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Epidemiology > Interventional Study Designs > Flashcards

Interventional Study Designs Flashcards

1
Q

Interventional study design

A

experimental; clinical trial; clinical study; experimental study; human study; investigational study

investigator selects interventions

researcher-forced group allocation

Buzz word: randomization

can demonstrate causation

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2
Q

phase 0

A
  • 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
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3
Q

phase 1

A
  • 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
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4
Q

phase 2`

A
  • assess effectiveness of drug
  • diseased population (may have narrow inclusion criteria)
  • larger sample size (few hundreds)
  • short to medium duration (weeks to months)
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5
Q

phase 3

A
  • 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

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6
Q

phase 4

A
  • 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
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7
Q

advantages of interventional studies

A

can demonstrate causation (cause precedes effect)*

key designs used by FDA for “approval” process*

environment can be highly controlled

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8
Q

disadvantages of interventional studies

A

costly
complexity
ethical considerations (risk vs benefit)
external validity*

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9
Q

pragmatic interventional studies

A

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

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10
Q

simple interventional study

A

divides (randomizes) subjects exclusively into 2 or more groups

single randomization process

used to test a single hypothesis

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11
Q

factorial interventional study

A

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

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12
Q

parallel interventional study

A

no switching of interventional groups after initial randomization

simple and factorial studies can be parallel

groups simultaneously and exclusively managed

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13
Q

cross-over (self-control) interventional study

A

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

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14
Q

hangover effect

A

effects of tx 1 carrying over to tx 2

need wash-out period between crossing over events

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15
Q

lead-in/run-in phase

A

beginning of study, set patients to baseline; all participants blindly given one or more placebos for initial therapy to determine new baseline

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16
Q

wash-out phase

A

reset to baseline during study, between group switches

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17
Q

disadvantages of cross-over studies

A

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

18
Q

patient-oriented Endpoints (POEM’s)

A
  • most clinically relevant
  • patient language
  • e.g. death, stroke, hospitalization, etc.
19
Q

disease-oriented endpoints (DOE’s)

A
  • more number based
  • surrogate markers
  • e.g. BP, cholesterol
20
Q

group allocation

  • non-random
  • random
A

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
21
Q

randomization

A

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

22
Q

simple randomization

A

equal probability for allocation within one of the study groups

23
Q

blocked randomization

A
  • 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

24
Q

stratified randomization

A

ensure balance with known confounding variables

e.g. gender, age, disease severity, comorbidities

25
Q

masking: single-blind

A

study subjects not informed which intervention (treatment) group they are in, but investigators know

26
Q

masking: double-blind

A

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

27
Q

masking: open-label (unmasked/unblinded)

A

study subjects and researchers know what intervention is being received

28
Q

masking: placebo

A

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

29
Q

placebo-effect

A

improvement in condition by power of suggestion of being “treated” (improvement can be as large as 30-50%)

30
Q

hawthorne-effect

A

study subjects change their behavior solely due to awareness of being studied/observed

31
Q

post-hoc sub-group analysis

A

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

32
Q

sample size determination

A

add in anticipated drop-out or loss to follow-up rates

33
Q

intent(ion) to treat: way to manage drop-outs/lost-to-follow-ups

A

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)

34
Q

benefits of intention to treat data analysis

A
  • 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)
35
Q

per-protocol/efficacy-analysis: way to manage drop-outs/lost-to-follow-ups

A
  • 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
36
Q

as-treated: way to manage drop-outs/lost-to-follow-ups

A
  • ignores group assignments

- allows subjects to switch groups and be evaluated in group they moved to, end in, or stay in most

37
Q

assessing adherence (compliance)

A
  • drug levels (multiple useful sites)
  • pill counts at each visit
  • bottle counter-tops
38
Q

methods of improving adherence (compliance)

A
  • frequent follow-up visits/communications
  • treatment alarms/notifications
  • medication blister packs or dosage containers
39
Q

systematic reviews

A

summary report about previous individual studies

used in both interventional and observational studies

40
Q

meta-analyses

A

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

Epidemiology (9 decks)

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