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A critical assessment of the utility of the case-control design in population-based databases A critical assessment of the utility of the case-control design in population-based databases

A critical assessment of the utility of the case-control design in population-based databases - PowerPoint Presentation

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A critical assessment of the utility of the case-control design in population-based databases - PPT Presentation

Martijn Schuemie History Originated in a time when data was not readily available Mayor success Doll amp Hills study showing the link between smoking and lung cancer Nowadays extensively used in retrospective populationbased databases eg CPRD ID: 912063

index cohort control time cohort index time control case isotretinoin date outcome random prior person 2001 year days design

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Slide1

A critical assessment of the utility of the case-control design in population-based databases

Martijn Schuemie

Slide2

History

Originated in a time when data was not readily available

Mayor success: Doll & Hill’s study showing the link between smoking and lung cancer

Nowadays extensively used in retrospective population-based databases (e.g. CPRD)

2

Slide3

Case-control still very popular

3

("Case-Control Studies"[MeSH] OR "case control"[Title/Abstract])

AND

("population-based" [Title/Abstract] OR observational [Title/Abstract] OR pharmacoepidemiology [Title/Abstract])

Slide4

Example study

Crockett et al. 2010

Does isotretinoin use cause IBD (UC)?

Database: PharMetrics

4

Slide5

Case-control (Crocket et al. 2010)

5

isotretinoin

isotretinoin

IBD

For every case (person with the outcome) find n controls

Determine exposure status on or before index date (= date of outcome)

Case

Control 1

Control 2

Jan 10, 2001

Jan 10, 2001

Jan 10, 2001

Exposed in past year?

Exposed in past year?

Exposed in past year?

isotretinoin

Matching on

Calendar time

Age

Gender

Time enrolled

Region (east, south, midwest, and west)

Health

plan

Slide6

Changing perspective

6

isotretinoin

isotretinoin

IBD

View same data as a cohort design

Case

Control 1

Control 2

Jan 10, 2001

Jan 10, 2001

Jan 10, 2001

Exposed in past year?

Exposed in past year?

Exposed in past year?

isotretinoin

Slide7

Changing perspective

7

isotretinoin

isotretinoin

IBD

View same data as a cohort design

Target 1

Target 2

Comparator 1

Jan 10, 2001

Jan 10, 2001

Jan 10, 2001

Outcome in 1 year follow-up?

Outcome in 1 year follow-up?

Outcome in 1 year follow-up?

isotretinoin

Target cohort:

Isotretinoin users

Severe

cystic acne and acne

not responsive

to other treatments

- Index date: any use of drug (not just first)

Comparator cohort:

Random persons

Matched by age, gender, and time enrolled

Index date: random point in time

Slide8

Theoretical objections

Target cohort:

Isotretinoin users

Severe cystic acne and acne not responsive to other treatments

Index date: any use of drug

Comparator cohort:

Random

persons

Matched by age, gender, time enrolled, region, plan

Index date: random point in time

8

Slide9

Theoretical objections

Target cohort:

Isotretinoin users

Severe cystic acne and acne not responsive to other treatments

Index date: any use of drug

Comparator cohort:

Random

persons

Matched by age, gender,

time enrolled, region, plan

Index date: random point in time

9

Vulnerable to between-person confounding

Slide10

Theoretical objections

Target cohort:

Isotretinoin users

Severe cystic acne and acne not responsive to other treatments

Index date: any use of drug

Comparator cohort:

Random

persons

Matched by age, gender, time enrolled, region, plan

Index date: random point in time

10

Vulnerable to within-person (time varying) confounding

Slide11

Empirical evidence to support theory

Replication of Crockett study

Faithful except no matching on

Region (east, south, midwest, and

west)Health planData: Truven CCAE

11

Slide12

Potential for between-person confounding

Std

diff

name

0.57

INTESTINAL ANTIINFLAMMATORY AGENTS

0.55

Aminosalicylic acid and similar agents

0.49

ANTIDIARRHEALS, INTESTINAL ANTIINFLAMMATORY/ANTIINFECTIVE AGENTS

0.47

mesalamine

0.36

Number of distinct drug ingredients observed in long_term_days on or prior to cohort index

0.35

ALIMENTARY TRACT AND METABOLISM

0.34

Number of distinct conditions observed in long_term_days on or prior to cohort index

0.32

Crohn's disease

0.29

Number of distinct procedures observed in long_term_days on or prior to cohort index

0.29

Noninfectious colitis

0.28

Number of visits observed in long_term_days on or prior to cohort index

0.27

Evaluation and management of established outpatient in office or other outpatient facility

