Spring 2008

Case-Control Studiesand Odds RatioSTAT 6395Filardo and Ng

Types of Epidemiologic studies

Case-Control studiesA study in which a group of persons with a disease (cases) and a comparison group of persons without the disease (controls) are compared with respect to the history of past exposures to factors of interest

Case-Control studiesA study in which a group of persons with a disease (cases) and a comparison group of persons without the disease (controls) are compared with respect to the history of past exposures to factors of interestPresentPastTimeType of studies Observational Case-Control

Case-Control studies (study schema)Type of studies Observational Case-Control

Cohort studiesA study in which a group of persons exposed to a factor of interest and a group of persons not exposed are followedType of studies Observational Cohort studies

and compared with respect to the incidence rate of the disease or other condition of interestTime

Comparison is fundamental in determining the relationship between an exposure and a diseaseCohort studyIncidence rate in exposed group is not enough (Needs nonexposed comparison group)

Case-control studyPast exposures of a group of cases is not enough (Needs a control group for comparison)

Fundamental difference between a case-control study and a cohort studyA case-control study starts with people: a) with; and b) without the disease of interest and compares their past exposures

A cohort study starts with people: a) with; and b) without the exposure of interest and compares their future disease

The fundamental difference between a case-control study and a cohort study is not the calendar time period during which exposures took placefor example, in a both a retrospective cohort study and a case-control study, the calendar time period during which exposures took place is in the past

How do we measure past exposures in a case-control study?Interview

Medical records/charts

Assays of biological specimens (e.g. nested case-control studies)

Goal is to measure exposures that occurred before the onset of disease

Selection of cases: incident vs. prevalentIncident (newly diagnosed) casesRisk factors might contribute to the development of the disease

Prevalent (existing) casesCannot distinguish between risk factors for the development of the disease and risk factors for cure or survivalMore difficult to know which came first, the exposure or the diseaseExposure measurements problematic

Prevalence = Number of a given disease at a particular time point or during a particular time period (this is a proportion and not a rate)

Selection of casesDefinition of source population -- the population that gives rise to the cases

Case definition -- need to have definite medical criteria for who is a case of the disease

Case identification -- need to put a system in place for finding all cases who meet the case definition and are members of the source population Source Population Cases and Controls

Selection of appropriate controls is the major methodological challenge in case-control studies

In a case-control study, we want to determine whether exposures of interest differ between the case group and the source population

Controls should be selected from the source population that gave rise to the cases. Selection of controlsSource Population Cases and Controls

The controls should be representative of the source population with respect to the exposures of interest.

Ideally, controls should be a random sample of the source population.

Selection of controls (continued)Prevalent cases of the disease should not be eligible to be controls

Study I: Controls selected such that they have a higher level of exposure than the source population, producing an an artifactual result that the exposure is negatively associated with the disease

Study II: Controls selected such that they have a lower level of exposure than the source population, producing an artifactual result that the exposure is positively associated with the disease

Study III: Controls selected such that they have the same level of exposure as the source population, producing the unbiased (true) result that the exposure is not associated with the disease

Case-control studies classified by type of source population (population that gives rise to the cases)Population-based case-control studies

Hospital (or clinic)-based case-control studies

Nested case-control studiesCase-Control studies Population-based, hospital-based, nested

Population-based case-control studiesSource population: all residents of a defined geographic area who do not have Disease X

Cases: all new cases of Disease X that occur among residents of a defined geographic area over a specified period of time

Controls: sample (ideally random) of the source population over the same period of timeCase-Control studies Population-based, hospital-based, nested

Population-based: Parkinsons diseaseSource population: residents of Texas who do not have Parkinsons disease

Cases: all new cases of Parkinsons disease among Texas residents identified over a 3 year period through a rapid-reporting system

Controls: sample (ideally random) of residents of Texas who do not develop Parkinsons disease over the same 3 year periodCase-Control studies Population-based, hospital-based, nested

Selection of controls in population-based case-control studiesRandom sample from a population registry

Neighborhood controls -- sample of persons who reside in the same neighborhoods as the casesOften done by matchingCase-Control studies Population-based, hospital-based, nested

Selection of controls in population-based case-control studies (continued)Random selection of telephone numbers (random digit dialing)

members of the source population does not have the same probability of being contacted (not a random sample): Case-Control studies Population-based, hospital-based, nestedpersons without a landline have zero probability of being selected households vary the amount of time someone is home and number of telephonesmany people screen their telephone calls

Hospital-based case-control studiesSource population: all people without Disease X who would attend Hospital A if they had Disease X

Cases: all new cases of Disease X identified in Hospital A over a specified period of time

