Study Design Outline of Topics

1. Study DesignOutline of Topics • Individual vs group as unit of observation • Study base or cohort • Cohort design • Cross-sectional design • Case-control design • 3 ways to sample controls • Primary & secondary study bases • Incident versus prevalent disease • Retrospective versus prospective – what matters Epi Methods, Fall 2009

2. Human Subjects Studies Unit of observation Group (eg, geographic area) Individual Cohort Cross-sectional Case-Control Clinical Trial Ecological Studies

3. 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 ways of sampling the disease experience of a study base or cohort

4. Concept of the Study Base • The study base is the population who experience the disease outcomes you will observe in your study • In a cohort study, the study base is an explicitly defined cohort • In a cross-sectional study, the study base is a hypothetical cohort sampled at one point in time • In a case-control study, the study base is the cohort, either explicit or hypothetical, that gave rise to the cases

5. 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 sampled • Consider the timing of measurements relative to the time period of the experience of the Study Base

6. 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

7. Cohort study design D = disease occurrence; arrow = losses to follow-up Minimum loss to follow-up (1%)

8. 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

9. 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 likelyto leave? ? ? ? ? ? ? ?

10. 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

11. 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) Two Cohort Studies of HCV/HIV Coinfection and Risk of AIDS

12. Cross-Sectional Study Design

13. Cross-Sectional Design • Measures prevalence of disease at one point in time. Two types: • Point prevalence: Do you currently have a backache? (study takes 4 months) • Period prevalence: Have you had a backache in the past 6 months? (study takes 4 months) • Main weakness: Cannot determine whether putative cause preceded the disease outcome • Also: Cannot distinguish factors associated with disease (incidence) from factors associated with survival with disease (prevalence)

14. Case-Control Design: Concept of the Study Base • Study Base = the population (or 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

15. Case-Control Key Concept #1 • Think of the selection of cases and controls as occurring from an underlying cohort (or study base)

16. 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.

17. Cohort study design D = disease occurrence; arrow = losses to follow-up Given that all the cases are diagnosed, how would you sample controls from this cohort for a case-control study?

18. 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

19. 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 follows that a subject who is a control at one time may become a case later in time.

20. 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. 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 Apr 8. [Epub]

21. Counterintuitive Idea #1 • Individual persons can be controls at one point in time and cases at another time

22. Case-cohort design: sample baseline of cohort

23. Example of case-control study with baseline sampling of a cohort (primary study base) Abstract 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. Comparing extreme quartiles, insulin [hazard ratio (HR)q4–q1, 1.73; 95% confidence interval (CI), 1.16–2.57; Ptrend = 0.005], waist circumference (HRq4–q1, 1.82; 95% CI, 1.22–2.70; Ptrend = 0.001), and free IGF-I (HRq4–q1, 1.35; 95% CI, 0.92–1.98; Ptrend = 0.05) were each associated with colorectal cancer incidence in multivariate models… Insulin, Insulin-like Growth Factor-I, Endogenous Estradiol, and Riskof Colorectal Cancer in Postmenopausal WomenGunter, et al. Cancer Res 2008;68(1):329–37

24. Case-control design using prevalent controls atend of follow-up.

25. 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

26. Incidence Density Sampling in a Dynamic Cohort (e.g., a primary study base: San Francisco County) Primary Study Base New residents D Incidence-density sampling in a specified population with new subjects entering

27. 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 registry data. …Controls were a random sample of persons identified by random digit dialing… resided in the same six counties as the casesat 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 NonsteroidalAntiinflammatory Drugs and Non-Hodgkin Lymphoma: A Population-based Case-Control Study.Am J Epidemiol 2006; Sept 1, 164:497-504.

28. Definition of a Primary Study Base • Primary Study Base = population that gives rise to cases that can be defined before cases appear by a geographical area or some other identifiable entity like a health delivery system or a research cohort study • Our previous examples of an “underlying cohort” for a case-control study were primary study bases

29. Definition of a 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

30. 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

31. Secondary Study Base • Example: glioma cases seen at UCSF • Difficult because referrals come from many areas • 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

32. 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

33. 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

34. 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)

35. 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)

36. Example of 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 cases at UCSF, secondary study base.

37. Case Control Key Concept #4 • Incident sampling of both cases and controls is preferable to prevalent sampling

38. “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.

39. A Comment on the Terms Prospective and Retrospective • Prospective and retrospective refer to when the study is done in relation to the study base experience (text uses concurrent and non-concurrent) • But the key issue for the strength of the design is when the measurements were made in relation to the study base experience. Accuracy of the measurements better if done prior to outcome.

40. “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

41. Case Control Key Concept #5 • Strength of design rests on accurate measurements made prior to the outcome, not whether it is cohort or case-control sampling

42. Example of Strong Case-Control Design • Kaiser Research Division 1990 • Question: Does screening sigmoidoscopy prevent colon cancer deaths? • Design choices • Prospective cohort: incidence about 100 deaths per yr but only about 15% of colon cancers detectable by sigmoidoscopy—10 to 20 yrs • Retrospective cohort: Kaiser members in 18-year period--100,000’s of records to review • Case-control

43. 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) Blinded review of prior 10 years of medical records Predictor=screening sigmoidoscopy 8.8% of cases vs. 24.2% had prior screening sigmoidoscopy Case-Control Design A case-control study of screening sigmoidoscopy and mortality from colorectal cancer. Selby et al., NEJM 1992; 326:653-7

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