Anne Lang Dunlop, MD, MPH Emory University

1. Epidemiology Overview: Measures of disease occurrenceMeasures of associationStudy designScreening for disease Anne Lang Dunlop, MD, MPH Emory University

2. I. Measures of Disease Occurrence • Incidence: the rate of accumulation of new cases of a condition within a specified time period (i.e., the “risk” of disease within a time period) = No. of new cases in a time period/No. at risk during the time period • Useful for monitoring trends in disease onset and understanding etiology. • Prevalence:the proportion of a population with a specific condition at a single point in time = No. with disease/No. at risk for the disease • Useful for planning resourcesaround need for services and for monitoring progress in disease treatment.

3. Incidence Incidence quantifies the “development” of disease -- the most fundamental measure of disease frequency and leads to the development of the concept of risk (i.e., transition from non-diseased  diseased)

4. Calculating Incidence (or Risk) Incidence (or Risk)exposed= a/a + b Incidence (or Risk)unexposed= c/c + d

5. Incidence • Incidence provides an estimate of the probability (risk) that an individual will develop a disease during a specified period of time. • To accurately calculate cumulative incidence, we need to follow the entire populationfor the specified time interval. Often times, this does not fully occur. • Some people in the population will die from causes other than the outcome under study ( “competing risk” )

6. Prevalence The presence (proportion) of disease or condition in a population (generally irrespective of the duration of the disease) Prevalence: Quantifies the “burden” of disease. - Point Prevalence - Period Prevalence

7. “Point” Prevalence Number of existing cases at set point in time P = -------------------------------- Total population

8. Calculating Point Prevalence Prevalence = a + c/a + b + c + d = those with disease/those ‘at risk’

9. “Period” Prevalence Number of existing cases during a time period Pp = -------------------------------- Total population ► Includes existing cases before beginning of time period

10. “Period” Prevalence Example: Between June 30 and August 30, 1999, neighborhood A has: • average population of 1,600 • 29 existing cases of hepatitis B on June 30 • 6 incident (new) cases of hepatitis B between July 1 and August 30 So, Pp = (29 + 6) / 1600 = 0.022 or 2.2%

11. What is the relationship between incidence & prevalence? • Prevalence depends on incidence AND duration of the disease. • WHEN incidence rate (I) and duration of disease (D) have been constant over time: • P = ID / (1 + ID) • ID = P / (1 – P) • IF the prevalence of disease is low (i.e., < 0.10): • P = ID

12. What is the relationship between incidence & prevalence? Incident cases reflect etiologic factors alone… …while prevalent cases reflect factors related to the incidence of disease (etiological factors), AND factors related to the duration of disease (prognostic factors): • Subject’s constitution • Severity of disease • Access to care • Availability of treatment • Social support

13. Prevalence: Indicates those who should be targeted for control measures Helps to plan services Incidence: Study etiological factors Evaluate primary prevention programs Forecast need for services Uses of Prevalence & Incidence

14. Risk Ratio (a.k.a. Relative Risk): = Incidenceexposed/Incidenceunexposed = Riskexposed/Riskunexposed Estimate of strength of the individual risk factor. 1 is value indicating ‘no difference’. Risk Difference (a.k.a. Absolute Risk): = Riskexposed– Riskunexposed Estimate of the amount of risk attributable to that risk factor OR amount of disease that could be prevented in exposed individuals if exposure was eliminated. 0 is value indicating ‘no difference’. II. Measures of Association(between Exposure & Disease)

15. Calculating Measures of Assoc. • RR = Risk exposed/Risk unexposed • = (a/a + b)/(c/c + d) • AR = Risk exposed - Risk unexposed • = (a/a + b) - (c/c + d)

16. Number needed to treat (NNT): = 1 / Absolute risk (reciprocal of absolute risk) Answers the question: How many patients would have to be treated to decrease the expected number of cases by one? Conceptualizing Absolute Risk

