Biostatistics Case Studies 2014

1. Biostatistics Case Studies 2014 Session 3: Research Study Designs I Youngju Pak, PhD. Biostatistician ypak@labiomed.org

2. Type of Research Study Designs • Observational Study : Researchers do not attempt to influence subjects or surroundings. The goal is to OBSERVE/COLLECT data on characteristic of interests w/o influencing subjects • Experimental Study : Researchers deliberately influence the course of events & investigate the effect of the treatment on selected population of subjects

3. More specific types of observational studies • Observation Studies • Ecological Studies : Utilize population level data. • e.g. Total cigarette consumptions and lung cancer prevalence by different countries • Case Reports / Case Series • Single subject or case • Simple description of series of individual case • e.g., CDC and prevention Morbidity and Mortality Week Reports(MMWR) of Pneumocystis pneumonia in previously healthy, homosexual men (LA,1981) (http://www.cdc.gov/mmwr/preview/mmwrhtml/june_5.htm)

4. More specific types of observational studies cont. • Cross Sectional: Single time point studies that define a population at a specific time point, may unsuitable for rare disease • Prevalence or Incidence of disease or other characteristics • National Health and Nutrition Examination Survey on overweight and obesity in US. • Case-Control • Typically retrospective studies • Good for rare disease • Case/Control are collected by PI and retrospectively looking for risk factors/exposure • Prospective Longitudinal Cohort Study • Suitable for rare exposure • Large sample size are needed for rare disease • Risk factors/exposure are collected by PI and follow up study participants over time

5. How to make a better cross –Sectional Study • Sometimes it is hard to define denominator if it is an incidence study • Determining what to be studied is the most important things. • A disease or a disease condition or characteristics may be very difficult to define at a certain time point. eg, atherosclerosis is so common and its manifestations at time can be very subtle. • The definition of the condition and health characteristics under study SHOULD be standardized, reproducible, and feasible to apply for a larger scale study.

6. Advantage and Disadvantages of Cross-Sectional studies • Can avoid potential biases if it is truly population based sample • Short duration, less expensive for common diseases for a particular target population (e.g., workers in a given industry) • More expensive and time consuming compared with case-control studies particularly for rare diseases • Unsuitable for rare disease or for diseases of short duration (eg., influenza) • Potential bias due to non-responses (<80%) • Prevalence estimates are best derived from cross-sectional studies but factors associated with a disease or condition can be assessed by both cross-sectional and case-control studies. • Information you will need • Equivalence Margin • Non-Inferiority Margin(NIM) =1.5 for the IOP study • Assumed mean difference in change of IOP between two groups -> usually zero difference assumed but it is assumed 0.5 for the IOP study • SD of changes of IOP = 3.5 • α (usually set to 2.5%) since the confidence level of the confidence interval is (100-2 x α) %

7. Cross Sectional Examples • Jonas JB, et al. Diabetes mellitus in rural India.Epidemiology. 2010;21:754–755. • Hedley AA, Ogden CL, Johnson CL, Carroll MD, Curtin LR, Flegal KM. Prevalence of overweight and obesity among US children, adolescents, and adults, 1999-2002. JAMA 2004;291:2847-50. • Measure height and weight in National Health and Nutrition Examination Survey (NHANES) • Flegal KM, Graubard BI, Williamson DF, Gail MH. Cause-specific excess deaths associated with underweight, overweight, and obesity. JAMA 2007;298:2028-37.

8. Case-Control Studies • Observations regarding possible associations between a single outcome (usually a disease) and one or more hypothesized risk factors or Exposures • Well suited for studying – Rare diseases – Diseases with long latency periods • Generally quicker and less expensive than cohort studies No Disease Disease Exposed Non-exposed Exposed Non-exposed

9. Advantage and Disadvantages of Case-Control studies • Suitable for rare disease & Unsuitable for rare exposure • Multiple etiological factors can be studied simultaneously • Less expensive and time consuming • Associations with risk factors are consistent with other types of study if assumptions are met. • Do not estimate prevalence nor incidence • Relative risk can be indirectly measured by the odds ratio if the disease is rare

10. How to make a better Case-Control study? • Cases • Represents all patients who developed disease • Standardized selection criteria from well defined population • Can be NESTED in a larger cohort • Where? • Case registries • Admission records • Pathology logs • High participation rate • Controls • Represent “healthy” population without disease • No perfect control group exists • Standardized selection criteria from well defined population • Where? • General population • Neighborhood • Families • Hospitals

11. How to make a better Case-Control study? • All observation made using the same methods for cases & controls (consistency) • To avoid selection bias  the same hospital or family control • Avoid interviewer or recall bias  standardize data collection methods, train the interviewers • Consider cost & accessibility • To minimize confounding  Matched controls for age, sex, or other risk factors that are not interests of the study

12. Analyses for Case Control Studies Summarizing frequencies with a 2x2 Contingency Table • Odd Ratio ( [a/b]/[c/d]) is usually used to test • the association. • When a & c are very small(rare disease), • then OR ≈ RR • Chi-square or Fisher’s exact tests • If the risk factor (X) is continuous measure such as BMI, the a logistic regression model will be used to estimate OR as one unit change in X.