0.27

established patient

0.27

IMMUNOSUPPRESSANTS

0.27

IMMUNOSUPPRESSANTS

0.27

RESPIRATORY SYSTEM

0.26

DRUGS FOR OBSTRUCTIVE AIRWAY DISEASES

0.26

DERMATOLOGICALS

0.26

Corticosteroids acting locally

0.26

A detailed history; A detailed examination; Medical decision making of moderate complexity. Counseling and/o

0.26

ANTIINFECTIVES FOR SYSTEMIC USE

0.25

ANTIBACTERIALS FOR SYSTEMIC USE

0.25

NASAL PREPARATIONS

0.25

Glucocorticoids

0.25

OTHER DRUGS FOR OBSTRUCTIVE AIRWAY DISEASES, INHALANTS

12

Covariates with highest standardized difference between cases and controls, captured 720-365 days prior to index

Slide13

Potential for

within-person counfounding

13

Slide14

Estimating residual bias

Same design + outcome definition

25 negative control exposures (drugs we believe do not cause IBD)

Evaluate consistency of ORs with the null

14

Slide15

Case-control residual bias

15

Slide16

Comparing to another design

16

Same data, same negative controls, using case-time-control

Slide17

Bad example?

“Most case-control studies nowadays are nested”

“Most case-control studies nowadays include additional covariates”

17

Slide18

Example study 2

Chou et al. 2014

Do DPP-4

inhibitors cause acute pancreatitis?Database: Taiwan’s NHIRD database

Nested in T2DMMatching on age, sex, and cohort entry yearAdjusting for covariates (gallstone

disease, alcohol-related disease, hypertriglyceridemia, cystic fibrosis, neoplasm, obesity, tobacco use, DCSI,

furosemide, NSAIDs

, corticosteroids, antibiotics, and cancer

drugs)

18

Slide19

Reformulating as a cohort study

Target cohort:

DPP-4 inhibitor users

Index date: any use of

drugComparator cohort:Random persons with T2DM

Matched by age, gender, and time

in cohort

Index date: random point in

time

Outcome model:

- Include hand-picked covariates

19

Slide20

Empirical evidence to support theory

Replication of Chou study

Faithful except we probably don’t have smoking status

Data: Truven CCAE

20

Slide21

Potential for between-person confounding

Std diff

name

0.42

Number of distinct conditions observed in long_term_days on or prior to cohort index

0.41

Abdominal pain

0.41

Number of distinct drug ingredients observed in long_term_days on or prior to cohort index

0.40

Imaging of abdomen

0.38

Emergency department patient visit

0.36

Number of distinct procedures observed in long_term_days on or prior to cohort index

0.36

A comprehensive history; A comprehensi

0.34

Evaluation and management of inpatient

0.34

Radiologic imaging, special views and positions

0.34

Acute pancreatitis

0.34

Diagnostic radiography of abdomen

0.33

Initial patient assessment

0.33

Procedure on abdomen

0.32

Imaging by body site

0.32

ANXIOLYTICS

0.32

Diagnostic radiography, posteroanterior

0.32

Ultrasonography

0.31

Diagnostic radiography of chest, PA

0.31

Radiologic examination, chest; single view, frontal

0.31

OTHER PLAIN VITAMIN PREPARATIONS

0.31

Other plain vitamin preparations

0.31

Epigastric pain

0.31

Romano adaptation, using conditions all time on or prior to cohort index

0.31

Patient discharge

0.30

Chest imaging

21

Covariates with highest standardized difference between cases and controls, captured 372-7 days prior to index

Slide22

Potential for

within-person counfounding

22

Slide23

Estimating residual bias

Same design + outcome definition

25 negative control exposures (drugs we believe do not cause AP)

25 corresponding nesting cohortsEvaluate consistency of ORs with the null

23

Slide24

Case-control residual bias

24

Slide25

Comparing to case-time-control

25

Slide26

Intermediaries

26

Exposure

Covariate capture

Outcome

Inter-mediary

Case-control

Exposure

Covariate capture

Outcome

Cohort method

Slide27

Conclusions

Case-control design is vulnerable to both between-person and within-person confounding

It combines the weaknesses of a cohort design with the weaknesses of a self-controlled design

Both designs are therefore expected to have better performanceAt equal costs (since the data is already collected)

Limited ability to adjust for confounders due to intermediaries

27

Slide28

OHDSI Symposium is coming!(October 18)

Posters?

OHDSI methods benchmark

Results of large set of methods on benchmark…

28

Slide29

Topic of next meeting(s)?

?

29

Slide30

Next workgroup meeting

Eastern

hemisphere:

June 283pm Hong Kong / Taiwan

4pm South Korea4:30pm Adelaide9am Central European time8am UK time

Western hemisphere: July

6

6pm Central European time

12pm

New York

9am Los Angeles /

Stanford

http://www.ohdsi.org/web/wiki/doku.php?id=projects:workgroups:est-methods