Matching in case control studies
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Matching in case control studies. Yvan Hutin. Cases of acute hepatitis (E) by residence, Girdharnagar, Gujarat, India, 2008. Attack rate per 1,000 > 40 30-39 20-29 >0-10 0. Water pumping station. Leak. Drain overflow.

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Matching in case control studies

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Matching in case control studies

Matching in case control studies

Yvan Hutin


Matching in case control studies

Cases of acute hepatitis (E) by residence, Girdharnagar, Gujarat, India, 2008

Attack rate per 1,000

> 4030-3920-29

>0-10

0

Water pumping

station

Leak

Drain overflow


Risk of hepatitis by place of residence girdharnagar gujarat india 2008

Risk of hepatitis by place of residence, Girdharnagar, Gujarat, India, 2008

RR = 2.3, Chi Square= 41.1 df= 1. P < 0.001


Attack rate of acute hepatitis e by zone of residence baripada orissa india 2004

Underground water supply

Pump from river bed

Attack rate of acute hepatitis (E) by zone of residence, Baripada, Orissa, India, 2004

Attack rate

0 - 0.9 / 1000

1 - 9.9 / 1000

10 -19.9 / 1000

20+ / 1000

Chipat river


Case control study methods acute hepatitis outbreak baripada orissa india 2004

Case-control study methods, acute hepatitis outbreak, Baripada, Orissa, India, 2004

  • Cases

    • All cases identified through active case search

  • Control

    • Equal number of controls selected from affected wards but in households without cases

  • Data collection

    • Reported source of drinking water

    • Comment events

    • Restaurants


Consumption of pipeline water among acute hepatitis cases and controls baripada orissa india 2004

Consumption of pipeline water among acute hepatitis cases and controls, Baripada, Orissa, India, 2004

Adjusted odds ratio = 33, 95 % confidence interval: 23- 47


Key elements

Key elements

  • The concept of matching

  • The matched analysis

  • Pro and cons of matching


Controlling a confounding factor

Controlling a confounding factor

  • Stratification

  • Restriction

  • Matching

  • Randomization

  • Multivariate analysis


The concept of matching

The concept of matching

  • Confounding is anticipated

    • Adjustment will be necessary

  • Preparation of the strata a priori

    • Recruitment of cases and controls

      • By strata

      • To insure sufficient strata size

  • If cases are made identical to controls for the matching variable, the difference must be explained by the exposure investigated


Consequence

Consequence....

  • The problem:

    • Confounding

  • Is solved with another problem:

    • Introduction of more confounding,

    • so that stratified analysis can eliminate it.


Definition of matching

Definition of matching

  • Creation of a link between cases and controls

  • This link is:

    • Based upon common characteristics

    • Created when the study is designed

    • Kept through the analysis


Types of matching strategies

Types of matching strategies

  • Frequency matching

    • Large strata

  • Set matching

    • Small strata

    • Sometimes very small (1/1: pairs)


Unmatched control group

Unmatched control group

Cases

Controls

Bag of cases

Bag of controls


Matched control group

Matched control group

Cases

Controls

Sets of cases and controls that cannot be dissociated


Matching false pre conceived ideas

Matching: False pre-conceived ideas

  • Matching is necessary for all case-control studies

  • Matching needs to be done on age and sex

  • Matching is a way to adjust the number of controls on the number of cases


Matching true statements

Matching: True statements

  • Matching can put you in trouble

  • Matching can be useful to quickly recruit controls


Matching criteria

Matching criteria

  • Potential confounding factors

    • Associated with exposure

    • Associated with the outcome

  • Criteria

    • Unique

    • Multiple

    • Always justified


Risk factors for microsporidiosis among hiv infected patients

Risk factors for microsporidiosis among HIV infected patients

  • Case control study

  • Exposure

    • Food preferences

  • Potential confounder

    • CD4 / mm3

  • Matching by CD4 category

  • Analysis by CD4 categories


Mantel haenszel adjusted odds ratio

Mantel-Haenszel adjusted odds ratio

ai.di) / Ti]

bi.ci) / Ti]

