Case-cross over studies, case-time-control studies and other case-only studies

Dr. Jørn OlsenEpi 200B

February 25, 2010and

March 2, 2010

People with acute diseases often try to identify their causes.

RED WINE HEADACHE

IR after red wine exposure, IR without exposure; cross-over designs

Case-cross over study

A design for cause-effect associations with short induction/latency time periods

Cell phone use car accidents

Exposure ref. Exp.W

10 min 10 min

Accident

Case types

Type Exp ref Exp w

1

2

3

4

-

-

+

+

-

+

-

+

OR =

∑ type 2

∑ type 3

The design rules out time-stable personal habits (including genetic factors) as confounders but not time-dependent factors.

Selection bias if type 2 and type 3 cases decide on participation based upon their exposure status.

Information bias is a potential problem if exposure status is based upon recall.

The case-crossover design is biased if the exposure varies over the time period under study.

The case-time study tries to incorporate adjustment for this change over time by including data on exposure used over time for controls.

This will not automatically adjust for confounding by indication. Detailed data on disease severity are needed.

Examples

Case-crossover studyN Engl J Med 1997;336:453-58

Aim:Use of cellular telephones - a risk factor for motor vehicle accidents?

Methods:Case-crossover = case ascertainment North YorkCollision Reporting Centre, Toronto. July 1, 1994- August 31, 1995, 10-18 hours, Monday-Friday.

Note! Centre does not include accidents with injuries, only substantial property damage.

Criteria:Excl. drivers who had no cellular phone or no billing records.

Case-crossover studyN Engl J Med 1997;336:453-58

Timing of the accidentSubject statementPolice recordsCall to emergencyTwo out of 3 = exact

Timing of exposure:10 minutes prior to accident

Reference exposure time:Workday before the accidentSame weekdayThe week before the accidentAdjustment for driving

Case-crossover studyN Engl J Med 1997;336:453-58

5890 drivers - 1064 had a phone - 742 participated -

699 had a billing record

Time of accident: exact 231 inexact 468

170 had used the phone 10 minutes prior to the accident

37 the weekday before

crude OR 6.5 (4.5, 9.9)

adj OR 4.3 (3.0, 6.5)

Table 2. Relative risk of a motor vehicle collision in 10-minute periods, according to selected characteristics

CharacteristicsNo. with telephone

use in 10 min

before collision

Relative Risk (95% CI)

All subjects 170 4.3 (3.0-6.5)

Age (yr)< 2525-3940-54≥ 55

21954410

6.5 (2.2 – N/A)4.4 (2.8 - 8.8)3.6 (2.1 - 8.7)3.3 (1.5 – N/A)

SexMale Female

12347

4.1 (2.8 - 6.4)4.8 (2.6 - 14.0)

High-school graduation

YesNo

15317

4.0 (2.9 - 6.2)9.8 (3.0 – N/A)

Type of job ProfOther

34136

3.6 (2.0 - 10.0)4.5 (3.1 - 7.4)

Characteristics

No. with telephone use

in 10 min before collision

Relative Risk (95% CI)

Driving experience (yr)

0-910-1920-29≥ 30

40673627

6.2 (2.8 - 25.0)4.3 (2.6 - 10.0)3.0 (1.7 - 7.0)4.4 (2.1 - 17.0)

Cellular telephone experience (yr)

0 or 12 or 34 or 5≥ 6

51393644

7.8 (3.8 - 32.0)4.0 (2.2 - 12.0)2.8 (1.7 - 6.7)4.1 (2.3 - 12.0)

Type of cell phone

Hand-heldHands free

12941

3.9 (2.7 - 6.1)5.9 (2.9 - 24.0)

Fig. 2 Time of cellular-telephone call in relation to the relative risk of a collision

10

8

6

4

2

0•

• •

•

Fig. 3 Consistency of relative risks obtained from different collision times

100.0

10.0

1.0

0.1

Mornin

g Aftern

oon

Evening

Other

Monda

y

Tuesday

Wed

nesd

ay

Thurs

day

Frid

ayW

eeke

nd

•• • • • •

••

•

•

Time of Day Day of Week

Similar study

Similar study from Pearth (MCEvoy et al, BMJ 2005)

Cases=Drivers > 17 years seen in emergency departments 2002-2004 who used or had a cell phone; Monday to Friday 8am-9pm

Excl. fatalities

Data

Interviews, billing records Reference period-24Hr, 72Hr, 7 days

prior to accident exposure time period 10 minutes

Timing of crash: Interviews, police reports, medical records

Participants

1625 drivers 454 no cell phone 133 not eligible 97 declined

Total = 941

Anger and Injury

Winson et al Ann Fam. Med. 2006;4:66-68

Case-cross over study on anger and injury-2117 cases and 1533 regular controls (population based RDD)

Data on anger shortly before and 24Hr prior to injury

Anti-Inflammatory Drugs

Etienney. Gut 2003; 52:260-263 Cases 285 pt. visiting GPs from 1998-

99 in France with diarrhea Exposure: Use of NSAIDs 1,3,6 days

prior to disease – similar periods 4 months earlier

Several conditions need to be fulfilled. One is no time trend in exposure over study period – o.k. for the cell phone study when exposure data is measured one week apart.

