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Less Commonly Used Observational Study Designs

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Title: Observational Study Design Author: Fredrick Schumacher Last modified by: John Witte Created Date: 1/7/2002 3:52:40 PM Document presentation format – PowerPoint PPT presentation

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Title: Less Commonly Used Observational Study Designs


1
Less Commonly Used Observational Study Designs
  • John S. Witte
  • jwitte_at_ucsf.edu
  • 1/20/2012

2
Overview
  • Points from last week
  • Cross-sectional study designs
  • Standard, case / control
  • Repeated survey, survey follow-up, intervention
    follow-up
  • Proportionate mortality
  • Case-only design
  • Case-crossover
  • Case-specular
  • Genetic epidemiology
  • Hardy-Weinberg Disequilibrium
  • Transmission / disequilibrium
  • Gene x Environment Interaction
  • Family members
  • Ecologic Studies

3
Highlights From Last Week
  • Cohort Studies
  • Closed vs. Open Cohorts
  • Classifying Person-Time
  • Case-control Studies
  • Selection of cases and controls
  • Measures of association
  • Control sampling schemes
  • Sources of controls
  • Controls should be selected
  • from the same population the source population
    that gave rise to the cases.
  • independently of exposure, within strata of
    factors that will be used for stratification in
    the analysis.

4
Recall Rare Disease Assumption
  • When is this required for case control study?
  • Consider sampling methods what measure of
    effect being estimated.
  • Case-cohort (risk ratio, rate ratio)
  • Density sampling (rate ratio)
  • Cumulative case-control (incidence OR, risk ratio)

5
Case-Cohort Sampling
X
X
X
X
X
Time
6
Case-Cohort, Option 1 Simple Random Sample _at_
Start, Exposure _at_ Baseline
X
X
X
X
X
Time
7
Case-Cohort, Option 2 Follow Sub-cohort,
Estimate Person-Time Distribution
X
X
X
X
X
Time
8
Case-Cohort, Option 3 Form Risk Sets by Matching
on Time
Time
9
Two-Stage Sampling
Cases
Complete Exposure Info
Partial Covariate Info
10
2. Cross-Sectional Study
11
Cross-Sectional Studies
  • Subjects all in population at the time of
    ascertainment or a representative sample.
  • Often exposures that can not change
  • E.g., blood type or other invariable personal
    characteristics.
  • Cross-sectional analyses of baseline information
    in cohort studies provides possible
    exposure-disease associations that can later be
    confirmed.
  • Cases in a cross-sectional study will over
    represent cases with a long duration of illness
    and under represent those with a short duration
    of illness.

12
Case or Control Cross-Sectional Studies
  • Use cases only to determine estimates of disease
    prevalence etc. among different groups (e.g.,
    defined by geographical region).
  • Use controls to estimate exposure prevalence in
    population.

13
Cross-Sectional Study Strengths

14
Cross-Sectional Study Weaknesses
15
Repeated Survey
X
X
X
X
X
X
X
Time
16
Repeated Survey
  • Combines two or more cross-sectional studies of
    the same source population at different times.
    Although we might say that the population is
    followed in this type of study, individuals are
    not followed.
  • Design is not much better than the simple
    cross-sectional study for testing etiologic
    hypotheses.
  • Study population trends or to evaluate the
    effectiveness of population interventions
    initiated between surveys.
  • Assess the extent to which change in disease rate
    can be explained by changes in specific exposures.

Hal Morgenstern
17
Survey Follow-up
  • Combines a cross-sectional study followed by a
    cohort study of those individuals who are still
    at risk of developing the disease.
  • This design is used when
  • Want to estimate both the prevalence and
    incidence rates of a disease in the same source
    population
  • It is hard to distinguish between prevalent and
    incident cases.
  • To make baseline assessments to identify persons
    still at risk of developing the disease (e.g, as
    a necessary first phase of a cohort study)

Hal Morgenstern
18
Intervention Follow-up
  • Combines an intervention with a cohort study,
    each part having a different followup period and
    outcome variable.
  • The first followup period is short and is used to
    assess the effect of an intervention / exposure
    on an outcome (not primary disease).
  • The second followup period is generally longer
    and is used to observe disease occurrence.
  • This design is useful for examining relationships
    between acute biological/behavioral responses and
    chronic health effects.

