Epidemiologic MethodsFall 2012

First 5 Lectures

• Overview of Study Design (today)

• Disease Occurrence I and II

• Disease Association I and II

Study DesignOutline of Topics for Today

• Individual vs group as unit of observation• Underlying study base or cohort• Cohort design• Cross-sectional design• Case-control design

– 3 ways to sample controls

– Primary & secondary study bases

• Case-crossover/case series design• Incident versus prevalent disease• Retrospective versus prospective – what matters

Human Subjects Studies

Unit of observation

Group (eg, geographic area) Individual

Ecological Studies

Between-SubjectCohort

Cross-sectionalCase-Control

RandomizedNon-randomized

ObservationalExperimental

Within-SubjectCase-crossover

Case onlySelf-controlled case series

Ecological study: water fluoride & dental caries

• 191 municipalities in Denmark in 2004.

• Unit of analysis was the municipalities.

• Mean DMFS of 15-year-olds was used as outcome variable.

• Concentration of fluoride in the water supply (mean) ppm.

Ekstrand et al. Factors associated with inter-municipality differences in dental caries experience among Danish adolescents. Community Dent Oral Epidemiol 2010

Ecological association

Fluoride concentration in the water supply versus mean DMFS among 15-year-olds in the different municipalities in 2004. Tendency line is presented.

Ecological fallacy• Mean income and traffic injuries

• Results using community as the unit of analysis

Mean income

Injuries (%)

Popn A $23,940 57%

Popn B $22,430 43%

Popn C $21,410 29%Communities with higher income have more traffic injuries.

What about individuals with higher income?

• Results using individual as the unit of analysis:

Mean income

Cases (traffic injury) $13,230

Ctrls (no injury) $32,310

Individuals with higher income have fewer traffic injuries.

Ecological Fallacy

Human Subjects Studies

Unit of observation

Group (eg, geographic area) Individual

Ecological Studies

Between-SubjectCohort

Cross-sectionalCase-Control

RandomizedNon-randomized

ObservationalExperimental

Within-SubjectCase-crossover

Case onlySelf-controlled case series

Cohort is the basis of design with the individual as the unit of measurement

With individual as unit of observation, all study design is best thought of as sampling the disease experience of an underlying study base or cohort

Concept of the Study BaseThe study base is the population that experiences the

disease outcomes you will observe in your study

Study Design Study Base

cohort explicitly defined cohort

cross-sectional hypothetical cohort sampled at one point in time

case-control the cohort, either explicit or hypothetical, that gave rise to the cases

Three Keys to Study Design Using Observation of Individuals

• Identify the population that is the Study Base

• Determine how the experience of the Study Base population will be/was sampled

• Consider the timing of measurements of exposure and outcome, relative to each other

Cohort study designD = disease (event) occurrence; arrow = losses to follow-up

Minimum loss to follow-up (1%)

Cohort study designD = disease (event) occurrence; arrow = losses to follow-up

Minimum loss to follow-up (1%)

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Cohort study• Every cohort has competing events, unless the outcome is

all-cause mortality.

• Schematic assumes one-time event but also possible to study repeated events

• In a cohort study, we can measure: – rate of event occurrence, how many events occur in a certain

amount of person-time

– risk of event occurrence, probability of event occurring over set time

• For now, we are assuming that we can accurately identify when an event occurs

What is a cohort?

• From the Latin cohors, the basic unit of a legion in the Roman army.

• A cohort is defined and described by its characteristics at baseline, i.e. the beginning of follow-up.

Examples:

• Research cohort, recruited and followed for particular study, e.g. Framingham study

• Administrative cohort, e.g., Kaiser members

• Geographically defined cohort, e.g.,residents of SF

Cohort Study Design

• Mimics individual’s progress through life and accompanying disease risk

• Gold standard because exposure/risk factor is observed before the outcome occurs

• Randomized trial is a cohort design with exposure assigned rather than observed

Framingham Cohort Study The impact of diabetes on survival following myocardial

infarction in men vs women. The Framingham Study.Abbott RD, Donahue RP, Kannel WB, Wilson PW.