Conditions

Conditions

Now think about this design in the

context of identifying teratogens during

pregnancy.

Which advantages?

Which problems?

A study on antiepileptic drugs and congenital malformations

3-6 pregnant women per 1000 suffer from epilepsy. Some of these women need treatment. Will treatment increase the risk of congenital malformations? Case-control studies show associations.

Ref. Kjaer et al. Pharmoepidemiology and Drug Safety. 2007;16:181-88.

Conditions

A case-cross over study would be less vulnerable to recall bias?

1 2 3 4 5 6 7 8 9CASE

Pregnancy marker

Organogenese Reference

OR = Exp organogenesis – Not exp reference (type2)Exp ref – not exposed organogenesis (type 3)

But drug use change over pregnancy time – declines with time

Would be biased – in which direction?We need controls to adjust for this time trend – case-time-control study

Our measure of association then becomes

OR cases OR controls

∑ type 2∑ type 3

∑ type 2∑ type 3OR =

Case-time-control

1 2 3 4 5 6 7 8 9

1 2 3 4 5 6 7 8 9

CASES

CONTROLS

Pregnancy months

Pregnancy months

Organogenese Reference

Organogenese Reference

N Discordant OR pairs 95%CI

Phenytoin, phenobarbit

al eller diazepam

ControlCases

38151

22843

560/1564457/1057

1,2 (1,0-1,4)

Specielle grupper MM

NTD 1202 44/532,3 (1,5-

3,5)

Cleft-lippalate

1374 36/541,9 (1,2-

2,9)

Intestinal malformations

153 7/63,2 (1,1-

9,7)

Arms/legs

548 18/222,3 (1,2-

4,3)

Multiple Malformations

1349 39/901,2 (0,8-

1,8)

Results from the Hungarian case-control study

Interaction: the effect measure of one exposure is changed by the different values of another variable.

Depends, sometimes, upon the scale on which the effect is measured.

And depends upon which effect measure you want to estimate Effect measure modification

Other case-only studiesInteractions

Leiden mutation

OC use

Risk per 10 000 women years

RR RD

No No 1

No Yes 4 4 3

Yes No 8

MM Yes Yes 32 4 24

AM Yes Yes 11 1.37 3

MM = Multiplicative Model

AM = Additive Model

Model

MM RRLOC = RRL x RROC

32 = 8 x 4 / 32/1 = 8/1 x 4/1

AM (RRLOC - 1) = (RRL - 1) + (RROC - 1)

(11 - 1) = (8 - 1) + (4 - 1)

Interaction is a statistical term that depends upon the use of a specific scale.

Effect measure modification may be used to describe statistical interaction and biological interaction.

Effect measure modifiers are part of the hypothesis, they are not external to the hypothesis.

Public health interaction has the additive model as the starting point.

Rothman Do you agree?

If we say Leiden V and OC use do not interact, most will believe the combined risk equals the sum of the 2 risks

Using causal fields – two component causes are independent if no sufficient causal fields involves both of them – their combined effect could then follow an additive model.

A – C, etc. works additively, perhaps.

A – B more than additively.

A B C D A E

Causal fields

Additive model- Lung CancerCopper mining

NO YES

NO 1 5

Smoking

YES 10 14

Relative risk for copper exposure:

in non-smokers: 5 / 1 = 5

in smokers: 14 / 10 = 1.4

(RRSC-1) = (RRS-1)

+ (RRC-1)

Multiplicative model

Asbestos

NO YES

NO 1 5

Smoking

YES 10 50

RRSA = RRS x RRA

Relative risk for asbestos:

in non-smokers: 5 / 1 = 5

in smokers: 50 / 10 = 5

Supramultiplicative model

Gene polymorphic variant

NO YES

NO 1 5

Smoking

YES 10 70

RRSG > RRS x RRG

Genotype Environ.

Exp.

Cases Controls OR

Yes Yes a b a/c

No c d b/d

No Yes e f e/g

No g h f/h

The measure of interaction is:

((a/c)/(b/d) / (e/g)/(f/h))if multiplicative this measure is 1

Gene-environment interaction andthe case only study

Can also be written

(a/c) / (b/d)(e/g) / (f/h)

(a/c) / (e/g)(b/d) / (f/h)

Status Env.

Exp.

Genotype

Yes No

OR

Cases Yes a e a/c

No c g e/g

Controls Yes b f b/d

No d h f/h

Stratified on case status

Measure association between environmental exposure and genotype in cases and controls

The interaction term is

e/g

a/c

f/h

b/d If

)(e/g)/(f/h

)(a/c)/(b/d written be alsocan

)(b/d)/(f/h

)(a/c)/(e/g

will therefore measure the deviation from multiplicative effect of the genotype and env. Exp. on disease risk.

is 1; no association between genotype and environmentalexposure.

