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case control study

The content of preventive medicine epidemiological case-control studies summarizes data collection and analysis, advantages and limitations of case-control studies, overview, Design and implementation, etc.

Edited at 2024-01-19 15:43:27

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Outline

Epidemiology
- 231
Avinash Kaur
Epidemiological Study Designs
- 236
- 1
Khalid Taha
Public Health
- 64
CARMEN ANDREA CARIAS ENR�QUEZ
copd
- 31
- 1
College Registrar S8
Epidemiology Chapter 3 Descriptive Research
- 34
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Epidemiology—case-control study
- 39
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Epidemiology—descriptive research
- 39
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Distribution of disease
- 30
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Human Health Ninth Edition Epidemiology Chapter 5 Cohort Study
- 41
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Epidemiology Ninth Edition Chapter 4 Descriptive Research
- 25
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case control study

Overview

concept

Select people with the disease under study from the target population as the case group, and people without the disease as the control group. Investigate and compare whether the two groups have been exposed to certain or certain suspicious factors in the past and the degree of exposure. Compare the two groups. Differences in exposure history, an observational research method that analyzes whether the exposure factor is associated with the disease and the degree of association

Since the exposure ratio between the case group and the control group is often obtained through the review of the research subjects, that is, the "cause" is inferred from the "effect", it is also called a retrospective study.

Basic Features

Observational research method

Is a retrospective study

Research object grouping standards

Analyze metrics based on exposure rates

Design and implementation

Clarify research purpose

The main function of case-control studies is to test etiological hypotheses and screen for etiological factors.

Case-control study classification

Classified by whether there is a hypothesis before research

exploratory case-control study

Identify possible risk factors and formulate hypotheses. such as food poisoning investigation

experimental case-control study

On the basis of descriptive research, after initially forming an etiological hypothesis, this method is then used to test whether this hypothesis is true.

Sort by matching

matched case-control study

Advantages: Can increase statistical testing capabilities during analysis

Disadvantages: complex selection and comparison, troublesome data collection and analysis

unmatched case-control study

Suitable for exploratory case-control studies, easy to implement and obtain more information

Choose research subjects

Case selection

in principle

Diagnosis is reliable

Selected cases must have the potential to be exposed to the factors under investigation

Source of cases: hospital cases, community diseases

Type of case

new cases

Advantages: Recalling exposure history is easier and more reliable

Disadvantages: Longer waiting time to obtain a sufficient number of cases to meet the study sample, and therefore higher costs

Current cases

Refers to survivors of past disease

Deaths

Refers to cases who died before exposure history was collected in the study

Control selection

Principles for choosing comparisons

representative

Comparability

Exposure cannot be used as a basis for selecting controls

source of comparison

Drawn from the source population for selected cases

Hospital comparison

crowd control

Matching of cases and controls

Matching: Also known as matching, when selecting research subjects, the case group and the control group are consistent in certain characteristics or variables.

Overmatching: As matching factors increase, the exposure factors under study gradually converge between the case group and the control group, thus masking or underestimating the association between exposure and disease.

Group matching (group matching, frequency matching)

Requires controls to have the same overall distribution of matching factors as cases

individual matching

Matching of cases and controls on an individual basis

Generally no more than 1:4, 1:1 matching is also called matching

Estimate sample size

Determinants of sample size

1. The estimated exposure rate of the studied factor in the control population (P1); 2. The estimated exposure rate (P2) or odds ratio (OR) of the studied factor in the case group; 3. Hypothesis test significance level (α); 4. Test efficiency or test confidence (1-β)

Data collection content and methods

Collect content

(1) General conditions (2) Disease conditions (3) Exposure history

Collection method

Check existing records

Interview (questionnaire)

Physical examination and laboratory tests

Organizing of data

Proofreading Review File or type into computer

Data compilation and analysis

General steps

Descriptive Statistics

inferential statistical analysis

Comparison of differences in exposure history between case group and control group

Estimate of tie strength

Analysis of the strength of association between exposure and disease (OR value)

Analysis of data from case-control studies in group design

X 2 inspection

Calculation of tie strength

Calculate odds ratio OR

OR =ad/bc

Ratio: refers to the ratio of the probability of something happening to the probability of not happening

Odds ratio (OR): the ratio of the exposure ratio of the case group to the exposure ratio of the control group

The meaning of OR value

OR=1: Indicates that there is no association between exposure and disease;

OR>1: There is a "positive correlation" between exposure factors and diseases. Exposure factors are risk factors for diseases and increase the risk of disease;

OR<1: Exposure factors are "negatively related" to the disease. Exposure factors are protective factors for the disease and reduce the risk of disease.

Estimate of 95% confidence interval for OR

The 95% confidence interval of the OR contains 1, which indicates that the relationship between the exposure factor and the disease is not statistically significant or that the risk of disease caused by exposure is not significantly higher than that without exposure.

Stratified analysis

Role: Control confounding bias

Stratification is to stratify the study sample according to the exposure of one or more confounding factors, analyze the association between exposure and disease within each stratum, and calculate the OR value within each stratum

hierarchical analysis

Significance: Analyze the dose-response relationship between exposure and disease to increase the basis for causal inference

Analysis of paired data

X 2 inspection

OR=c/b

Advantages and limitations of case-control studies

advantage

1. The required research time is short, and manpower, financial and material resources are saved;

2. Suitable for research on rare diseases;

3. Suitable for research on diseases with long incubation periods;

4. The relationship between multiple factors and a disease can be explored simultaneously

limitation

1. The sample is poorly representative and prone to selection bias;

2. The exposure data is inaccurate and prone to recall bias;

3. Not suitable for research on populations with very low exposure rates;

4. It is generally impossible to calculate RR, and one can only use OR to estimate the strength of association, and generally cannot draw conclusions about causality.

Common biases and their control

Types of bias

selection bias

Systematic errors arising from systematic differences in characteristics between study subjects and non-research subjects

Mainly in the research and design stage

Such as: admission rate bias, existing case-new case bias, detected symptom bias, time effect bias, etc.

information bias

It is caused by unclear or inconsistent diagnosis of diseases, leading to grouping errors; due to unclear definition of exposure factors, or inconsistent standards between comparison groups, leading to misclassification of exposures and incorrect grading of exposure levels.

Such as: recall bias, survey bias

confounding bias

Factors that are related to both the exposure and the disease being studied and which, if unevenly distributed between cases and controls, may distort the true relationship between the exposure and the disease

Control of bias

1. Design rationally and use randomization sampling as much as possible; 2. Pay attention to the application of blinding; 3. It is best to have objective indicators for survey variables; 4. When organizing data, pay attention to the balance between the case group and the control group; 5. To control confounding bias, matching design methods can be used in design; 6. Strict quality control