The impact of diabetes on recurrent myocardial infarction (MI) and fatal coronary heart disease was examined in survivors of an initial MI using 34-year follow-up data in the Framingham Study. Among nondiabetic patients, the risk of fatal coronary heart disease was significantly lower in women compared with men (relative risk, 0.6). In the presence of diabetes, however, the risk of recurrent MI in women was twice the risk in men. In addition, the effect of diabetes doubled the risk of recurrent MI in women (relative risk, 2.1) but had an insignificant effect in men.

JAMA, 1989

Threat to Validity in a Cohort Study: Losses to follow-up What bias do those lost introduce? Missed disease diagnoses?Those with a risk factor more or less likely to leave?

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Subjects lost during follow-up

• If losses are random, only power is affected

• If disease incidence is research question, losses that are related to outcome will bias results

• If association of risk factor to disease is focus, losses bias results only if related to both outcome and the risk factor

Two Cohort Studies of HCV/HIV Coinfection and Risk of AIDS

• Swiss HIV Cohort

• 3111 patients, ‘96-’99

• At least two visits

• Med. follow-up 28 mos

• HCV+ more rapid disease progression

• Adj RH = 1.7 (95% CI = 1.3 - 2.3)

• No loss to follow-up info (Greub, Lancet, 2000)

• Johns Hopkins Cohort

• 1955 patients, ‘95-’01

• At least two visits

• Med. follow-up 25 mos

• HCV not associated with disease progression

• Adj RH = 1.0 (95% CI = 0.9 - 1.2)

• No loss to follow-up info (Sulkowski, JAMA, 2002)

Cross-Sectional Study Design

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Cross-Sectional DesignMeasures Prevalence

• Measures prevalence of disease at one point in time. Two types:– Point prevalence: Do you currently have a

backache?

– Period prevalence: Have you had a backache in the past 6 months?

• Don’t confuse with length of time to conduct the study. e.g., Both examples above could occur in a study conducted over 4 months.

Cross-Sectional DesignWeaknesses

• Cannot determine whether putative cause preceded the disease outcome

• Cannot distinguish factors associated with disease (incidence) from factors associated with survival with disease (prevalence)

Example of Cross-sectional Study• Objective: Determine the prevalence of neck and

shoulder pain in a well-functioning cohort, identify factors associated with this pain, …and evaluate the impact of this pain on physical functioning.

• Methods: 3,075 men and women in Health ABC study. 50% white/50% black. 70-79 y.o. Well-functioning.

• Baseline visit: Participants were asked if they had had neck or shoulder pain lasting at least 1 month during the previous year, and to rate severity of any pain.

Vogt et al. Neck and shoulder pain in 70- to 79-year-old men and women: findings from the Health, Aging and Body Composition Study. Spine 2003.

(continued)

• Assessment of functioning was carried out using a battery of lower-extremity performance tests

• Results: 11.9% reported neck pain and 18.9% reported shoulder pain. .. More severe neck/shoulder pain associated with lower physical performance measures.

Case-Control Design• Case-control studies are an efficient way to

sample an underlying cohort

• Study Base in case-control design = the population (or underlying cohort) that gave rise to the cases (Szklo and Nieto call it the “reference population”).

• Case-control design is best understood by considering how the experience of a cohort is sampled

• Study base is the key concept that links case-control design and cohort design

Case-Control Key Concept #1

• Think of the selection of cases and controls as occurring from an underlying cohort (or study base)

Primary & Secondary Study Bases• Case-control studies can be thought of as evolving from one of two study

bases (i.e. underlying cohorts):

– Primary study base vs Secondary study base

• A primary study base is one where the underlying cohort is readily defined, either because it is:

– previously assembled for research (e.g., Framingham)

– administratively defined (e.g., Kaiser members in 2004)

– or geographically defined (e.g., SF residents in 2008)

• A secondary study base is more elusive. It starts with the cases and then works backwards.

