classification schemes for error in clinical research szklo and nieto –bias »selection bias...

Classification Schemes for Error in Clinical Research

Szklo and Nieto

– Bias

» Selection Bias

» Information/Measurement Bias

– Confounding

– Chance

Other Common Approach

– Bias

» Selection Bias

» Information/Measurement Bias

» Confounding

– Chance

Confounding and Interaction I

Confounding: one of the central problems in observational clinical research

– What is it? What does it do?

– What kind of variables act as confounders?

– Which variables to consider as confounders?

– Which variables not to consider as confounders?

» Emphasis on specifying the research question

Smoking, Matches, and Lung Cancer

A tobacco company researcher believes that exposure to matches is the cause of lung cancer

He conducts a large case-control study to test this hypothesis


The researcher has located 1000 cases of lung cancer from a population-based registry, of whom 820 have a history of carrying matches.

Among 1000 reference (control) patients (selected randomly from the population and determined to have normal chest x-rays), 340 carry matches.

Quantitate the relationship between matches and lung cancer in your colleague’s data.

Matches and Lung Cancer

Exposure odds ratio = (820/180) / (340/660) = disease odds ratio

OR = 8.8

95% CI (7.2, 10.9)

LungCancer

No LungCancer

Matches 820 340No matches 180 660


You decide to look at the relationship between matches and lung cancer in the smokers separately from the non-smokers.

You find that among the 1000 cases, 900 are smokers and 810 (OF THE 900) carry matches.

Among the 1000 control patients, 300 are smokers and 270 (OF THE 300) carry matches.

Draw the necessary stratified tables and calculate the relevant measure of association


Lung Ca No Lung CaMatches 820 340No Matches 180 660

Lung CaNo

Lung CAMatches 810 270No Matches 90 30

Stratified

Crude

Non-SmokersSmokersOR crude

OR CF+ = ORsmokers OR CF- = ORnon-smokers

Stratification produces two 2-by-2 tables

In each stratum, all subjects are homogeneous with respect to smoking

We have adjusted or controlled for smoking

ORcrude = 8.8 (7.2, 10.9)

ORsmokers = 1.0 (0.6, 1.5)

ORnon-smoker = 1.0 (0.5, 2.0)

Lung CaNo

Lung CAMatches 10 70No Matches 90 630

Confounding: Smoking, Matches, and Lung Cancer

Illustrates how confounding can create an apparent effect even when there is no actual true effect

– Can also be opposite: confounding can mask an effect when one is truly present

Proper terminology

– In the relationship between matches and lung cancer, smoking is a confounding factor or a confounder

– Smoking confounds the relationship between matches and lung cancer

In clinical research, confounding has a very specific meaning

Estes continues to be confounding puzzle Ray RATTO

SHAWN ESTES seemed loath to analyze his own performance last night, for fear that people would see the first three innings and use them to obscure the last four.

But that's what made his outing so perfectly Estes-like -- an ongoing argument with himself that he eventually won.

Well, an argument in which he held his own and his teammates won for him in the bottom of the ninth.

Ramon Martinez lined a game-tying single with two outs, and Jeff Kent followed two batters later with a bases-loaded walk off Juan Acevedo to give the Giants a 2-1 victory against Colorado and move them to within 4 1/2 games of division leader Arizona. It was in many ways an eye-opening victory for a team that hadn't had one of this type for a while.

Finding: “After an initial course of post-exposure prophylactic (PEP) medication following a sexual exposure to HIV infection, gay men reported a decrease in the practice of high-risk behavior over the following year.”

Reviewer: “Perhaps the men simply withheld the real amount of high-risk behavior they had in order to be eligible for future courses of PEP. How do you account for this confounding?”


The study is not over!

To be complete, you also decide to examine the relationship between smoking and lung cancer independent from the use of matches.

What tables should you construct to do this?


Lung Ca No Lung CaSmoking 900 300No Smoking 100 700

Lung CaNo

Lung CASmoking 810 270No Smoking 10 70

Stratified

Crude

Matches Absent

Matches Present

OR crude

OR CF+ = ORmatches

Lung CaNo

Lung CASmoking 90 30No Smoking 90 630

OR CF+ = OR no matches

ORcrude = 21.0 (16.4, 26.9)

ORmatches = 21.0 (10.7, 41.3)

ORno matches = 21.0 (13.1, 33.6)

Confounding: Smoking, Matches, and Lung Cancer

Interpretation?

What is the effect of matches on the relationship between smoking and lung cancer?

