence)
phase 0 through phase 4
what are the differentiators within each phase?
- purpose/focus
- population studied (healthy/diseased)
- sample size
- duration
pre-clinical
prior to human investigations– bench or animal research
phase 0
exploratory; investigational new drug– FIRST human contact
- assess drug-target actions and possibly pharmacokinetics in single or ‘a few’ doses
- healthy (or diseased in oncology) volunteers
- small population (less than 20)
- short duration (single dose to few days)
phase 1
investigational new drug
- assess safety/tolerance (first in human)
- healthy OR diseased
- small pop (20-80)
- short –> few days to few weeks
phase 2
investigational new drug
- assess effectiveness, continues to assess safety/tolerability
- diseased
- 100-300
- short to medium duration–> few weeks to few months
phase 3
investigational new drug–> LAST PHASE before FDA approval
- assess effectiveness
- diseased (expanded inclusion criteria & placebo comparison)
- 500-3000
- few months to a year
* *few rounds of this needed
phase 4
post FDA approval
- assess long-term safety, effectiveness, and optimal use
- diseased volunteers
- whole population used
- wide-range of durations (few weeks to several years)
* **registries and surveys used to track long-term
advantages of interventional trials
cause precedes effect–> can demonstrate CAUSATION
only designs used by FDA approval process
disadvantages of interventional trials
cost
complexity/time
ethical considerations
generalizability (external validity)
exploratory study
answers research question –> EXPLORES research for dosages, etc.
useful? helpful? best dose?
explainatory (pragmatic) study
real clinical life
clinicians making decisions: dosages changes, drug switches, etc.
hard to compare at the end
interventional study designs (pick one of each)
- simple OR factorial
2. parallel OR cross-over
simple interventional study
only ONE randomization step to divide subjects into groups
tests SINGLE hypothesis at a time
factorial interventional study
randomizes subjects into groups TWO OR MORE times
can ask more than one question at a time
ex: drug 1 alone OR drug 1 + 2 combined better??
parallel interventional study
groups are simulataneously and exclusively managed; once they’re randomized into groups they STAY there = no cross-over occuring
cross-over interventional study
groups serve as their own control by crossing over from one intervention to another during the study
- -allows for smaller study size because you can get double the data from a single person (they try both drugs)
- -DOWNFALL: lasts longer because they’re followed for BOTH drugs and they have washout phase; only suitable for long-term conditions that are not curable; complex data analysis
what two phases occur before/during a cross-over interventional study
lead in phase
wash out phase
lead in phase
“practice run” with placebo to flush out previously used drugs AND test compliance, adherence, etc.
can determine new baseline
wash out phase
period of time where NO drugs are given in order to clear system before next drug is given
outcomes/endpoints of interventional studies
primary = most important
secondary, tertiary, etc. = lesser importance, but still valuable
composite = combines multiple endpoints into single outcome
patient-oreinted endpoints (POEM’s)
death, stroke, myocardial infarction, hospitalization, preventing need for dialysis
disease-oreinted endpoints (DOE’s)
blood pressure (for stroke risk) cholesterol (for heart attack risk) change in SCr (for worsening renal function)
purpose of randomization
to make groups as equal as possible, based on known and unknown important factors (confounders); attempts to reduce bias between groups
–equality is NOT guarenteed & documentation of equality of groups must be reported
types of randomization
simple
blocked
stratified
simple randomization
equal probability for allocation within one of the study groups (just normal randomization)
blocked randomization
ensures balance within each intervention group; used when researchers want to make sure they’re equal SIZE
–block “checks” can influence where people are put in groups to ensure same numbers in each
stratified
ensures balance with known confounding variables
ex: gender, age, disease, comorbidities, etc.
types of masking in interventional studies
single-blind
double-blind
open-label
placebo (dummy) therapy
single-blind study
study subjects not informed which group they’re in
investigators do know
double-blind study
neither investigators nor study subjects are informed which intervention group subjects are in
open-label
both study subjects and researchers know what intervention is being received
placebo (dummy) therapy
inert treatments made to look identical in all aspects to the active treatments; dosage form, dosing frequency, monitoring, etc.
double dummy therapy
more than one placebo used
placebo effect
improvement in condition by power of suggestion of being “treated” (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
not accepted as appropriate, by most, when NOT prospectively planned
–“data-dredging” or “fishing”
IS accepted when planned ahead
ways to manage drop-outs/lost-to-follow-ups
- include them anyway: intent to treat
- ignore them
- treat them “as treated”
intent to treat
- *most conservative decision
- -last known observation is carried forward for all subsequent assessments (LOCF)
- -convert all subsequent yet missed to assessments to a null-effect (no benefit)
result of intent-to-treat
preserved randomization process
preserves baseline characteristics and group balance at baseline, which controls for known and unknown confounders
maintains statistical power
ignoring drop-outs
including only compliant or completing subjects
- -per protocol or efficacy-analysis
- compliance must be pre-defined
treating drop outs “as treated”
ignores group assignments
allows subjects to switch groups and be evaluated in group they moved to, end in, or stayed in most
impact of drop out decisions
per-protocal results in biases estimates of effect (commonly over-estimates)
-reduces generalizability
how to assess adherence (compliance)
drug levels
pill counts at each visit
bottle counter-tops
how to improve adherence (compliance)
frequent follow-up visits/communications
treatment alarms/notifications
medication blister packs or dosage containers
