Transcript Creating a Cohort of Cases -Case Definition

Creating a Cohort of Cases –
ICTR Workshop on
Clinical Registries
Josef Coresh, MD, PhD
Professor of Epidemiology, Biostatistics & Medicine
Johns Hopkins University
Director, George W. Comstock Center for Public
Health Research and Prevention
Director, Cardiovascular Epidemiology Training
Program
Outline
• Cohort definition (see Gordis “Epidemiology” text for overview)
– Membership criteria (“Case” Definition in a clinical cohort of
cases – but remember that case series is a weak design)
- Considering Referral Pathway
- Considering Precohort Factors
• Data collection – Exposures, Treatments & outcomes (mostly
covered by other lectures)
• Examples of different cohorts to illustrate ideas:
– ARIC
– CHOICE
– CLUE
• Discussion of planned cohorts by participants
Taxonomy of Designs
• Randomized Controlled Trial
• Prospective Cohort Study
– Variations exist – non-concurrent (going
back to old records etc.)
• Case-Control Study
• Cross-Sectional Study
• Other Designs
– Quasi-Experimental
– Ecologic
– Case Report
The basic fighting unit was a cohort, composed of six centuries
(480 men plus 6 centurions). The legion itself was composed of ten cohorts, and the first
cohort had many extra men—the clerks, engineers, and other specialists who did not
usually fight—and the senior centurion of the legion, the primipilus, or “number one
javelin.”
pro·spec·tive
Pronunciation: pr&-'spek-tiv also 'prä-", prO-',prä-'
Function: adjective
Date: circa 1699
1 : relating to or effective in the future
2 a : likely to come about : EXPECTED <the
prospective benefits of this law> b : likely to be or
become <a prospective mother>
“Prospective” in Epidemiology
• Clearly defined cohort (group, sample) of persons at risk
followed through time
– For pre-defined outcomes
– And their relationship to “exposures” measured prior to the
outcome (reduces bias, e.g. recall; but confounding &
effect of subclinical disease remain)
• Data regarding exposures (risk factors, predictors)
collected prior to data on outcomes (endpoints)
• Research-grade data collection methods used for
purpose of testing hypothesis (?)
Distorted Associations – Reverse Causation?
(Baseline Subclinical Disease  lower Cholesterol higher CVD)
Adjusted* 3-year cardiovascular mortality in Dialysis Patients
3-year CVD Mortality Rate Per 100
35
30
Presence of
Inflammation/Malnutrition
25
20
Overall
15
10
Absence of
Inflammation/Malnutrition
5
0
120
160
200
240
Cholesterol, mg/dL
*Adjusted to the age of 60 years, female,
Whites, HD and non-smokers.
Liu et al. JAMA 2004; 291(4):451-9.
Cohort - Membership
• Cohorts are defined at baseline and followed
subsequently (exception: open cohorts can continue to enrol during
follow-up)
• Reasons for selection:
– Group of interest for follow-up (e.g. specific disease brain cancer, MI, ESRD, “middle age”)
• Basis for Inferences:
– Internal comparisons (within the cohort) are strongest
(randomized; “exposure” measured prior to outcome)
– External comparisons are quite weak (e.g. case series)
• Selection: biases all external comparisons but only
some internal comparisons.
Why Do A Cohort Study?
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•
•
•
•
Get incidence data
Study a range of possible risk factors
Establish temporal sequence (risk factor before outcome)
Get representative data (of some population)
Prepare for randomized controlled trial
– Effect size estimates
– Population of eligible participants (“registry”)
• Establish a research empire (not a good primary goal)
Types of Cohorts
•
•
•
•
Occupational (e.g. Asbestos workers)
Convenience (e.g. Precursors, Nurses)
Geographic (e.g. Framingham, ARIC)
Disease or Procedure
– Natural History (e.g. Syncope, Lupus)
– Outcomes Research (e.g. Dialysis, Cataracts)
Sources of Cohort Data
• Clinic Visits
– Laboratory Assays
• Medical Records
• Administrative Data
– Interview
– Medicare
– Physical Examination
– Medicaid
– Imaging
– Managed Care
– Physiologic tests
– Veterans Admin
• Home visits
• Mailed materials
• Telephone Interview
• Birth Records
• Death Certificates
• Specimen Bank
Challenges in Cohort Studies
•
•
•
•
•
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Possibly long duration
Possibly large sample size
Need to recruit people “at risk”
Drop outs, Deaths, Other losses
Concern about residual confounding
Multiple comparisons  Type I error
How to Exploit Cohort Design When
Time is Short & Money is Scarce
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•
•
•
•
•
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Analyze existing data from another study
Piggy-back onto on-going study
Choose hospital-based cohort
Choose short-term outcome
Consider administrative data
Consider public-use data
Consider non-concurrent design
Examples – Food for Thought
Results Drift – Even in a “good” lab
Serum Creatinine Compared to the Mean of All Labs:
College of American Pathologists (CAP) Data
Serum Creatinine Difference, mg/dl
0.5
White Sands - Mean of All Methods
Cleveland Clinic - Mean of All Methods
0.4
Average White Sands - Mean of All Methods
Average Cleveland Clinic - Mean of All Methods
0.3
0.2
0.1
0
-0.1
-0.2
-0.3
-0.4
1/1/1992
1/1/1994
1/1/1996
1/1/1998
Date
Coresh J et al. Am J Kid Dis 2002;39:920-929
1/1/2000
Systematic Errors can be “corrected”
• NHANES 1988-1994 data can be “calibrated” to the
cleveland clinic foundation (CCF) 2006 standardized serum
creatinine assay using regression
1.5
1
.5
0
-.5
3
2
1
-1
-1.5
0
0
0
1
Bland-Altman Plot for Creatinine
black lines are +/- 1.96*SD
Difference (CCF 2006 scr - Original NH3 scr)
4
Uncalibrated NHANES III vs 2006 CCF with identity line
2
3
Uncalibrated NHANES III (mg/dL)
4
.5
1
1.5
2
2.5
3
Mean ([CCF 2006 scr + Original NH3 scr]/2)
diff1
3.5
4
Fitted values
Selvin et al. Am J Kidney Dis. 2007; 50(6):918-26.
