designing a new study:

Designing a New Study:

II. Cross-sectional and Case-control Studies

• A cohort study: the sequence of making the measurements is the same as the chronology of cause and effect.

• Cross-sectional (prevalence) study

º All measurements on a single occasion.

º Determine predictor and and outcome after the data collection

º Estimate prevalence

• Case-control study

º Begin with the outcome, then identify the predictor

º Explore the potential association

CROSS-SECTIONAL STUDIES

Well suited to the goal of describing variables and their distribution patterns

• Structureº Similar to cohort study (except that measurements are

made at once)

º Can examine associations based on the investigator’s hypothesis, not based on the study design.

• e.g., age, race---usually predictors blood lead level and hyperactivity ---->misleading (historic information on the time course)

Cross-sectional Study

Risk factor; Disease

Risk factor;No disease

No risk factor;Disease

No risk factor;No Disease

Population

SampleSteps:1. Select a sampling from the population2. Measure predictor and outcome variables

CROSS-SECTIONAL STUDIES

• Designingº Settle on the research question

º Specify criteria for the target and accessible populations

º Establish the design for drawing the sample

º Decide the phenomena to study

º Define the approach to measuring appropriate variables.

Example 8.1: Sexually transmitted disease and the use of oral contraceptives

Statistics for expressing disease frequency in observational studies

Type of Study Statistics Definition

Cross-sectional Prevalence

Cohort Incidence

# of people who have the disease at one point in time

# of people at risk at that point

# of new cases of disease over a period of time

# of people at risk during that period

* Relative prevalence = Relative risk prevalence/incidence bias

Cross-sectional Studies• strength

º Relatively fast and inexpensive

º No waiting time to see the outcome

º No loss to follow-up

º Provide the prevalence of a disease or a risk factor

º Convenient for examining networks of causal links

• alcohol intake and HDL-cholesterol

º First step for investigations

• weaknessº Difficult to establish causal

relationship

º Impractical for the study of rare diseases or risk factors from a general population

• e.g., 1 in 10,000 in a general population for a stomach cancer in 45-59 year old men

º Susceptible to prevalence/incidence bias

• e.g., Kids with HLA-A2 were at increased risk factor for the incidence of leukemia ???[truth was that HLA-A2 kids live longer]

Cross-sectional Studies

• Case series =~ cross sectional studies for relatively rare diseasesº the sample from a diseased population not from a general population

º suitable to describe the characteristics of the disease than to analyzing differences between these patients and healthy people

e.g., Of the first 1000 patients with AIDS, for example, 727 were homosexualor bisexual males and 236 were I.V. drug abusers. Furthermore, within a sample of patients with a disease there may be association of interest, the higherrisk of Kaposi sarcoma among AIDS patients who are homosexual than amongAIDS patients who are I.V. drug abusers.

Cross-sectional Studies

• Serial Surveysº To draw inferences about changing patterns over time.

• e.g., census data

º Not a cohort study (i.e., following a single group of people)

Case-Control Studies

• Structureº the prevalence of the risk factor in subjects with the

disease (cases) can be compared with the prevalence in subjects without the disease (controls).

º Retrospective

º “house red”more modest and a little riskier than the other selections, but much less expensive and sometimes surprisingly good!

Case-control design

THE PAST OR PRESENT THE PRESENT

Risk factorpresent

Riskfactorabsent

Risk factorpresent

Risk factorabsent

Disease

No disease

Sample of cases

Sampleof controls

Much larger population without disease (controls)

Populationwith disease(cases)


• Steps:1. Select a sample from a population of people with the

disease (cases)

2. Select a sample from a population at risk that is free of the disease (controls)

3. Measure predictor variables

Designing a case-control study

• Settle on the research question• Specify criteria for the target and accessible

populations (the cases and the controls)• Establish the design for drawing the sample• Decide the phenomena to study• Define the variables and measurement approaches,

and establishes the hypotheses to be tested.


• Settle on the research question

“Whether there is an association between use of aspirin and the development of Reye’s syndrome”


• Specify criteria for the target and accessible populations (the cases and the controls)

º The cases: Children with a viral infection followed by Reye’s syndrome

º The controls: Children with a viral infection but no Reye’s syndrome


• Establish the design for drawing the sample(cases)

“all 30 patients with Reye’s syndrome who are accessible to him for study”

• Establish the design for drawing the sample(controls)

“60 patients drawn from the much larger population of accessible patients who have had minor viral illnesses without Reye’s syndrome”


• Decide the phenomena to study• Define the variables and measurement approaches,

and establishes the hypotheses to be tested.“ask the subjects in both groups about their use of aspirin.”

“approximate relative risk can be computed”


• Cannot yield estimates of the incidence or prevalence of a disease, because the proportion of study subjects who have the disease is determined by how many cases and how many controls the investigator chooses to sample, rather than by their proportions in the population.

• Can yield some descriptive information on the characteristics of the cases and an estimate of the strength of the association between each predictor variable and the presence or absence of the disease (odds ratio).

Odds ratio and relative risk

• Odds ratio in a cross sectional studies

ad/cb

Risk factor presentRisk factor absent

Disease No disease

a bc d

ad/cd =a/b

c/d

[a/(a + b) c/(c + d)]..

= a ( c + d)c (a + b)


• Strengthsº Efficiency for rare

outcomes• high yield of information

from relatively few subjects

º Usefulness for generating hypotheses

• Weaknessesº no incidence

º no prevalence

º no attributable or excess risk

º Sampling bias, and how to control it

• randomization is near impossible (pts with a diagnosed)

• misdiagnosed or misdiagnosed are omitted


• Weaknessesº selection of cases ---

relatively straightforward

º selection of controls---??

º Sampling the cases and controls in the same way

º Matching

º Using two or more control groups

º Using a population-based sample

º Differential measurement bias, and how to control it

• Use of data recorded before the outcome occurred

• Blinding

designing a new study:

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