Some Information on Case Control, Cohort and Survival Studies

By

RAMNATH TAKIAR

Ex-scientist G

National Cancer Registry Programme

(National Centre for Disease Informatics and Research, Bangalore)

Bangalore

NOVEMBER 2014

A cohort study is a form of longitudinal or a type of

observational study used in medicine, social sciences

and ecology.

A cohort is a group of people who share a common

characteristic or an experience within a defined

period (e.g., are born, are exposed to a drug or a

vaccine, etc.). Thus a group of people who were born

in a particular year (period), say 1948 (1945-50),

form a birth cohort.

Cohort studies

In a Cohort study usually the population selected isfree from certain disease or health condition. Thepopulation so selected is followed up for a specifiedperiod of time and information is obtained todetermine which subjects either have a particularcharacteristics (e.g., blood group A) that is suspectedof being related to the development of the diseaseunder investigation or have been exposed to apossible etiological agent (e.g., cigarette smoking,alcohol drinking). The entire study population is thenfollowed up in time and the incidence of the disease inthe exposed individuals is compared with theincidence in those not exposed.

Healthy Population

Exposed (P1) Non-Exposed (P2)

Diseased Non-diseased Diseased Non-diseased

(N1-P1) (N2) (N2-P2)(N1)

R1 = (N1/P1) R2 = (N2/P2)

IF R1> R2 => Exposure increases the disease risk IF R1< R2 => Exposure decreases the disease risk

IF R1= R2 == > Exposure does not increase the risk of occurrence of disease

Cohort Study :

OutcomeExposure

Yes No

Yes a b

No c d

Total a+c b+d

Risk in exposed group (P1) = a/(a+c)

Risk in Unexposed group (P2) = b/(b+d)

Risk ratio = P1/P2 ;

Risk Difference = P1-P2

Outcome (Cancer)

Exposure (Smoking)Total Yes

(Ever)No (Never)

Yes 392 323 715

No 16953 13114 30067

Total 17345 13437 30782

Risk in exposed group (P1) = 0.023 = 2.3%

Risk in Unexposed group (P2) = 0.0240 = 2.4%

Risk ratio = 0.023/0.0240 = 0.946 ; NS

Risk Difference = 0.023 – 0.024 = - 0.001 = - 0.1%Source: Karunagappally Cohort study (1990-97) –published in Health Physics society 2009

Study population: 359619; 10 year duration

Outcome(Lung

Cancer)

Exposure (Smoking)Total

Ever Never

Yes 12 14 26

No 11560 19031 30591

Total 11572 19045 30617

Risk in exposed group (P1) = 0.010 = 1.0% (103)*

Risk in Unexposed group (P2) = 0.007 = 0.7% (73)*

Risk ratio = 0.010/0.007 = 1.41; NS

Risk Difference = 0.01 – 0.007 = - 0.003 = - 0.3%Source: Karunagappally Cohort study (1990-97) –published in Int J Cancer 2008

Study population: 359619; 8 year duration (1997-2004)

* Represents Crude Rate

If study subjects have unequal follow-up periods ,

this must be taken into account in the analysis.

Follow-up durations may differ markedly if subjects

were recruited into the study population over a

relatively long period of time, or if some are lost to

follow-up during the course of the study. One way

of handling variable follow-up periods is to

calculate rates which use person years at risk as the

denominator.

9

Calculation of Person years for Incidence rate

SUBJECT 2001 2002 2003 2004 2005 2006 2007 Time at risk

A 2

B + 4

C + 4

D 5

E 5

Total years at risk 20

Incidence = 2 person for 20 person years

= 10 /100 person years of observation

Hypothetical group of 5 persons with certain risk factor were followed up for 7 years, two of whom developed the disease of interest.

Here, we are dealing with the time for which the population is exposed.

10

.

Person years:

It is the cumulative sum of time periods for which the

population is exposed to the risk of developing certain disease

condition during the specified period of time.