ARIC – Atherosclerosis Risk in Communities
• NHLBI cohort to study atherosclerosis
– Community based sample ages 45-64
– ~5 hour examination: interview, exam,
phlebotomy, carotid ultrasound (all standardized)
• Baseline, 3, 6, 9 years … 25 years
– Annual telephone calls
– Chart abstraction of all hospitalizations
– Morbidity and Mortality Classification Committee
review of CHD outcomes
ARIC-NCS Study Design Overview
Exam 1 Exam 2 Exam 3 Exam 4
Calendar Year
1987-89
Median follow-up ,y
0
Brain
MRI
1990-92
1993-95
1996-99
2004-06
3
6
9
17
48-67
14,348
51-70
12,887
54-73
11,656
62-82
1,134
Vascular risk factors X
X
X
X
X
Vascular markers
X
X
X
Age range,y
(n)
45-64
15,792
X
R
ARIC
ARIC-NCS V5
2011-13
25
Combined
visit
68-89
8220 examined
more incl. phone
R
X
X
X
Echocardiogram
X
Aim 1
Cognitive testing
(n)
X
X
14,201
11,343
Aim 2
Aim 3
Brain MRI
Genetics – Aim 5
R – Retinal photography
X
1,929
X
Prevalence
8,220+phone
Stage 2 Eval
2637
Stage 3
MRI
X
X
1,134 Aim 4 2,000**
** Includes 357 dementia,852 MCI, 791 normal; 547 with 2 previous brain MRIs
•Numbers updated to reflect 2011 start + distant + no lower age limit
ARIC – NCS: Aims
 1) estimate the prevalence of dementia/MCI by race and sex




in participants aged 70-89,
2) determine whether midlife vascular factors (risk factors
and markers of macrovascular and microvascular disease)
predict dementia, MCI and cognitive change,
3) determine whether the associations between midlife
vascular factors and dementia/MCI differ by dementia/MCI
subtype defined clinically or by MRI signs,
4) identify cerebral markers associated with cognitive
change, including progression of MRI ischemic burden and
atrophy across 3 MRI scans spanning 17 years, and
5) identify genomic regions containing susceptibility loci
for cognitive decline, using 106 SNPs spanning the genome.
Overview of ARIC Visit 5 + NCS Data Collection
Type of contact
Content
Sample for Stages 2 & 3
Stage 1 (n=6886)
(4/d * 5 d/wk)
Stage 2 –
participant +
proxy
(2.3/d*3d/wk)
AFU Call
Clinic visit
Home or LTC
Stage 3
(2/d * 2d/wk)
Contract V5 + NCS Neuro** +
Cognitive Function retinal
* MRI eligibility
* Schedule stage2
(+MRI for subset)?