OR M-H=


Matched analysis by set pairs of 1 case 1 control

Matched analysis by set (Pairs of 1 case / 1 control)

  • Concordant pairs

    • Cases and controls have the same exposure

    • No ad and bc: no input to the calculation

CasesControlsTotal

Exposed112

Non exposed000

Total112

CasesControlsTotal

Exposed000

Non exposed 112

Total112

No effect

No effect


Matched analysis by set pairs of 1 case 1 control1

Matched analysis by set (Pairs of 1 case / 1 control)

  • Discordant pairs

    • Cases and controls have different exposures

    • ad’s and bc’s: input to the calculation

CasesControlsTotal

Exposed101

Non exposed011

Total112

CasesControlsTotal

Exposed011

Non exposed 101

Total112

Positive association

Negative association


The mantel haenszel odds ratio

The Mantel-Haenszel odds ratio...

S [(ai.di) / Ti]

S [(bi.ci) / Ti]

OR M-H=


Becomes the matched odds ratio

…becomes the matched odds ratio

SDiscordant sets case exposed

SDiscordant sets control exposed

OR M-H=


And the analysis can be done with paper clips

…and the analysis can be done with paper clips!

  • Concordant questionnaire : Trash

  • Discordant questionnaires : On the scale

    • The "exposed case" pairs weigh for a positive association

    • The "exposed control" pairs weigh for a negative association


Analysis of matched case control studies with more than one control per case

Analysis of matched case control studies with more than one control per case

  • Sort out the sets according to the exposure status of the cases and controls

  • Count reconstituted case-control pairs for each type of set

  • Multiply the number of discordant pairs in each type of set by the number of sets

  • Calculate odds ratio using the f/g formula

Example for 1 case / 2 controls

Sets with case exposed:+/++, +/+-, +/--Sets with case unexposed: -/++, -/+-, -/--


The old 2 x 2 table

The old 2 x 2 table...

CasesControlsTotal

ExposedabL1

UnexposedcdL0

TotalC1C0T

Odds ratio: ad/bc


Is difficult to recognize

... is difficult to recognize!

ControlsExposedUnexposedTotal

Exposedefa

Unexposed ghc

TotalbdP (T/2)

Odds ratio: f/g

Cases


The mac nemar chi square

The Mac Nemar chi-square

(f - g) 2

(f+g)

Chi2McN=


Matching advantages

Matching: Advantages

  • Easy to communicate

  • Useful for strong confounding factors

  • May increase power of small studies

  • May ease control recruitment

  • Suits studies where only one factor is studied

  • Allows looking for interaction with matching criteria


Matching disadvantages

Matching: Disadvantages

  • Must be understood by the author

  • Is deleterious in the absence of confounding

  • Can decrease power

  • Can complicate control recruitment

  • Is limiting if more than one factor

  • Does not allow examining the matching criteria


Matching with a variable associated with exposure but not with illness overmatching

Matching with a variable associated with exposure, but not with illness(Overmatching)

  • Reduces variability

  • Increases the number of concordant pairs

  • Has deleterious consequences:

    • If matched analysis: reduction of power

    • If match broken: Odds ratio biased towards one


Hidden matching crypto matching

Hidden matching (“Crypto-matching”)

  • Some control recruitment strategies consist de facto in matching

    • Neighbourhood controls

    • Friends controls

  • Matching must be identified and taken into account in the analysis


Matching for operational reasons

Matching for operational reasons

  • Outbreak investigation setting

  • Friends or neighbours controls are a common choice

  • Advantages:

    • Allows identifying controls fast

    • Will take care of gross confounding factors

    • May results in some overmatching, which places the investigator on “the safe side”


Breaking the match

Breaking the match

  • Rationale

    • Matching may limit the analysis

    • Matching may have been decided for operational purposes

  • Procedure

    • Conduct matched analysis

    • Conduct unmatched analysis

    • Break the match if the results are unchanged


Take home messages

Take home messages

  • Matching is a difficult technique

  • Matching design means matched analysis

  • Matching can always be avoided


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