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Case Control Studies

Dr Naveen Phuyal

MBBS(KU),MD(MUHS)

Introduction

• Imagine you are a clinician

• You have seen few patients with certain type of cancer

• Almost all of them have been exposed to a particular chemical

• You hypothesize that their exposure is related to their risk of developing this type of cancer

• How will you go about confirming or refuting your hypothesis?

Example 1

• In the early 1940s, Alton Ochsner, a surgeon in New Orleans, observed that virtually all of the patients on whom he was operating for lung cancer gave a history of cigarette smoking

• Although this relationship is accepted and well recognized today, it was relatively new and controversial at the time that Ochsner made his observation.

• He hypothesized that cigarette smoking was linked to lung cancer.

• Based only on his observations in cases of lung cancer, was this conclusion valid?

Example 2

• Again in the 1940s, Sir Norman Gregg, an Australian ophthalmologist, observed a number of infants and young children in his ophthalmology practice who presented with an unusual form of cataract.

• Gregg noted that these children had been in utero during the time of a rubella (German measles) outbreak. He suggested that there was an association between prenatal rubella exposure and the development of the unusual cataracts.

• Keep in mind that at that time there was no knowledge that a virus could be teratogenic.

• Thus, he proposed his hypothesis solely on the basis of observational data, the equivalent of data from ambulatory or bedside practice today.

Classification of research methods

Research methods

Observational

Descriptive

Case series, case reports,

CS, cohort

Analytical

Ecological Cross-sectional

Case control Cohort

Experimental

ControlledUncontrolled,

Non-random

Position in the evidence hierarchy

6

Dogma of case control study

Assemble cases –diseased

Time

Direction of enquiry

Assemble controls –not having disease

Measure exposure status

Exposed and non-exposed

7

Design of a case-control study

Hallmark of Case Control Study: from cases and controls and searches for exposure.

Definition

• A case control study is defined as an epidemiological approach in which the researcher starts by picking up ‘cases’ who have already developed particular disease or ‘outcome’ of interest and a comparison group (controls) who have not developed the disease but are similar to cases.

• Than he/she tries to find out the presence of particular exposure which he/she thinks is a risk factor and compares the two groups in regards to presence of history of exposure.

• Case : A person in the population or study group identified as having the particular disease, health disorder or condition under investigation. (Dictionary of Epidemiology: 3rd ed; John M Last. 2000)

• Control: Person or persons in a comparison group that differs, in disease experience (or other health related outcome) in not having the outcome being studied. (Dictionary of Epidemiology: 3rd

ed; John M Last. 2000)

Features of case controls study

• Both exposure and outcome has happenedbefore the start of the study.

• The study proceeds backwards from effect tocause.

• It uses a comparison group to support orrefute an inference.

Design of case control study

Steps

• Selection of cases and controls

• Matching

• Measurement of exposure

• Analysis and interpretation

1.Selection of cases and controls

Selection of cases

• Definition of case

– Diagnostic criteria

• Single hospital

• Network of hospitals

– Eligibility criteria

• Incident cases

• Prevalent cases

• Sources of cases

Hospitals

General population

Selection of controls

• Controls must be free from disease under study

• Must be similar to the cases except for the disease under study

• Selection of controls is the most difficult

• Sources of controls– Hospitals

– Relatives

– Neighborhood

– General population

Source Advantage Disadvantage

Hospital based Easily identified.Available for interview.More willing to cooperate.Tend to give complete and accurate information (recall bias).

Not typical of general population.Possess more risk factors for disease.Some diseases may share risk factors with disease under study. (whom to exclude???)Berkesonian bias

Population based(registry cases)

Most representative of the general population.Generally healthy.

Time, money, energy.Opportunity of exposure may not be same as that of cases. (locn, occu,)

Neighbourhood controls/ Telephone exchange random dialing

Controls and cases similar in residence.Easier than sampling the population.

Non cooperation.Security issues.Not representative of general population.

Best friend control/ Sibling control

Accessible, Cooperative.Similar to cases in most aspects.

Overmatching.

How many controls are needed?

• 1:1 for larger studies

• 1:2

• 1:3

• 1:4

• Multiple control

• Failure to select appropriate control group results in bias.

• Multiple controls of different types are valuable for exploring alternate hypothesis & for taking into account possible potential recall bias.

• (From Gold EB, Gordis L, Tonascia J, Szklo M; Risk factors for brain tumors in children. Am J Epidemiol 1979)

Children with brain tumours

Children with other cancers

Children without cancer

Radiation causes cancers

Radiation causes brain cancers only

2.Matching

Matching

• Matching is a process in which we select controls in such a way that they are similar to cases with regard to certain pertinent variables (eg. age) which are known to influence the outcome of disease and which if not adequately matched for comparability could distort or confound the results.

What is a confounding factor?