Hal Morgenstern
19
Proportionate Study
  • Proportional morbidity or mortality study
    involves data on cases or deaths.
  • Special type of case-control (or cross-sectional)
    study.
  • A group of individuals with (or dying from) the
    index disease of interest is compared with a
    group of individuals with (or dying from) certain
    other diseases.

Hal Morgenstern
20
Example Proportional mortality study
  • Occupational exposure to low-level ionizing
    radiation on cancer.
  • All certified deaths among employees of the
    Hanford nuclear power facility between 1944 and
    1972 were classified by cause of death and
    exposure status (based on company records of
    radiation monitoring).
  • Proportion of deaths that were exposed to
    ionizing radiation (i.e., at least one positive
    badge reading) among male employees, by cause of
    death (n3520). Cancers of the reticuloendothelial
    system (RES) include lymphomas, myelomas, and
    leukemias.

Mancuso et al. Health Physics 1977
33369-385. Hal Morgenstern
21
3. Case-Only Studies
  • Use theoretical considerations to construct a
    distribution of exposure in the source
    population.
  • Use this distribution in place of an observed
    control series.
  • Case-crossover studies
  • Case-specular Studies
  • Genetic epidemiology
  • Hardy-Weinberg Disequilibrium
  • Gene x Environment Interaction

22
Case Crossover Study
X
X
X
X
X
X
X
X
X
X
23
Case-Crossover Studies
  • One or more time periods are selected as matched
    control periods for the case.
  • Compare exposure status at the time of disease
    onset to the control exposure status within the
    same individual.
  • Depends on the assumption that neither exposure
    nor confounders are changing over time in a
    systematic way.
  • i.e. cyclic manner
  • Exposure must vary over time within individuals
  • Exposure must have a short duration and a
    transient effect

24
Example Physical Exertion MI
  • A number of different exposure periods can be
    measured.
  • One might also use a bidirectional approach to
    measuring exposures.

Tager, 2000
25
Limitations of Case-Crossover Studies
26
Case-Specular Design
  • Use some physical properties to distinguish
    controls environmental exposures.
  • E.g., In a study of electromagnetic field
    exposure and disease, measure cases homes
    distance to electrical wires. Then flip block
    and measure distance from specular home to
    electrical wires for controls distance.

27
Genetic Epidemiology Case-Only Studies
  • The laws of inheritance may be combined with
    certain assumptions to derive a population of
    genotypes.
  • Hardy-Weinberg Principle Genotypes will reflect
    allele frequency distributions in the general
    population.
  • That is, both allele and genotype frequencies in
    a population remain constantthey are in
    equilibriumfrom generation to generation unless
    specific disturbing influences are introduced.
  • Can look for disequilibrium among cases only.

28
Case-Parents Transmission Disequilibrium Test
(TDT)
  • Transmitted alleles vs. non-transmitted alleles

M1 M2
M2 M2
M1 M2
29
TDT
  • Transmitted alleles vs. non-transmitted alleles

Non-Transmitted Allele Non-Transmitted Allele Non-Transmitted Allele
Transmitted M1 M2
Transmitted M1 n11 n12
Transmitted M2 n21 n22
TDT (n12 - n21)2 (n12 n21)
Asymptotically c2 with 1 degree of freedom
30
TDT
  • For this one Trio

Non-Transmitted Allele Non-Transmitted Allele Non-Transmitted Allele
Transmitted M1 M2
Transmitted M1 0 1
Transmitted M2 0 1
TDT (1 - 0)2 (1 0)
1
p-value 0.32
31
Case-Only for Interactions
E E-
G G- G G-
Case A11 A10 A01 A00
Control B11 B10 B01 B00
32
Family-Based Association Studies
Siblings
Parents
G
G
G
G
G
G
Cousins
G
G
33
Comparison of Designs
  • Family-based designs can be less efficient than
    population-based designs.

Rare Recessive
Common
Rare Dominant
High Risk
Low Risk
High Risk
Population-based
100
100
100
Case-sibling
69
51
50
Case-cousin
97
88
88
TDT
231
102
101
Witte et al. Am J Epidemiol 1999
  • Further, family-based designs can require more
    recruitment efforts.

34
Population Stratification
  • Confounding bias that may occur if ones sample
    is comprised of sub-populations with different
  • allele frequencies (?) and
  • disease rates (RpR)
  • Cases are more likely than controls to arise from
    the sub-population with the higher baseline
    disease rate.
  • Cases and controls will have different allele
    frequencies regardless of whether the locus is
    causal.