Cohort study designD = disease occurrence; arrow = losses to follow-up

Given that all the cases are diagnosed, how would you samplecontrols from this cohort for a case-control study?

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3 Ways to Sample Controls within a Cohort (Primary Study Base)

• At time each case is diagnosed = incidence density sampling

• A random sample of the cohort at baseline = case-cohort design

• From persons without disease at the end of follow-up = prevalent controls design (aka “cumulative” or “epidemic” design)

Incidence Density Sampling within a Cohort Study Study Base = Cohort

In this example, controls are randomly sampled each time a case is diagnosed from those still in follow-up without the diagnosis. It followsthat a subject who is a control at one time may become a case later in time.

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Example of case-control study with incidence density sampling (of a primary study base)

Abstract

We investigated associations between metabolic syndrome, its components, and breast cancer risk in a nested case–control study on postmenopausal women of the ORDET cohort (N = 10,000).

After a median follow-up of 13.5 years, 163 women developed breast cancer…Four matched controls per case were selected by incidence density sampling, and rate ratios were estimated by conditional logistic regression. Metabolic syndrome (i.e. presence of three or more metabolic syndrome components) was significantly associated with breast cancer risk (rate ratio 1.58 [95% confidence interval 1.07–2.33])…

Metabolic syndrome and postmenopausal breast cancer in the ORDET cohort: A nested case–control study Agnoli et al. Nutr

Metab Cardiovasc Dis. 2009

Efficient design! 815 (163 cases + 652 ctrls) represent 10,000

Counterintuitive Idea #1• Individuals can be controls at one point in time and

cases at a later time

• Incidence density sampling: Sampling “person-time” not individuals. Each time a case occurs, the remaining cohort is sampled for controls from those in follow-up at that time.

• Compare with a full cohort: Individuals contribute person-time up until becoming a case or the end of their follow-up. This case-control design samples from the person-time experience of the cohort.

Another example of incidence density sampling

• Objective: Associations between serum C-reactive protein (CRP) and colon and rectal cancer

• Methods: Nested case-control study within the European Prospective Investigation into Cancer and Nutrition, over 520,000 participants recruited 1992–2000.

• Cases: Incident cancer cases (N=1,096) identified through record linkage with regional cancer registries. Closure dates ranged from December 1999 to June 2003

• Controls: We used an incidence density sampling protocol for control selection (N=1,096), such that controls could include subjects who later became cases, while each control subject could also be sampled more than once. Matching characteristics were study center at the time of enrollment, sex, age at blood collection (6-month to 2-year intervals),…

• Results: Evidence that elevated CRP concentrations are related to a higher risk of colon cancer but not rectal cancer.

Aleksandrova et al. Circulating C-Reactive protein concentrations and risks of colon and rectal cancer. AJE 2010

Case-cohort design: sample baseline of cohort

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Case-cohort design: Case-control study using sampling of the baseline of the

underlying cohortAbstract

We conducted a case cohort investigation of colorectal cancer among nondiabetic subjects enrolled in the Women’s Health Initiative Observational Study, a prospective cohort of 93,676 postmenopausal women.

Fasting baseline serum specimens from all incident colorectal cancer cases (n = 438) and a random subcohort (n = 816) of Women’s Health Initiative Observational Study subjects were tested for insulin, glucose, total IGF-I, free IGF-I, IGF binding protein-3, and estradiol.

Gunter et al. Insulin, Insulin-like Growth Factor-I, Endogenous Estradiol, and Risk of Colorectal Cancer in Postmenopausal

Women. Cancer Res 2008;68(1):329–37

Individual can be a control and a case in case-cohort design

• In the subcohort, some will go on to become cases. How can we include them in the control group?

• Goal is to compare the prevalence of the exposure of interest between the cases and the cohort. Not comparing cases and “non-cases.”

• By comparing exposure between the cases and the underlying cohort, we can calculate an unbiased estimate of the risk ratio.

