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Classifying Human Studies into Design Types Using Factors
December 19, 2011
CTSA Human Studies Database Projecthttp://hsdbwiki.org/
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Study Design Typology Goal• Identify most parsimonious set of unambiguous
factors that when collected, will correctly classify any study on individual humans into a set of common study design types
• collection can be via manual review, or automated extraction from Clinical Trial Management Systems (e.g., Velos) or electronic IRB systems (e.g., ClickCommerce)
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What the Classification Yields
• The high-level study types (in red) represent distinct approaches to human investigations that are each subject to a distinct set of biases and interpretive pitfalls (e.g.,selection bias, generalizability, etc.)• Additional Descriptors elaborate on secondary design and
analytic features that introduce or mitigate additional biases and interpretive pitfalls
• some Additional Descriptors apply only to some study design types
• The classification also groups studies for • discussing design considerations for how T0 research fits with
T1-3 research (e.g., subject selection for tissue specimens)• Particular types of administrative overview/IRB approval needed
(e.g., interventional, retrospective, etc.)
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A study (see slide 8 for definition)
Is the study an original study, or a meta study (a study of other studies*)?
Original
No
Non-organismal Studies(organization studies, policy analyses,
device tests, etc)
Non-human Organism Study(rat, mouse, etc.)
Is the organism human?
Meta
Human Study
Is the human data at the individual level?
Yes No (data is aggregated)
No
Systematic Review (of summary-level data: human, non-human,
policy, etc.)
Ecologic Study(see next slide)
Are any of the entities that are enrolled, exposed, or observed in the study any of the following: an organism, some part of an organism, or a collection of organisms?
Yes
•in original studies, observations are acquired directly on or from the study participants (including individual participant-level data from databases, and participant-level meta-analysis) •in meta studies, observations are acquired from journal articles, abstracts, etc. reporting on other studies
Yes
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Interviews, focus groups, ethnographic studies, etc.
Qualitative Studies
Does the study use primarily quantitative or qualitative methods?
qualitative quantitative
Does the investigator assign one or more interventions?
Individual-human study
Yes No
see next slides
Yes No
Does the investigator have a choice of interventions to assign participants to?
Single Group
Does investigator assign interventions to and analyze data only within a single study
participant?
Crossover
Yes No
N-of-1 Crossover
Interventional Studies
Is the main comparison across or within participants?
Within Across
Parallel Group
What is the main variable on which participant selection is based?
An outcome variable A predictor variable
Themselves A variable that is neither an outcome
nor a predictor
Cross-sectional Cohort
Are participants with the main outcome being compared to:
Other participants
Case Control
Observational Studies
Case Crossover
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Yes No
Does the investigator have a choice of interventions to assign participants to?
Single Group
Does investigator assign interventions to and analyze data only within a single study
participant?
Crossover
Yes No
N-of-1 Crossover
Interventional Studies
Is the main comparison across or within participants?
Within Across
Parallel Group
Interventional study
Additional Descriptors N-of-1 Crossover Parallel Group Single Group, etc.
Comparative intent (superiority, non-inferiority, equivalence)
√ √ √ N/A
Sequence generation (random, non-random) √ √ √ N/A
Allocation concealment method (a to e) √ √ √ N/A
Assignment to study intervention (non-factorial, factorial)
√ √ √ N/A
Unit of allocation (individual, cluster) N/A √ √ N/A
Blinding/Masking (yes/no of each of:participant, investigator)
√ √ √ N/A
Study phase (0, 0/1, 1,1/2, 2, 2/3, 3, 4) √ √ √ √
Pooled data (yes, no) N/A √ √ √
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What is the main variable on which participant selection is based?
An outcome variable[retrospective inference:
outcome → exposure]
A predictor variable[prospective inference: exposure → outcome]
Themselves
Case Crossover Cross-sectional Cohort
Are participants with the main outcome being compared to:
Other participants
Case Control
Observational study
Additional Descriptors Case Crossover Case Control Cross-sectional Cohort
Have outcomes occurred before the study start? (yes [historical], no [prospective])
N/A N/A N/A √
Are cases and controls (or exposed andunexposed) drawn from the same studycohort/sample? (yes = nested, no = non-nested [akadouble cohort for cohort studies])
N/A √ √ √
Matching (subsamples matched on covariates ornot)
N/A √ √ √
Sampling method (probability, non-probability) √ √ √ √
Pooled data (yes, no) √ √ √ √
Is the comparison group selected or identifiedbased on genetic relation? (yes, no)
N/A √ √ √
A variable that is neither an outcome nor a predictor
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What is a [unitary] StudyA study has two orthogonal components: a sample - i.e., a specific set of participants (i.e.,
recruited/selected entities) drawn from a population or collection
an inferential approach - i.e., how observations are collected with respect to interventions/exposures and/or how inference is drawn [e.g., a historical cohort and a prospective cohort may have identical inferences but observations are collected differently]
A study is a unitary study if and only if it has a single defined intended or actual sample and a single defined inferential approach
A study is a hybrid study if it has more than one intended or actual sample and/or more than one inferential approach
The study design typology should be applied to each unitary study (i.e., each unitary study is one pass through the study design typology)
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The Six Entities that Characterize a Study
1. Entity that is recruited/selected• e.g., humans, clinics, randomized trials, states, mice
2. Entity that is randomized [if applicable]• e.g., humans, rats, eyes
3. Entity that is subject to intervention(s)/exposure(s)
• e.g., humans, hospitals, schools, monkeys
4. Entity that is observed, i.e., on which observations are made
• e.g., humans, policies/strategies, organizations, randomized trials
5. Finest-grain entity that is/was available for analysis
• e.g., individual patient data, clinic-level averages, population mean, summary-level patient results from randomized trials
6. Entity about which conclusions are made e.g., humans, rats, policies (e.g., costs of), populations