35
Genomic Control
  • Use population-based design, but incorporate into
    analysis genomic information to adjust for
    population stratification.
  • Genomic control adjust test statistics for
    outliers due to population stratification.
  • Use unlinked genetic markers.

36
Principal CompoenentsGenetic Matching of
Controls
Luca et al. AJHG 2008
37
Continuum of Genetic Epi Study Designs
Population-based
Ethnicity Matched
Genomic-based
Family-based
Population Stratification
Overmatching
(Biasversus...efficiency)
  • ? Sharing of genes envt.
  • Efficiency
  • Also, recruitment issues

38
4. Ecologic Studies
  • Levels of Measurement
  • Aggregate measures summaries (e.g. means,
    proportions) of observations derived from
    individuals in each group.
  • Environmental measures physical characteristics
    of the place in which members of each group live
    or work (e.g. air pollution level, hours of
    sunlight).
  • Global measures attributes of groups,
    organizations, or places for which there is no
    distinct analogue at the individual level (e.g.
    population density, level of social
    disorganization, existence of a specific law, or
    type of health-care system).

39
Ecologic Studies
  • Levels of Analysis
  • - The common level for which data on all
    variables are reduced and analyzed.
  • a. Complete ecologic analysis
    Total

Disease Exposure Exposure Exposure Exposure
Disease -
Disease ? ? T1
Disease - ? ?
Disease T0 T
40
Ecologic Studies
  • Levels of Analysis
  • - The common level for which data on all
    variables are reduced and analyzed.
  • a. Complete ecologic analysis
  • b. Partially ecologic analysis
    Z1 Z0 Total

Disease Exposure Exposure Exposure Exposure
Disease -
Disease ? ? M11
Disease - ? ? M01
Disease N11 N01 T1
Exposure Exposure Exposure Exposure
-
? ? M11
- ? ? M01
N10 N00 T0
Exposure Exposure Exposure Exposure
-
? ? T1
- ? ? T0
T1 T0 T
41
Ecologic Studies
  • Levels of Inference
  • -Want to make ecologic inferences about effects
    on group rates (an ecologic effect).
  • e.g., Helmet-use laws
  • - May want to estimate the contextual effect of
    an ecologic exposure on individual risk.
  • Commonly found in infectious disease
    epidemiology

42
Ecologic Study Designs
  • Multiple-group Design
  • -The rate of disease is compared among many
    groups during one period of time to search for
    spatial patterns.
  • Example NCI cancer study
  • - The rate of disease may be compared between
    migrants and their offspring and residents of
    the countries of immigration and emigration.
  • -Environmental or behavioral risk factors
  • -Genetic risk factors
  • Examples Migrant Study and Multiple-group
    Analytic Study

43
Example Standardized Mortality Ratios
Japanese
Cancer Site Japan Not US Born US Born US Caucasians
Stomach (M) 100 72 38 17
Colorectal (F) 100 218 209 483
Breast 100 166 136 591
MacMahon B, Pugh TF. Epidemiology. 1970178.
44
Ecologic Study Designs
  • Time-trend Design
  • One group or population is followed over time to
    assess a possible association between a change in
    exposure frequency and a change in disease
    frequency.
  • Example NCI study of artificial sweetener
    consumption and bladder cancer between
    1950-1969.
  • Mixed Design
  • A mixture of the two previous designs. A number
    of groups or populations are followed over time
    to assess a possible association between a change
    in exposure frequency and a change in disease
    frequency.
  • Example Change in annual CVD mortality rate for
    males between 1948 and 1964 in 83 British towns
    by age and water level hardness.

45
Ecologic Studies Strengths?
46
Ecologic Studies Weaknesses?
47
Criteria for Comparing Study Designs
  • There are three general criteria for evaluating
    and comparing different study designs.
  • 1. Relevance of the information to the
    investigator
  • Extent to which expected findings will satisfy
    the specific objectives of the study
  • Investigator's desire to estimate specific
    population parameters
  • 2. Quality or accuracy of the information
    expected in the data
  • Ability of the investigator to determine that the
    exposure preceded disease occurrence
  • Ability of the investigator to eliminate the
    possibility that the statistical findings were
    due to various methodological problems or sources
    of error
  • 3. Cost of the information
  • The ultimate worth of a study is the total value
    of all derived information--now and in the
    future--relative to the total (direct and
    indirect) costs of the study
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