• More on this in the Disease Association lectures.

Another case-cohort example

• Objective: Determine whether serum C-reactive protein levels, a sensitive indicator of inflammation, are associated with the risk of cardiovascular mortality among older women.

• Methods: We conducted a case-cohort study within the Study of Osteoporotic Fractures, a population-based study involving 9,704 women aged > or = 65 years from four U.S. centers.

• Cases: Random sample of 92 women from the 1,125 women in the cohort who had died during the first 6 years of follow-up.

• Controls: We randomly selected 400 women from the entire cohort.

• Baseline serum C-reactive protein levels

• Results: During 6 years of follow-up, women with C-reactive protein levels in the highest quartile (>3.0 mg/L) had a 8.0-fold (95% confidence interval [CI]: 2.2 to 29) greater risk of cardiovascular mortality than those in the lowest quartile (< or = 1.0 mg/L).

Tice et al. The relation of C-reactive protein levels to total and cardiovascular mortality in older U.S. women. Am J Med 2003.

Case-control design using incident cases + prevalentcontrols

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Case-Control => Case-Referent

• We often think of controls in the “case-control” design as "never cases." With that framework, the prevalent control design looks best. However, as we can see, the prevalent control design is biased. So, case-control is sort of a misnomer. It is best thought of as a "case vs reference" design.

Case-Control Key Concept #2

• Closed (fixed) vs open (dynamic) cohorts

• Any well-enumerated administrative or geographic defined population can be thought of as a dynamic cohort that continues to recruit new subjects over time

Incidence Density Sampling in a Dynamic Cohort (e.g., a primary study base: San Francisco County)

New residents

Incidence-density sampling in a specified population with new subjects entering

D

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Example of case-control study with incidence density sampling in a primary (dynamic) study base

The association between long-term use of NSAIDs and non-Hodgkin lymphoma (NHL) was examined …in an ongoing population-based case-control study in the SF Bay Area. Cases were identified using Surveillance, Epidemiology, and End Results (SEER) registry data. …Controls were a random sample of persons identified by random digit dialing…resided in the same six counties as the cases at the time of diagnosis……After adjustment for age and sex, there was no consistent association between long-term use and NHL for all NSAIDs combined, aspirin, nonselective NSAIDs, and COX-2 inhibitors.

Flick, et al. Use of Nonsteroidal Antiinflammatory Drugs and Non-Hodgkin

Lymphoma: A Population-based Case-Control Study. Am J Epidemiol 2006; Sept 1, 164:497-504.

Dynamic study base: Cases

• Incident NHL between October 2001 and May 2004 in the 6 SF Bay Area counties.

• Eligible cases were those who were SF Bay Area residents at the time of diagnosis, aged 21–85 years at the time of diagnosis, and able to complete an interview in English. NHL cases were identified using rapid case ascertainment and SEER registry data.

• A total of 1,000 cases

Dynamic study base: controls• Control participants were frequency-matched to cases by age, sex,

and county of residence. Control participants were a random sample of persons identified by random digit dialing or from Centers for Medicare and Medicaid Services files. Eligible controls had no history of NHL, resided in the same six counties as the cases at the time of diagnosis, were aged 21–85 years, and were able to complete an interview in English.

• Participants completed in-person interviews designed to measure potential NHL risk factors. Questions were asked regarding use during the past 20 years of aspirin, prescription and over-the-counter nonselective NSAIDs, and cyclooxygenase-2 (COX-2) inhibitors.