In above example, you can notice two things:

1. Registration of cases is not in same year.

2. Follow up period differ from one subject to another.

3. Loss to follow-up exist in the study.

OutcomeExposure

Yes No

Cases a bPerson-time at

risk x y

Rate in exposed group (r1) = a/x

Rate in unexposed group (r2) = b/y

Rate ratio = r1/r2;

Rate difference = r1-r2

Oral contraceptive use

Ever Never Total

Cases 204 240 444

Person years at risk 94029 128528 222257

Rate per 100000 pyrs 217 187 199

Rate Ratio = Relative Risk = 217/187 =1.16

95% confidence for the rate ratio = 0.96-1.40

Rate difference = 217-187 = 30 per 100,000 years

Example: Incidence of Breast cancer amongnurses aged 45-49 years at the time of their entryinto the cohort was examined in relation to use oforal contraceptives.

Source: IARC 1999: Cancer Epidemiology : Principles and Methods ; Page 179

The Nurses' Health Study, established in 1976 by Dr. FrankSpeizer, and the Nurses' Health Study II, established in1989 by Dr. Walter Willett, are the most definitive long-term epidemiological studies conducted to date onwomen's health. The US study has followed 121,700female registered nurses since 1976 initially aged 30 to 55and 116,000 female nurses since 1989 registered to assessrisk factors for cancer and cardiovascular disease. Thestudies are among the largest investigations into riskfactors for major chronic diseases in women everconducted.Over the time additional questions have been added, mostnotably the dietary assessment added in 1980. Deaths,usually reported by kin or by postal authorities, werefollowed up.

In a cohort study carried out among 78140 womenaged 30-84 years in Karunagappally, Kerala, anattempt was made to examine the relationshipbetween chewing habits and development of oralcancers.

Baseline information collected was related tolifestyle including tobacco chewing and socio-economic factors during the period 1990-97.

By the end of 2005, 92 oral cancers wereidentified.

Total person years covered were 921051 years.

Tobacco Chewing and Oral Cancer among women

Outcome Chewing habit

Current Former Never

Oral Cancer 53 14 25

Persons years at risk 183749 26804 706872

Incidence per 100000

28.8 52.2 3.5

Relative Risk 8.2 14.8 1

95% CI 5.1-13.1 7.7-28.4

Source: PA Jayalekshmi, P Gangadharan, S Akiba et al. : Tobacco Chewing and Female Oral Cavity cancer risk in Karunagappally cohort, India; British J of Cancer (2009) –Table 3.

Calculation of Confidence Limit for Relative Risk

RR ln(RR)SE of ln(RR) FORMULA

SE

8.2 2.09869 [(1/25)+(1/53)]^0.5 0.243

LL UL

For ln(RR) 2.09- (1.96*0.243) =

1.622.09+(1.96*0.243) =

2.57

anti log 5.07 13.12

Major steps followed in a Cohort Study:

1. Definition of the objectives

2. Choice of the study population

3. Choice of the comparison group

4. Measurement of exposure (s)

5. Measurement of outcome(s)

6. Follow-up of the subjects

7. Follow up periods

8. Analysis

Definition of the objective: It is essential that a clear

hypothesis is formulated before the start of a

cohort study. This should include a clear definition

of exposure(s) and outcome(s) of interest.

1. Choice of the study population: The choice of the

study population mainly depends on the specific

hypothesis under investigation. The cohort chosen

may be a general population group such as the

residents of a community or more narrowly defined

population that can be readily identified and

followed up.

3. Choice of the comparison group: The selection of

the unexposed is the most critical aspect in the design

of a cohort study . The unexposed group should be as

similar as possible to the exposed group with respect

to the distribution of all factors that may be related to

the outcome(s) of interest except the exposure under

investigation.

Two main type of comparison group may be used in a

cohort study: internal and external.

General population cohorts tend to be heterogeneous

with respect to many exposures and hence their

members can be classified into different exposure

categories.

In such circumstances, an internal comparison group

can be utilized. That is, the experience of those

members of the cohort who are either unexposed or

exposed to low levels can be used as the comparison

group.

4. Measurment of Exposure: Measurement of the

exposure(s) of interest is a critical aspect in the design

of a cohort study. Information should be obtained on

age at first exposure, dates at which exposure started

and stopped, dose and pattern of exposure and

changes over time.

Information on the exposure(s) of interest may be

obtained from a number of sources like

i) Information provided by subjects through personal

interviews or questionnaire;

ii) Data obtained by medical examination or other

testing of the participants.

iii) Biological specimens: or

iv) Direct measurements of the environment in which

cohort members have lived or worked.