Controls (most commonly): sample of patients in Hospital A with diagnoses other than Disease X over the same period of time Case-Control studies Population-based, hospital-based, nested

Hospital-based: Parkinsons diseaseSource population: all persons who would attend Baylor University Medical Center (BUMC) if they had Parkinsons diseaseNote that this source population is, in practice, impossible to identify

Cases: all new cases of Parkinsons disease seen at BUMC over a 3 year period

Controls: sample of patients at BUMC with diagnoses other than Parkinsons disease over the same 3 year periodCase-Control studies Population-based, hospital-based, nested

Source population: all persons who would attend the hospital if they developed the disease of interest

Selection of controls in hospital-based case-control studiesSource population in a hospital-based case-control study is usually not identifiable

A random sample of the general population will not necessarily correspond to a random sample of the source population because it does not take into account the referral patterns of the hospital

Furthermore, referral pattern depends on the diseaseCase-Control studies Population-based, hospital-based, nested

Hospital-based controls are patients without the disease from the same hospital

Selection of controls in hospital-based case-control studies (continued)Hospital-based controls are a nonrandom sample of the source population, most of whom are healthy

Nonrandom sampling of the source population introduces the possibility that the distribution of the exposure of interest among the controls is not the same as it is in the source populationCase-Control studies Population-based, hospital-based, nested

Hospital-based controls may not reflect the exposure distribution in the source populationExposures of interest may cause or prevent the diseases for which patients in the control group were hospitalizedCase-Control studies Population-based, hospital-based, nested

Hospital-based controls may not reflect the exposure distribution in the source populationPersons with an exposure of interest may be more or less likely than persons without the exposure to be hospitalized for their disease if they develop it (this could also be an issue for cases)Case-Control studies Population-based, hospital-based, nested

Hospital-based controls unrepresentative of the exposure distribution in the source population: Parkinsons diseaseControls: random sample of persons hospitalized for other diseases, many of whom were hospitalized for heart disease

Low folic acid intake is a risk factor for heart disease

This control group would have a lower proportion of persons with high folic acid intake than the source populationCase-Control studies Population-based, hospital-based, nested

Controls selected such that they have a lower level of exposure than the source population, producing an artifactual result that the exposure is positively associated with the diseaseCase-Control studies Population-based, hospital-based, nested

Selection of controls in hospital-based case-control studies (continued)Limit the controls to those hospitalized for diseases for which there is no suspicion of a relationship with the exposures of interestCase-Control studies Population-based, hospital-based, nested

Selection of controls in hospital-based case-control studies (continued)Include a variety of diseases in the control group, so as to dilute the biasing effects of including a disease that might related to the exposure, unbeknownst to the investigator

Case-Control studies Population-based, hospital-based, nested

Selection of controls in hospital-based case-control studies (continued)Excluded diseases should only apply to the diagnosis at the current hospitalizationCase-Control studies Population-based, hospital-based, nested

Excluded diseases should only apply to the diagnosis at the current hospitalization: Parkinsons diseaseControls: persons hospitalized due to traumatic injury, who are believed to be representative of the source population with respect to folic acid intake

Persons with a history heart disease should not be excluded from this traumatic injury control group. This would cause the control group to have an over-representation of persons with high folic acid intakeCase-Control studies Population-based, hospital-based, nested

Controls selected such that they have a higher level of exposure than the source population, producing an an artifactual result that the exposure is negatively associated with the diseaseCase-Control studies Population-based, hospital-based, nested

Nested case-control studies (nested within a concurrent cohort study)Source population: the subjects in an ongoing concurrent cohort study who did not have Disease X at baseline

Cases: all new cases of Disease X that occurred in the cohort over a defined period of follow-up

Controls: random sample of subjects in the cohort who did not develop Disease X over the defined period of follow-upCase-Control studies Population-based, hospital-based, nested

Nested case-control studies (nested within a concurrent cohort study)Exposures measured by assay of stored biologic specimens collected from the subjects at baselineNested case-control study has advantage of cohort studies: exposure measured at baseline before development of disease

Nested case-control studies (nested within a concurrent cohort study)Collection of additional exposure information not collected at baseline requires labor-intensive data collection activities, such as abstraction from recordsNested case-control study has advantage of cohort studies: exposure measured at baseline before development of disease

Nested case-control studies (nested within a concurrent cohort study)biologic specimens collected from the subjects at baseline

cases and controls identified

specimens used to assess exposure and compare it among study groupsTimeCase-Control studies Population-based, hospital-based, nested

Nested case-control: Parkinsons disease

Source population: the members of the Nurses Health Study cohort who donated blood samples in 1989-1990 and had no history of Parkinsons disease

Cases: all new cases of Parkinsons disease that developed in this source population from 1991 to 2000

Controls: random sample of the Nurses Health Study cohort who did not develop Parkinsons disease from 1991 to 2000

Measurement of exposure: serum folic acid level at baselineCase-Control studies Population-based, hospital-based, nested

Advantages of the nested case-control studies over the concurrent cohort study itselfCost: suppose there were 32,000 women in the source population, 200 cases, and 200 controls.