• A total of 1,060 controls

• Efficiency prize! 1,000 cases + 1,060 controls represent experience of Bay Area population (~4 million)

Definition of a Primary Study Base

• Primary Study Base = population that gives rise to cases that can be defined before cases appear

• Typically, based on participation in a research study; administrative definition; or geographical area

• Our previous examples of an “underlying cohort” for a case-control study were primary study bases

Secondary Study Base

• Secondary Study Base = population that gave rise to cases, defined as those persons who would have been identified as cases if they had developed disease during the period of study

• Start with cases and then attempt to identify hypothetical cohort that gave rise to them

• Difficult concept but crucial to case-control design when primary study base not possible

Case Control Selection from a Secondary Study Base

• Source of cases is often one or more hospitals or other medical facilities

• For controls, problem is identifying who would come to the facility if diagnosed with the disease

• Careful consideration has to be given to factors causing someone to show up at that institution with that diagnosis

Secondary Study Base

• Example: Incident glioma cases seen at UCSF

• The secondary study base is: Persons whom, if they had developed incident glioma, would have been seen at UCSF.

• Can we identify this secondary study base in practice? Referrals to UCSF come from many areas and for different reasons

• Common approaches fall short– One possible control group might be UCSF patients with a different

neurologic disease

– Patients from a similar tertiary referral clinic are another possible control group

– Residents of the neighborhood of the case are another possibility

Example: case control study with incident cases and 2ary study base

• Oral contraceptive (OC) use has been linked to increased risk of breast cancer, largely on the basis of studies conducted before 1990.

• In the Case-Control Surveillance Study, a US hospital-based case-control study of medication use and cancer, the authors assessed the relation of OC use to breast cancer risk among 907 case women with incident invasive breast cancer and 1,711 controls

• After control for breast cancer risk factors, the multivariable odds ratio for 1 year or more of OC use, relative to less than 1 year of use, was 1.5 (95% CI: 1.2, 1.8).

Rosenberg et al. A Case-Control Study of Oral Contraceptive Use and Incident Breast Cancer AJE 2008

Selection of cases & controls• The present analyses included patients interviewed from

1993 through 2007 in participating hospitals in Baltimore, New York, and Philadelphia. Eligible cases were women aged 25–69 years with invasive breast cancer diagnosed within the previous year who had had no other cancer besides nonmelanoma skin cancer.

• Secondary study base: women aged 25-69 who would have been admitted to a participating hospital if they developed invasive breast cancer

• Can those who belong in this secondary study base be identified?

Selection of cases & controls• Here’s what the investigators did to identify controls: Controls

were selected from 2,330 women aged 25–69 years with no history of cancer, other than nonmelanoma skin cancer, who had been admitted for nonmalignant diagnoses that we judged to be unrelated to OC use…

• Selection of controls should NOT be based on exposure status. Investigators should be concerned with identifying women from the appropriate secondary study base.

Primary vs. Secondary Study Base

• Main problem with a primary base is often ascertainment of all cases

– eg, no registry of all cases for many diseases by geographic area

• Main problem with a secondary base is the definition of the base

– eg, hospital-based case-control studies common but very difficult to determine the study base

Primary vs. Secondary Study Base (cont.)

• Important, under-emphasized aspect of case-control design

• Primary study base case-control studies can be very strong design

• Secondary study base often not explicitly recognized by researchers

– Even when recognized, difficult design to manage and source of many bad case-control studies

Case-Control Key Concept #3

• A biased control group is usually the result of the inability to identify a well defined secondary study base (or the result of ignoring the study base concept entirely)

Two Concepts to Distinguish

• Primary versus Secondary study base focuses on identifying the source of the cases and controls

• Incident versus Prevalent sampling refers to how the cases and controls are sampled (both types of sampling can be done either in a primary or a secondary study base)

Case-control study using prevalent cases (and prevalent controls)

Most common case-control design – and most susceptible to bias.

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A case-control design using prevalent cases

• Sampling glioma patients under treatment in a hospital during study period

• Poor survival so patients in treatment will over-represent those who live longest

• Nature of bias variable and not predictable

• Note: If cases at Kaiser, primary study base. If at UCSF, secondary study base.