17. PAR: Similar concept to attributable risk but applies to entire population Amount of disease could be prevented in the entire population if exposure was eliminated. = Incidence population - Incidence unexposed Example: The absolute reduction in incidence of lung cancer that could be prevented by eliminating smoking in a population. Population-Attributable Risk

18. Odds ratio: = Odds of Diseaseexposed/Odds of diseaseunexposed 1 is value indicating ‘no difference’. Used to approximate RR in case-control studies in which incidence measures cannot be calculated. Approximates RR if disease is sufficiently rare (< 10%). Measures of Association (cont’d)

19. Calculating Measures of Assoc. • OR = Oddsexposed/Oddsunexposed • = (a/b)/(c/d) • = ad/bc

20. Risk Ratio and Odds Ratio • If exposure is not related to disease then RR or OR= 1 • If exposure is positively related to disease (risk factor) then RR or OR> 1 • If exposure is negatively related to disease (protective factor) then RR or OR< 1

21. III. Types of Study Designs • Research designs are the rules that govern the process of collecting and arranging data for analysis • Choice of design is based on multiple considerations: speed, cost, data available • Each research study design has advantages and disadvantages • Type of analysis used varies by research design

22. Cross Sectional Survey • Surveys a population at a single point in time • e.g., prevalence of smoking among high school students; knowledge, attitudes, health practices of heterosexual women and HIV transmission • ADVANTAGES: Useful for hypothesis generation, fairly quick and easy to perform • DISADVANTAGES: Do not provide temporal relationship between risk factor and disease, shows association but not causality, not good for hypothesis testing, selection bias (e.g., selects for longer lasting diseases rather than rapidly fatal illnesses)

23. Case Control Studies • Select cases and controls by outcome (dz or no dz) and then compare frequency of exposure to risk factors for disease • Eg., babies with birth defects vs. babies born in same hospital, same birth date, same sex and race, same hometown, mother with similar age and measure prenatal care factors (nutrition, etc.) • ADVANTAGES: fairly quick and easy; can study many risk factors; good for rare diseases • DISADVANTAGES: only relative measure of odds is obtained rather than absolute risk; recall bias; selection of controls difficult; temporal relationships unclear; can study only one disease outcome at a time

24. Case-Control Studies •  Begin with sample of “Cases and Controls” •  Start with Disease status, then assess and compare Exposures incases vs. controls.

25. Study Design Disease (Outcome) _ + + Exposure (Risk Factor) _

26. CASE-CONTROL STUDIES • Bottom line: • Only cohort studies (including clinical trials) can yield incidence and relative risk. • The odds ratio, (e.g., from a case-control study) will always be greater than the relative risk. For rare diseases, the odds ratio will be close to the relative risk.

27. CASE-CONTROL STUDIES Sample Population

28. CASE-CONTROL STUDIES • BIAS! • Selection • & • Information

29. Cohort Studies • Select a group for study and follow that group over time; defined on basis of exposure and followed for outcomes • ADVANTAGES: can obtain a true (absolute) measure of risk; can study many disease outcomes; good for rare risk factors; can be retrospective (collect outcome data in present time from an assembled cohort with historical risk factors OR prospective • DISADVANTAGES: time consuming, costly, can study only the risk factors measured at the beginning; can be used only for common diseases; may have losses to follow up

30. Cohort Studies • Begin with sample  “Healthy Cohort” (i.e., subjects without the outcome yet) • Start with Exposure status, then compare subsequent disease experience in exposed vs. unexposed.