5. Measurement of outcome(s):

A major advantage of cohort studies is that it is

possible to examine the effect of a particular exposure

on multiple outcomes (Malnutrition Vs. Ht, Wt, Menarche) or

effect of multiple exposures on single outcome (Age,

parity, sexual partners and their effect on occurrence of Cervix cancer ).

Many cohort studies make use of existing routine,

surveillance systems to ascertain the outcomes of

interest. Such system include cancer registries and

death certification.

Case-control studies:Case Control studies are particularly suitable for the

study of relatively rare diseases with long induction

period, such as cancer. This is because a case-control

study starts with subjects who have already

developed the condition of interest, so that there is

no need to wait for time to elapse between exposure

and the occurrence of disease.

In an unmatched study, the numbers of cases

and controls found to have been exposed and not

exposed to the factor under investigation can be

arranged in 2x2 table as shown in the following table.

Subjects Exposed Unexposed TotalCases a b a+b

Controls c d c+d

Total a+c b+d N

Odds of exposure in the cases = a/b

Odds of exposure in the controls = c/d

Odds ratio = Odds of exposure in the

cases/Odds of exposure in the controls

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

It is not possible to estimate the disease incidence in exposed and unexposed group. However, it is possible to calculate the odds of exposure in the cases and in the controls.

Study Population

Cases (N1) Controls (N2)

Exposed Non-exposed Exposed

(N1-P1) (P2) (N2-P2)(P1)

Odds in Cases = O1 = P1/(N1-P1) Odds in Controls =O2 = P2/(N2-P2)

IF O1> O2 => Exposure increases the disease prevalence IF O1< O2 => Exposure decreases the disease prevalence

IF O1= O2 == > Exposure does not increase the risk of occurrence of disease

Case-control study:

Non-Exposed

Selection

A population based case-control study was carriedout in Spain and Colombia to assess therelationship between cervical cancer andexposure to human papilloma virus (HPV),selected aspects of sexual and reproductivebehaviour, use of oral contraceptives screeningpractices , smoking, and possible interactionsbetween them. The study included 436 incidentcases of histoligically confirmed invasivesquamous–cell carcinoma of the cervix and 387controls of similar age randomly selected from thegeneral population that generated the cases(Munoz et al., 1992)

In a cervical cancer control study conducted inColombia and Spain, the risk of developingcervical cancer was examined in relation to thelifetime number of sexual partners. (Based onPooled data of Colombia and Spain)

Outcome Number of Sexual partners

0-1 2-5 6+

Cervical cancer cases (a) 265 125 46

Controls (b) 305 74 8

Odds (a/b)

0.87 1.69 5.75

Odds ratio* 1 1.94** 6.62**

95% CI - 1.39 - 2.70 3.07 - 14.28

* Keeping 0 - 1 category as reference** Significantly different from reference categorySource: IARC 1999: Cancer Epidemiology: Principles and Methods: Page 207

Calculation of OR by classical method

Outcome Number of Sexual partners

2-5 0-1

Cervical cancer cases 125 (a) 265 (b)

Controls 74 (c) 305 (d)

Odds in Cervical cancer cases = a/b = 125/265

Odds in Controls = c/d = 74/305

OR = a/b/c/d = ad/bc = 125*305/(74*265) = 1.944

Calculation of 95% Confidence Interval:

The formula for calculation of SE for OR is given by

Sqrt (1/a + 1/b + 1/c + 1/d)

sqrt { (1/25) + (1/265) + (1/74) + (1/305) }

= (0.02856)^0.5 = .1690

LL = ln(1.944) – 1.96*0.1690

= 0.6647 – 0.3312 = 0.3335 =exp(0.3335) = 1.396

UL = ln(1.994)+1.96*0.1690 = 0.9960 = exp(0.9960) =2.707

So. The 95% Confidence Interval = 1.396 – 2.707

Calculation of OR by classical method

Outcome Number of Sexual partners

6+ 0-1

Cervical cancer cases 46 (a) 265 (b)

Controls 8 (c) 305 (d)

Odds in Cervical cancer cases = a/b = 46/265

Odds in Controls = c/d = 8/305

OR = a/b/c/d = ad/bc = 46*305/(265*8) = 6.618

Nested Case Control Study:In a traditional cohort study all study individuals aresubjected to the same procedure – interviews,health examinations, laboratory measurements, etc.at the time of their entry into the study andthroughout the follow up period. Alternatively acohort may be identified and followed up until asufficient number of cases are obtained. Moredetailed information is then collected and analysedbut only for the cases and for a sample of thedisease free individuals (controls), not for allmembers of the cohort. This type of case controlstudy conducted within a fixed cohort is called anested case – control study.