• Historically most common design

Case-control study using prevalent cases

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Cross-Sectional Study Design

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Case-Control Key Concept #4

• Incident sampling of both cases and controls is preferable to prevalent sampling

“Nested” Case-Control Study  • Term is used ambiguously

• Most often refers to incidence density sampling within a previously existing research cohort study

• May refer to case-cohort sampling (or even prevalent controls) within a previously existing research cohort study

• Sometimes refers to any case-control study within a primary study base

• Main utility:  A reminder that there is often a far less expensive way to study various outcomes in a cohort than making measurements on everyone.

A Comment on the Terms Prospective and Retrospective

• Prospective and retrospective refer to when the study is conceived in relation to the study base experience (text uses concurrent and non-concurrent)

• But the key issue for the strength of the design is the timing of the measurements (or acquisition of specimens) in relation to each other. Preferable to obtain measurement (or specimen) prior to outcome.

“Exposure Prior to Outcome” is Stronger Design

• Stronger: Measurement recorded, or specimen for assay obtained, before case status known.

• Weaker: Cases and controls interviewed about events once disease status is known

• Exposure can be measured before outcome in prospective OR retrospective study. These terms don’t really tell us what we need to know about potential bias or strength of design for causality.

Case-Control Key Concept #5

• “Exposure measured prior to outcome”

• Strength of design rests on accurate measurements made prior to the outcome, not whether it is cohort or case-control sampling, or whether it is prospective or retrospective

Strong Case-Control Design• Kaiser Research Division 1990

– Question: Does screening sigmoidoscopy prevent colon cancer deaths?

• Design choices

– Start a new cohort: incidence about 100 deaths per yr but only about 15% of colon cancers detectable by sigmoidoscopy—10 to 20 yrs

– Look back at cohort: Kaiser members in 18-year period--100,000’s of records to review

– Case-control: Sample experience of Kaiser cohort

Case-Control Design• Colon cancer deaths

1971-1988: 1712

• Cases=colon ca deaths detectable by sigmoidoscopy: 261

• 4 controls per case

• Controls = alive and in Kaiser at time of matched CA death (incidence-density)

• Dynamic cohort

• Blinded review of prior 10 years of medical records

• Predictor=screening sigmoidoscopy

• 8.8% of cases vs. 24.2% had prior screening sigmoidoscopy

A case-control study of screening sigmoidoscopy and mortality from colorectal cancer. Selby et al., NEJM 1992; 326:653-7

Incidence Density Sampling in Kaiser (Dynamic Cohort)

New members

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Critical Features of Good Case-Control Design

• Clearly identifiable study base (preferably a primary study base)

• Cases: all, or random sample, of incident diagnoses in the study base

• Controls: an unbiased sample of study base to estimate exposure prevalence– Incidence density or case-cohort sampling

• Measurements preferably based on records or stored biological samples rather than recall

Case-Crossover Design

• Compare exposure just before event and exposure at an earlier time, in the same case

• Suited to brief (acute) exposure with a relatively rapid effect on the outcome

Case-crossover design: Just the cases

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Case-Crossover Example

• Objective: Relationship between air pollution and incidence of cardiac arrhythmia in patients with implantable cardioverter defibrillators (ICDs).

• Methods: 34 patients with ICDs residing in the Vancouver, Canada, area were included representing all patients attending the 2 ICD clinics in the study region who had recorded at least 1 ICD discharge during the study period.

• Air pollutant concentrations on days for which ICD discharges were observed (“case days”) were compared to concentrations on control days in case-crossover analyses.

• Control days were selected symmetrically, 7 days before and after each case day.

Rich et al. A Case-Crossover Analysis of Particulate Air Pollution and Cardiac Arrhythmia in Patients with

Implantable Cardioverter Defibrillators Inhal Toxicol, 2004

Summary: Three Keys to Study Design Using Observation of

Individuals• Identify the Study Base (or Underlying Cohort)

– For case-control: Primary or Secondary study base

• Determine how the experience of the Study Base will be sampled

– All members of cohort or a sample (incidence-density, case-cohort, case only)

– Incident vs prevalent disease

• Identify the timing of measurements of exposure and outcome, relative to each other

– Exposure measured (or specimen obtained) before outcome is known