MRI – same day as
Stage 2 for dementia +
normals (for borderline
cases MRI sampling
depends on Stage 2)
(6.5 hours)
(~3 hours)
(~1 hour)
Abbreviated exam
Abbreviated – No MRIs
done with
Stage 1
* Only applies to sampled individuals – sampling fractions based on CF & ∆CF
** Skip the neuro exam on most (all but n=50) normals
CHOICE Cohort
Choices for Healthy Outcomes in Caring for ESRD
• Study Design: national prospective cohort study
(CHOICE; PI:Powe & Klag & specimen bank Coresh)
• Study Population:
– 1026 incident outpatient dialysis patients
– Enrolled between 10/95 and 06/98 (DCI + St. Raph)
– Recruited within a median of 45 days from 1st dialysis
(98% within 4 months)
– From 81 dialysis clinics in 19 States
– Age 18 years or older, English or Spanish speaker
– Provided informed consent
• Main research topics: Dose & ModalityOutcomes
2
1
CHOICE Top Papers
119 cited 2,110 by 2010 by (Fink N* AND (Coresh or Powe or Klag))
1. Association between cholesterol level and mortality in - Role of
inflammation dialysis patients and malnutrition . Author(s): Liu YM,
Coresh J, Eustace JA, et al. JAMA 2004 Times Cited: 209
2. Traditional cardiovascular disease risk factors in dialysis patients
compared with the general population: The CHOICE study. Author(s):
Longenecker JC, Coresh J, Powe NR, et al. JASN 2002 Times Cited: 180
3. The timing of specialist evaluation in chronic kidney disease and
mortality Author(s): Kinchen KS, Sadler J, Fink N, et al. Ann Int Med 2002
Times Cited: 176
4. Validation of comorbid conditions on the end-stage renal disease
medical evidence report: The CHOICE study. Author(s): Longenecker JC,
Coresh J, Klag MJ, et al. JASN 2000 Times Cited: 141
5. Changes in serum calcium, phosphate, and PTH and the risk of
death in incident dialysis patients: A longitudinal study. Author(s):
Melamed ML, Eustace JA, Plantinga L, et al. Kidney Int 2006 Times Cited:
96
CHOICE Top Papers
119 cited 2,110 by 2010 by (Fink N* AND (Coresh or Powe or Klag))
6. MYH9 is associated with nondiabetic end-stage renal disease in
African Americans
Author(s): Kao WHL, Klag MJ, Meoni LA, et al. Nature Genetics 2008
Times Cited: 93
7. Timing of nephrologist referral and arteriovenous access use: The
CHOICE study Author(s): Astor BC, Eustace JA, Powe NR, et al. Am J
Kidney Dise 2001 Times Cited: 92
8. Comparing the risk for death with peritoneal dialysis and
hemodialysis in a national cohort of patients with chronic kidney
disease Author(s): Jaar BG, Coresh J, Plantinga LC, et al. Ann Int Med
2005 Times Cited: 86
9. Type of vascular access and survival among incident hemodialysis
patients: The choices for healthy outcomes in caring for ESRD
(CHOICE) study
Author(s): Astor BC, Eustace JA, Powe NR, et al. J Am Soc Nephrol 2005
Times Cited: 73
10. Comorbidity and other factors associated with modality selection
in incident dialysis patients: The CHOICE Study Author(s): Miskulin DC,
Meyer KB, Athienites NV, et al. J Am Soc Nephrol 2002 Times Cited: 72
Washington County, MD
Johns Hopkins University
Research Opportunities in
Washington County: From shoeleather epidemiology to
genomics
Josef Coresh, MD, PhD
Professor of Epidemiology, Biostatistics &
Medicine Johns Hopkins University
Director, George W. Comstock Center for
Public Health Research and Prevention
Ana Navas-Acien, MD, PhD
Assistant Professor, Environmental Health
Sciences & Epidemiology
Sleep
Heart
Health
CLUE I & CLUE II Studies
CLUE I (1974) N=26,147
• Serum stored at -70o
• Baseline questionnaire
CLUE II (1989) N=32,894
• Plasma , RBC, DNA -70o
• Toenail sample
• Baseline questionnaire
• Food freq. questionnaire
The CLUE Specimen Banks: A paradigm for long-term, population-based
studies to evaluate cancer-related biomarkers
CLUE I (1974)
N=26,147
CLUE II (1989)
N=32,894
Key advantages:
Odyssey
Serum
(8297 also
gave to
CLUE I)
Plasma
WBC
RBC
• large, prospective
• population-based
• long term follow-up
• specimens from multiple time points
• specimens obtained prior to
diagnosis
• multiple health outcomes
Baseline questionnaire – FFQ included in CLUE II
Follow-up for cancer outcomes through Washington County Cancer Registry
(medical record/treatment info available)
Active follow-up of CLUE II cohort: questionnaires
1996, 1998, 2000, 2003, 2007
Number of Deaths
from CLUE I and CLUE II Volunteers
as of 6/30/2009
Clue I
Clue I Clue II & II
Cause of Death
ICD10*
Heart Disease
Cancer
Cerebrovascular
Chronic Lower
Respiratory Disease
Influenza, Pneumonia
Accident
I20 – I51
C00 -C97
I60 – I69
1261
929
254
713
668
144
777
672
170
2751
2269
568
J40 –J47
J10 –J18
V01- X59,
Y85, Y86
N00 -N07,
N17 -N19
N25 -N27
222
149
83
125
61
59
121
72
52
468
282
194
53
30
33
116
5823
2379
8299
4855
Nephritis, Nephritic
syndrome, Nephrosis
Total
All deaths
Total
2476 10678
* ICD-8 and 9 used for previous years
Underlying caues of death data not available for 1999 CLUE I and 23 CLUE II participants (11 in CLUE I & II)
Thank you!
CKD-Epi
CHOICE Study
CVD-Epi
(it takes a team)
Stein Hallan
ARIC Staff