What case only studies measure

Methodological issues in case-only study

1. Choice of cases2. Assumes no association between external

exposure and genotype3. Evaluation of the individual effect of

external exposure and genotype is impossible

4. Associations may be due to linkage disequillibrium

5. Estimates departure from multiplicative model only – and there may be no reason expect a multiplicative effect

[What does it mean?]

ENV. EXP.

Genotype Yes

No

Yes 122 78 No 140 60

0.67 78/60

122/140

InterpretationLung cancer: cases only

OR =

From published literature: OR (genotype) = around 2

OR (Env. Exp.) = around 3

then:

under additivity: (2-1) + (3-1) = (4-1)

under multiplicativity: 2 x 3 = 6

OR for departure from multiplicative relation:

4 / 6 = 0.67

Genotype

In this example 0.67 indicates interaction on the multiplicative scale, but the gene and the environmental exposure do not operate antagonistic. They operate on the additive scale.

Reality is much complicated than these statistical models.

Deviations from these model assumption are called interactions or effect measures modifications.

These interactions are of interest if they tell us something about how genes and environmental factor actually interact. This is seldom the case.

Gene - environmental

Gene environmental interaction in a biological sense rest upon a functional understanding of biological mechanisms.

Vineis. IJE;204:945-6

Classification Errors True Relative Risks

% 1.5 2.0 2.5

Observed Relative Notes

90 1.1 1.1 1.1

40 1.3 1.5 1.7

20 1.4 1.8 2.1

10 1.4 1.9 2.3

Conclusion

Therefore we will continue to get misleading reports on gene-environment interactions.

The only useful information we get may be that the exposure only play a role for specific genotypes or specific genotypes require a certain exposure to activate a disease

Now genetic polymorphisms can be inherited or caused by the environmental exposure – a mutation

That effects the interpretation of the case-only design

ref. Rosenbaum. Biometrics 2004;60:233-40

Inherited genes

Assume the exposure does not prevent the disease

Case if exposed

Case if not-exposed

Yes

Yes

Yes

No

No

No

Genotype A

Genotype B

P1A

P1B

P2A

P2B

P4A

P4B

P1: doomed, P2: causal, P4: immune

The anatomy of the case only study – inherited genes

Let PE be the probability of exposure (strikes individuals at random) – independency assumption

The case only table would then be

Exposed Not exposed

Genotype A

Genotype B

PE(P1A + P2A)

PE(P1B + P2B)

(1-PE)P1A

(1-PE)P1B

The odds ratio would be as usual

PE (P1A + P2A) / (1-PE) P1A

PE (P1B + P2B) / (1-PE) P1B

P1A + P2A P1B + P2B

P1A P1B

Estimation

OR =

OR =

This OR for cases only will show how the exposure odds differ between the two genotypes.

If the environmental exposure has no effect in genotype B persons we have a measure of the relative risk, but that would be unusual.

A study of tumor cells – does the exposure cause a mutation?

E Mutation in a cell (e.g. disables a proto-oncogene (Rasgene))

self-sufficiency in growth signalscell growthmutation of P53 suppressor gene (DNA repair

and apoptosis)

loss of chromosomes (aneuploidy)-geneticinstability

tumor

In cases, we may look for K-ras mutations in tumor cells – indicator that at some point it time this mutation occurred.

Again, if we assume the exposure never prevents the mutation, the exposure strikes at random (PE).

Our table will look like this:

E case mutation in tumor cells

Case-only studies and genetic mutations

Case if

Exposed

Case if not

Exposed

Mutation found

In tumor if exposed

Mutation found in

Tumor if not exposed

Frequency

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Yes

No

Yes

No

No

P1YY

P1YN

P1NN

Yes

Yes

No

No

Yes

No

P2Y

P2N

No No No P4

The anatomy of the case-only study - mutations

And a case only study would look like this

Cancer

Mutation

in tumor Exposed Not exposed

Yes

Yes

Yes

No

PE(P1YY+P1YN+P2Y)

PE(P1NN+P2N)

(1-PE) P1YY

(1-PE) (P1NN+P1YN)

The odds ratio would be

OR =

OR =

But this is not a ratio of risk ratios

PE (P1yy + P1yn + P2y) / (1-PE) P1yy

PE (P1NN+P2N) / (1-PE) (P1NN+P1yn)

(P1yy + P1yn + P2y) / P1yy

(P1nn+P2n) / (P1nn+P1yn)

or

If P1yn = 0 (the mutation is never found in cases with no exposure)then

OR =

Which is a ratio of the risk ratio for having a tumor with the mutation if exposed – divided by the risk ratio for having a tumor without the mutation if exposed.

But this is not a nice estimate and the assumption may be wrong (multiple mutational pathways to the same tumor and genomic instability).

(P1yy + P2y) / P1yy

(P1nn+P2n) / P1nn

Interpretation

The difference between the two settings:

Exposures may cause mutations but not

inheritance of particular genes.

Use case-only design only to study environmental exposures and inherited genetic factors.

Conclusion