Matches have no effect on the relationshipMatches have no effect on the relationship

Effect of matches could have been predicted based on matches — lung cancer relationship

– Illustrates one important component in the requirements of a confounder

(aka a confounding factor) - A confounder must be associated with

the outcome

Confounding: Examples of Magnitude and Direction

OR Crude OR CF+ OR CF- Type of Confounding

4.0 2.0 2.0 Positive 4.0 1.0 1.0 Positive 0.2 0.9 0.9 Positive 4.0 4.0 4.0 No confounding 4.0 8.0 8.0 Negative 1.0 3.0 3.0 Negative 0.9 0.2 0.2 Negative 4.0 0.5 0.5 Qualitative (reversal of

effect)

Disease No DiseaseExposedUnexposed



Stratified (adjusted)

Crude (unadjusted)

Potential Confounder

Absent

Potential Confounder

Present

OR crude

OR CF+ OR CF-

Nightlights

Let there be light!Let there be light!

Nightlights and Myopia

Quinn et al. Nature 1999

Prevalence Ratio =

Myopia No MyopiaNight light 79 153No night light 17 155

5.6) to2.1 :CI (95% 4.3

1721723279

Insert picture with nightlight off

Lights are off and the stumbling around begins.

Lights are off and the stumbling around begins.

Nightlights and Myopia:

Two subsequent studies found no association and explained the prior result by confounding

– Zadnik et al. and Gwiazda et al. Nature, 2000

Child’s MyopiaChild’s Myopia

Night LightNight Light

Parental Myopia

Parental Myopia XX

Insert picture with nightlight on again

Let there be light (again)!Let there be light (again)!

AZT to Prevent HIV After Needlesticks

Case-control study of whether post-exposure AZT use can prevent HIV seroconversion after needlestick (NEJM 1997)

CrudeHIV No HIV

AZT 8 131No AZT 19 189

27 320 347

ORcrude = 0.61

(95% CI: 0.26 - 1.4)

Interpretation?

Could confounding be present?

Interpretation?

Could confounding be present?

HIVHIV

AZT UseAZT Use

Severity of

Exposure

Severity of

Exposure

??

Adjustment for Confounder

Potential confounder: severity of exposure

Minor Severity

Major Severity

Crude

Stratified

HIV No HIVAZT 8 131No AZT 19 189

27 320 347

HIVNo

HIVAZT 0 91No AZT 3 161

3 252 255

ORcrude =0.61

HIVNo

HIVAZT 8 40No AZT 16 28

24 68 92

ORadjusted = 0.30

(95% CI: 0.12 – 0.79)

Negative Confounding

What kind of variables act as confounders?

Properties of a True Confounder

– A true confounder (C) must be associated with:

» the exposure (E) in question and

» the disease (D) under study

ConfounderConfounder

DD

ANOTHER PATHWAY TO

GET TO THE DISEASE

ANOTHER PATHWAY TO

GET TO THE DISEASE

RQ: Is E associated with D independent of C?

RQ: Is E associated with D independent of C?

CC ??

EE

DD

Causal DiagramsCausal Diagrams Formally called directed acyclic graphs

(DAGs)

Frontier of epidemiologic theory

Use for identifying pitfalls of adjusting and not adjusting for certain variables (see text)

Lung CancerLung

Cancer

MatchesMatches

SmokingSmoking??

RQ: Are matches associated with lung cancer independent of smoking?

RQ: Are matches associated with lung cancer independent of smoking?


Refined Properties: Association with Exposure

A confounding variable can be either:

– the cause of

– the result of, or,

– simply associated in a non-causal manner with the exposure in question


DD

C causes EC causes E

? [via cardiovascular

work-out]

RQ: Is sexual activity associated with survival independent of general health?


Non-causal relationshipbetween C and E

Coronary Artery Disease

Other Meds (e.g., ASA)

Ca channel Blockers

GI Bleeding

?

RQ: Are Ca channel blockers associated with GI bleeding independent of other med use?

RQ: Are Ca channel blockers associated with GI bleeding independent of other med use?

E causes C

Poor Diet

Poverty

Mortality

? [access to care]

RQ: Is poverty associated with survival independent of effects on diet?

RQ: Is poverty associated with survival independent of effects on diet?


Refined Properties: Association with Disease

A confounding variable must be associated with the disease.

– It can be a “cause” of disease, or – associated in a non-causal manner


DD

Hep B and C virus

infection

C causes D

IDU

Early Mortality

? [via bacterial infections]

RQ: Is injection drug use associated with survival independent of effect on hepatitis infections?

RQ: Is injection drug use associated with survival independent of effect on hepatitis infections?

Maternal Age

Unknown biologic factor(s)

C as a marker for D

Birth Order

Down Syndrome

?

RQ: Is birth order associated with survival independent of maternal age?

RQ: Is birth order associated with survival independent of maternal age?

General Health

Unknown biologic factor(s)

C as a marker for D

Sexual Activity

? [via cardiovascular

work-out]

Mortality



SuicideSuicide

Anti-depressant use in children

Anti-depressant use in children

DepressionDepression??