Esophageal cancerAlcohol

Smoking

Matching types

• Group matching (Frequency matching)

• Pair matching ( Individual matching)

3.Measurement of exposure

Measurement of exposure

• Interviews

• Questionnaires

• Past records

– Hospital records

– Employment records

4. Analysis

Analysis

• Find out

– Exposure rates among cases and controls to suspected factor

– Estimation of disease risk associated with exposure ( Odds Ratio)

Exposure rates

Cases(with Ca Lung)

Controls ( without Ca lung)

Total

Smokers ( <5/day)

33(a)

55(b)

88(a+b)

Non-smokers 2(c)

27(d)

29(c+d)

Total 35(a+c)

82(b+d)

117(a+b+c+d)

A case control study between smoking and lung cancer

Exposure rates

• Cases= a/(a=+c)= 33/35= 94.2 %

• Controls= b/(b+d)= 55/82= 67 %

• So frequency of smoking was definitely higher among lung cancer patients than those without cancer

• Odds Ratio / Relative odds

– Odds: Odds of an event is defined as the ratio of the number of ways an event can occur to the number of ways an event cannot occur. (Epidemiology; Leon Gordis. 2004)

• If the probability of event X occurring is P, then odds of it occurring is = P/ 1-P.

– Odds ratio: Ratio of the odds that the cases were exposed to the odds that the controls were exposed.

• Odds ratio:

Odds that case was exposed

Odds ratio =Odds that control was exposed

= (a/c)/ (b/d) = ad / bc

Outcomes of Case Control Study

Diseased/ Cases Not diseased/ Controls

Exposed a b

Not exposed c d

Estimation of risk

• Odds Ratio (Cross-product ratio)

• Odds that cases were exposed= a/c

• Odds that controls were exposed=

b/d

• Odds ratio= (a/c)/(b/d)= ad/bc= 8.1

Interpretation

• The odds of smoking more than 5 cigarettes per day was 8.1 times more in the lung cancer patient than those without lung cancer.

OR

• Smoking (>5/day) was found be associated 8.1 times more in patients with lung cancer than those without lung cancer.

Bias in case control studies

• Bias due to confounding

• Selection bias

• Survivorship bias

• Healthy worker effect

• Memory or recall bias

• Berkesonian bias

• Interviewers bias

Bias due to confounding

Esophageal cancerAlcohol

Smoking



• Selection bias






Selection bias

• Selection of inappropriate control group

• Basic dictum is controls should be derived from the same source population from which the cases have come and that the controls should be equally at risk.

None use of condoms(exp) and development of STD(outcome)

• Cases: STD clinic

• Controls: same clinic who did not have STD

• But many of the controls may not have developed STD because their partner may not have STD weather they use condom or not.

• What was the right way to select cases and controls?

Cases: Has STD and partners also have STDControls: Does not have STD but partner has STD



• Selection bias






Survivorship bias

• A case control study taken to evaluate protective effect of physical exercise on MI

• Case: Patients with MI

• Control : Healthy

• Exposure : Exercise

• But Both cases and control gave a Hx of physical exercise

• Conclusion: Exercise does not protect MI

In reality 25% to 30% of the MI cases die in first 3 hrs and do not survive.

So only those who survived are available as cases.Maybe exercise prevents acute manifestations of MIOut of MI those who exercised survived but those who did not may have died so we have a biased conclusion.



• Selection bias






Healthy worker effect



• Selection bias






Memory/ Recall Bias

• The person who is diseased is more likely to remember about the exposure than the non –diseased.

• X-ray exposure and congenital malformation

• Unprotected sexual intercourse and HIV



• Selection bias






Berkesonian bias

• Hospital selective admissions

• Eg. Cigarette smoking causes peptic ulcer????

• Eg. High fever and febrile seizures.



• Selection bias






Advantage of case-control study

• Easy to carry out

• Rapid and inexpensive

• Rare disease investigation

• No risk to subjects

• Allows study of several etiological factors

• Rational prevention and control measures

• No attrition

• Minimal ethical problems

Disadvantages

• Bias

• Control selection is difficult

• Incidence cannot be measured

• Cannot differentiate between causes and associated factors

• Not suitable for evaluation of Rx.

• Representiveness of cases and controls

Examples of case control studies

• Adenocarcinoma of vagina

• Oral contraceptives and thromboembolic disease

• Thalidomide tragedy

Adenocarcinoma of vagina in young women

• 7 young women (15-22 yrs) born in Boston hospital

• 7 cases (time clustering) in 4 years at same hospital led to case control investigation

• As the disease was rare , 4 matched controls for each case

• Controls: taken from birth records, same hospital as cases

Adenocarcinoma of vagina in young women

• Information collected by personnel interview on:

1. Maternal age

2. Maternal smoking

3. Antenatal radiology

4. DES (diethyl-stilbestrol) exposure in foetal life

7 cases were exposed to DES in foetal life Their mother were given this drug to prevent miscarriage in pregnancyWhile none of the mothers in control group were given this drug.

Thalidomide tragedy

• Thalidomide was used as a safe hypnotic in 1960s• 1961: Birth of babies with congenital

malformation in UK, prev rare• Case control study of 46 mothers who delivered

deformed babies showed that 41 were found to have thalidomide in their ealry pregnancy.

• This was compared to 300 mothers who delivered normal babies bit their was no thalidomide exposure.

• Later laboratory experiments confirmed that thalidomide was teratogenic.

THANK YOU

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