Causality: the exposure occurred before the disease

Further research: preservation of precious biologic specimens remaining specimens available for other studiesCase-Control studies Population-based, hospital-based, nested

Accounting for confounders in selecting controlsMatching -- selection of controls such that they are similar to cases with respect to factors other than the exposures of interest

MatchingCommon matching factors: age, sex, race, socioeconomic status

Accounting for confounders Matching

MatchingFrequency matching: selection of controls such that the distributions of the matching factors (e.g., age, sex) are similar in the case and control groups

Accounting for confounders Matching

MatchingIndividual matching: each control is individually matched to a case with respect to specific factors, resulting in matched case-control pairs

For example, for each case, select a control of the same race, sex, age (within 3 years), neighborhood (within 3 blocks)Accounting for confounders Matching

Matching is intuitively appealing, but its implications are complicated In a case-control study, the association between matching factors and disease cannot be studied

Accounting for confounders Matching

Matching is intuitively appealing, but its implications are complicated Overmatching can occur if a matching factor is associated with the exposure of interest, thus making the controls artifactually like the cases with respect to that exposure

Accounting for confounders Matching

Matching is intuitively appealing, but its implications are complicated Matching must be taken into account in the analysis through special analytic techniques

We will cover some of these techniques in this course Accounting for confounders Matching

Conventional data layout for case-control study (2x2 table)

First select

Cases

Controls

Total

Then

Measure Past

Exposure

Exposed

a

b

m1

Not Exposed

c

d

m2

Total

n1

n2

N

Estimating relative risk in a case-control studyIn a case-control study, we cannot measure incidence rates in the exposed and nonexposed groups, and therefore cannot calculate the relative risk directly

In a case-control study, the odds ratio is a good approximation of the relative risk in some circumstances

OddsProbability that cases were exposed = a/(a+c)

Probability that cases were not exposed = c/(a+c)

Odds of a case having been exposed = [a/(a+c)]/[c/(a+c)] = a/c

Similarly, odds of a control having been exposed = b/d

Odds Ratio (OR)The ratio of the odds that the cases were exposed to the odds that the controls were exposed = (a/c)/(b/d) = ad/bc

The odds ratio is the cross-product ratio in the 2x2 table

Interpretation of the Odds RatioThe odds ratio is a good approximation of the relative risk when the disease being studied occurs infrequently (which is the situation in most circumstances case-control studies are conducted)

ONLY in this case the interpretation of the odds ratio in case-control studies is the same as the interpretation of the relative risk in cohort studies

Interpretation of the Odds RatioOR = 1 Risk in exposed = risk in nonexposedNo association

OR > 1Risk in exposed > risk in nonexposedPositive associationThe larger the OR, the stronger the associationMay or may not be causal

Interpretation of the Odds Ratio OR < 1Risk in exposed < risk in nonexposedNegative associationThe smaller the OR, the larger the negative associationMay or may not be causalIf causal, indicates a protective effect

Interpretation of the Odds Ratio: ExampleOR = (59 X 44) / (33 X 17) = 4.63

Patients that eat of served or less are 4.63 times more likely to be dependent feeding than patients that eat more than of served food

Interpretation of the Odds RatioA further example of the calculation and interpretation of the odds ratio is given by Bland & Altman (Bland J.M. & Altman D.G. (2000) The odds ratio. British Medical Journal 320, 1468.)

Interpretation of the Odds RatioThe odds ratio may be a misleading approximation to relative risk if the event rate is high (Deeks (1996) and Davies et al. (1998))

Interpretation of the Odds RatioSince the odds ratio is difficult to interpret, why is it so widely used?

Odds ratios can be calculated for case-control studies whilst relative risks are not available for such studies.

Attributable risk percent (exposed) using odds ratio [(OR - 1)/OR] x 100

Tells us what percent of the disease among the exposed is due to the exposure

Attributable risk percent (population) using odds ratio

_P x (OR-1) _ x 100 P x (OR-1) + 1

where P is the population prevalence of the exposure

P can be estimated by the prevalence of the exposure in the controls

Tells us what percent of the disease in the total population is due to the exposure