13. Prospective or Longitudinal Cohort Studies • Observations concerning associations between a given exposure and subsequent development of disease • Examine multiple outcomes for a single exposure • Directly calculate incidence of disease for each exposure group.

14. Concurrent vs. Non-concurrent Prospective Cohort Concurrent • Defined population is surveyed. • Identify group with supposed risk factor • Identify similar group without risk factor • Follow them forward in time • Compare incidence rates between groups Non-Concurrent • Define population with presence/absence of exposure ascertained in accurate, objective fashion in the past • Retrospective study since it is based on historical data • Surveyed in present: disease occurrence • Define incidence rates and compare between the two groups

15. Advantage and Disadvantages of Prospective or Longitudinal Cohort studies • More representative of cases than case-control (incidence) • Natural history of disease • Directly measure Relative Risk (RR) • Less bias than case-control • Firmly establish temporal relationship b/w exposure and disease but exposure must be IDENTIFIED and MEASURED at the initiation and should be followed during the study period. • Suitable for Rare exposure

16. Advantage and Disadvantages of Prospective or Longitudinal Cohort studies • Long follow-up and free-living population follow up is both difficult and expensive • Usually large scaled study • Extensive baseline data may need • Unsuitable for rare disease ( can have zero frequency in a 2x2 table if the sample size is not enough) • Still bias exists (eg., participant selection, exposure assessment, or loss to follow up)

17. How to make a better Prospective Cohort study • Exposed and non-exposed should be representative and well defined. • Non-exposed status should be maintained during the study period • Disease outcomes should be well defined prior to study and no changes during the study period • Standard criteria applied to both exposed and non-exposed. • Minimize loss to follow-up (>80%)

18. Analyses for Longitudinal Cohort Studies • Calculate incidence for the study period in exposed, unexposed, and test using Chi square or Fisher’s exact test. • Measure association with relative risk (or odds ratio) & 95% confidence limits • Life-tables (another way to say “survival analysis”) for “Time to Event” data • Regression models

19. Nested Case-Control studies • Select from prospective cohort study eg., Stored samples • Use baseline and follow up samples and data from newly occurring cases • Compare to matched or unmatched controls • Efficient for expensive/difficult to measure • Helps avoid selection and data collection biases • Need to have enough cases in the cohort • Need to store all the samples and data

20. Nested Case-Cohort studies • Similar to Nested Case-Control • Controls come from a subcohort sampled from the entire cohorts at baseline(t0), while controls for nested case-control are sampled from individuals at risk at the times(t1) when cases are identified. • Typically done when • Failure or event of interest is rare • Enormous resources to ascertain covariates values • Very difficult to analyze

21. Nested Case-Control vs Nested Case Cohort Example :

22. Prospective Cohort : Example Cancer incidence for 10% of US population in1973

23. Methods • SEER • Register cancer incidence for 10% of the US population in 1973 • Current incidence about 26% of the US population as of 2005 • Analyze registered breast cancer patients at age of 20-79 w/o previous cancer registered until Jan 1, 2002 from SEER. • Exclude: women with bilateral breast cancer & found at autopsy or the death certificate • Exposure: Irradiation from radiotherapy • Disease outcomes: Cause specific mortality • Primary : Death from Heart Disease: acute myocardial infraction, other ischaemic heart disease or other heart disease ( using ICD 9 code) • Secondary: Death from Lung Cancer

24. Results Why they didn’t compare radiotherapy group with no radiotherapy group?

25. Results

26. Nested Case-Control: Example • Risk Factors for Deep Vein Thrombosis and Pulmonary Embolism A population-Based Case-Control Study John A,Heit, MD; Marc D, Sliverstein, MD; etc, JAMA Internal Medicine 2000;160:809-815 • Deep Vein Thrombosis(DVT) occurs when a blood clot (thrombus) forms in one or more of the deep veins in your body. Deep vein thrombosis is a serious condition because blood clots in your veins can break loose, travel through your bloodstream and lodge in your lungs, blocking blood flow (pulmonary embolism). (resource: mayo clinic). • Venous Thromboembolism : Deep Venous Thrombosis & Pulmonary Embolism • Prevalence of DVT in US: new cases ( < 5 per 100,000 persons < 15 to 0.5% at age of 80 years. In general, 0.1%). Among these, 6% to 32% have PE based on severity of DVT.

27. Review points • Where case & control are obtained? Are they consistent ? • How were cases & controls defined? • Selection criteria? • Exclusion criteria? Why? • Any potential bias? • Minimize potential confounding?

28. Reference book