Survival Rate :

It indicates the percentage of people in a study ortreatment group who are alive for a given period of

time after diagnosis. Survival rates are important for

prognosis, for example whether a type of cancer hasa good or bad prognosis can be determined from its

survival rate.

Patients with certain disease can die directly from

that disease or from an unrevealed cause such as a

car accident or poisoning. When precise cause ofdeath is not specified, it is called the overall survival

rate or observed survival rate.

Survival rate is often expressed over standard timeperiods like one, three and five years. For example,prostate cancer has a much higher one year overallsurvival rate than pancreatic cancer and thus has abetter prognosis.

Relative Survival :

It is calculated by dividing the overall survival afterdiagnosis of a disease by the survival rate asobserved in a similar population that was notdiagnosed with the disease. A similar population iscomposed of individuals with at least age andgender similar to those diagnosed with disease.

Calculation of Relative survival - Mumbai

Total 1 year 3 years 5 years

Number of Breast cancer cases

7294 5682 4128 3355

% Absolute Survival

100 77.9 56.6 46.0

General survival 100 97.7 93.7 89.5

Relative survival 100 79.7 60.4 51.4

*Source: R. Sankarnarayanan, R Swaminathan; Cancer Survival in Africa, Asia, the Caribbean and Central America; IARC scientific Publications No. 162 (2011)

1992-94 -- > 1999; 1995-99 --> 2003

ChennaiKarunag

appallyMumbai Chennai

Karunag

appallyMumbai

Tongue C01-02 51.6 62.6 56.5 53.3 65.1 58.3

Oral cavity C03-06 60.9 65.6 60.5 62.9 68.3 62.2

Oesophagus C15 32.1 27.0 36.8 33.2 28.3 38.3

Stomach C16 34.5 22.1 33.6 35.7 23.1 34.8

Larynx C32 65.6 69.6 59.9 68.0 72.5 62.3

Lung C33-34 31.9 22.2 28.4 33.0 23.1 29.6

Breast C50 79.2 85.8 77.9 81.0 87.2 79.7

Cervix C53 77.0 82.9 75.2 78.4 85.7 76.6

Ovary C56 60.3 62.9 49.7 61.4 64.1 50.7

Prostate C61 50.2 93.5 64.3 51.3 101.2 77.9

One year Absolute and Relative Survival Rates for selected cancer sites

Source: Cancer Surviva l in Africa , As ia , the Caribbean and Centra l America - IARC Scienti fic

Publ ications No. 162; Edited by R. Sankaranarayanan and R. Swaminathan - 2011

Relative Survival

SiteICD10

code

Absolute Survival

ChennaiKarunag

appallyMumbai Chennai

Karunag

appallyMumbai

Tongue C01-02 19.4 25.9 25.3 23.0 31.9 29.3

Oral cavity C03-06 30.5 33.1 32.3 35.7 41.2 37.0

Oesophagus C15 6.9 2.9 13.0 8.3 3.5 15.4

Stomach C16 8.6 2.6 12.8 10.1 3.3 14.8

Larynx C32 30.7 29.6 28.6 36.8 35.1 34.6

Lung C33-34 6.5 5.3 10.9 7.6 6.4 13.2

Breast C50 43.7 46.8 46.0 48.6 51.2 51.4

Cervix C53 54.0 46.7 42.2 59.4 56.3 46.1

Ovary C56 27.4 26.0 22.8 29.7 28.1 24.6

Prostate C61 - 22.1 24.0 - 34.6 35.9

Source: Cancer Survival in Africa, Asia, the Caribbean and Central America - IARC Scientific

Publications No. 162; Edited by R. Sankaranarayanan and R. Swaminathan - 2011

Five years Absolute and Relative Survival Rates for selected cancer sites

SiteICD10

code

Absolute Survival Relative Survival