SeriousHead Injury

SeriousHead Injury

Use of Helmets in Motorcyclists

Use of Helmets in MotorcyclistsSafety-

oriented Personality

Safety-oriented

Personality

??Safe

Driving

Safe Driving

Cardio-vascular Disease

Cardio-vascular Disease

Anti-retroviral Drugs for HIV

Anti-retroviral Drugs for HIV

AgingAging ??

UnknownBiological

Factors

UnknownBiological

Factors

What is NOT a Confounder?

A variable that is an intermediate step in the causal path under study between the exposure in question and a disease is not a confounding variable.

EE

DD

factor Ifactor I

Despite being associated with both exposure and outcome,

Factor I is not a confounder

It is on the pathway under

study.

It is an intermediary

variable

Despite being associated with both exposure and outcome,

Factor I is not a confounder

It is on the pathway under

study.

It is an intermediary

variable

CCR5 and HIV Disease Progression

CCR5 (receptor)

defect

CCR5 (receptor)

defect

AIDSAIDS

How should CD4 count be handled in assessing the association between CCR5 defect status and progression in HIV disease to AIDS?


??

CCR5: the human cellular receptor for HIV –found on CD4 cells

Genetic defects in CCR5 now described

CD4 count potent predictor of time-to-AIDS




CD4 count

CD4 count

CCR5 and HIV Disease Progression

CCR5 (receptor)

defect

CCR5 (receptor)

defect

AIDSAIDS



CD4 countCD4 count







It depends upon the research question

CCR5 defectCCR5 defect

? [Other mechanisms]

? [Other mechanisms]

? [CD4 count]? [CD4 count]

AIDSAIDS

#1: Is CCR5 associated with progression to AIDS, irrespective of mechanism?



Low CD4 countLow CD4 count

AIDSAIDS

Do not adjust for CD4 count !

Do not adjust for CD4 count !

AIDS No AIDS Defect No defect



High CD4 countHigh CD4 count

CD4 countCD4 count

Do Adjust ! Do Adjust !

#2: Is CCR5 associated with progression to AIDS, independent of CD4 count?

#2: Is CCR5 associated with progression to AIDS, independent of CD4 count?

RQ 1: What if you did adjust for CD4 count?


AIDSAIDS



Low CD4 countLow CD4 count




High CD4 countHigh CD4 count

If “via CD4 count” was only pathway, no effect for CCR5 would be observed after stratification

If “via CD4 count” was only pathway, no effect for CCR5 would be observed after stratification

? [CD4 count]? [CD4 count]

Taylor et al. JAIDS 2003


Other mechanism

Other mechanism

#2 #2

??

CD4 countCD4 count

AIDSAIDS

#1#1


??

AIDSAIDS

Do not adjust !

Do not adjust !

CD4 countCD4 count

Adjust ! Adjust !

Crude (unadjusted) association:

- Relative hazard: 0.71

Crude (unadjusted) association:


Stratified (adjusted) by CD4 count


Stratified (adjusted) by CD4 count


Exercise and CAD

When evaluating the relationship between exercise and CAD, is HDL a confounder or an intermediary?

ExerciseExercise

CADCAD

HDL cholesterol

HDL cholesterol

HDL cholesterol

HDL cholesterol

It depends on the pathway under investigation

If interest is in a pathway other than through HDL, then HDL is a confounder

Therefore, HDL is extraneous to pathway under study

Confounding factors are extraneous factors

ExerciseExercise

CADCAD

[not yet specified

mechanism]

[not yet specified

mechanism]HDLHDL ??

Exercise and CAD If HDL is on the pathway in question, then HDL is

an intermediary variable.

e..g., Does exercise influence CAD risk in a newly studied population (elderly Asians)?

Hence, classification of HDL as confounder or intermediary depends upon the biological pathway under investigation

ExerciseExercise

CADCAD

HDL is not a confounder

here

HDL is not a confounder

here

[HDL . .+. . other mechanisms][HDL . .+. . other mechanisms]

When Planning a Study, Which Factors Should be Considered as

Potential Confounders?

With previously studied exposures-diseases:

– consider/measure any factor for which prior evidence indicates is a confounder

» e.g., effect of diet on CAD?

must deal with smoking as potential confounder

When studying new exposures for which little is known:

– plan on measuring ALL factors associated with the disease

– i.e. If you don’t, you may regret it later

Confounding can be dealt with in the analysis phase of a study but NOT if the confounder is not measured

Seeking cause of high Marin cancer rates Activists canvass residents to search for trends

Thousands of volunteers scattered across Marin County under baleful skies Saturday in an unprecedented grassroots campaign against the region's soaring cancer rate.

Armed with surveys, some 2,000 volunteers went door to door in every neighborhood in the county . . . . The volunteers hope to collect enough money to hire an epidemiologist . . .

classification schemes for error in clinical research szklo and nieto –bias »selection bias...

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