31. Study Design Disease (Outcome) _ + + Exposure (Risk Factor) _

32. Cohort Studies • Cohort Study • Key Point: • Presence or absence of risk factor is determined before outcome occurs.

33. Cohort Studies • Prospective: Outcomes have not yet occurred as study begins. • Retrospective: Outcomes have already occurred as the study begins. e.g., finding a trove of medical records allowing you to follow a cohort born in 1880 to death

34. Cohort Studies • Fixed Cohort X = outcome x Relative risk = (2/3)/(1/3) = 2.0 (+) x Exposure (-) x

35. Randomized Controlled Trial • Patients enrolled and then randomly assigned to intervention or control group with measurements at baseline and after administration of intervention or placebo/non-experimental intervention • ADVANTAGES: best for evaluating treatment interventions, most control over study factors • DISADVANTAGES: time-consuming, costly; only studies factors controlled by investigator; dropouts and therapy changes limit study; limited generalizability; often unethical to perform at all

36. Experimental Trial: • A trial is a type of cohort study, in that we follow a group that has yet to develop the outcome of interest. • Key Point  In a trial the investigators assign the “exposure” (i.e., the treatment).

37. A trial is a type of cohort study, in that we follow a group that has yet to develop the outcome of interest. • Key Point  In a trial the investigators assign the “exposure” (i.e., the treatment of intervention).

38. Randomized, Blinded Trial • (The Gold Standard) • Main Purpose: • Compare Treatments

39. FIXED COHORT X = outcome x 1/3 vs. 2/3 Med A x x Med B start end

40. IV. Screening for Disease • Screening:The application of a disease-detection test to people who are as yet asymptomatic. • Purpose:To classify individuals with respect to their likelihood of having a particular disease in order to lower morbidity and mortality of the disease in a population. ► Screening procedure itself does NOT formally make the diagnosis of disease.

41. Screening for Disease • “Unlikely” referred to next screening cycle • “Likely” further testing for diagnosis yes no referred to next treatment screening cycle

42. Screening for Disease Primary requirements for screening: 1) Early detection of disease leads to a more favorable prognosis due to early treatment, as compared to delayed treatment. 2) Pre-clinical disease left untreated typically progresses to clinically-evident disease (e.g. no spontaneous regression).

43. Screening for Disease Primary requirements for screening (cont’d): 3) The treatment for the disease in the preclinical or early symptomatic phase should offer benefits related to cost-effectiveness and quality of life. 4) Prevalence of pre-clinical disease should be relatively high among those screened.

44. Diseases for which screening has been recommended • Cervical cancer • Breast cancer • Prostate cancer • Colon cancer • Diabetes • Hypertension

45. Screening for Disease “PRICE” OF SCREENING: 1) Financial - may be very costly if screening is spread out over an entire population. 2) Anxiety - Individuals may have to be screened more often or may be troubled psychologically by anticipation of screening, procedure, or results. 3) Some morbidity occurs - both in terms of the initial screening procedure, and subsequent procedures. 4) Creation of “lead time” morbidity.

46. Natural History of Disease Age of Individual 20 30 40 45 50 55 60 Birth Exposure Cells Screened Symptom Death Neoplasia Exfoliate Diagnosis Diagnosis

47. Natural History of Disease Age of Individual 20 30 40 45 50 55 60 Birth Exposure Cells Screened Symptom Death Neoplasia Exfoliate Diagnosis Diagnosis Total Pre-Clinical Phase (TPCP) TPCP: Begins at the initiation of disease; ends when the disease is clinically manifested (25 years in this example)

48. Natural History of Disease Age of Individual 20 30 40 45 50 55 60 Birth Exposure Cells Screened Symptom Death Neoplasia Exfoliate Diagnosis Diagnosis Detectable Pre-Clinical Phase (DPCP) DPCP: Begins when screening test is able to detect disease; Ends when disease is clinically evident (10 years)

49. Evaluating Screening Tests Characteristics of a screening test: • Validity – the extent to which the test distinguishes between persons with and without the disease. High validity requires: • High Sensitivity • High Specificity • Performance (Yield) • Positive Predictive Value • Negative Predictive Value • Reliability • Cost, invasiveness, and discomfort

50. Validity of a Screening Test How do we judge the usefulness of a test? • How often is the test result correct for persons in whom the disease is known to be present? SENSITIVITY • How often is the test result correct for persons in whom the disease is known to be absent? SPECIFICITY Sensitivity & Specificity are measures of test function. • Independent of disease prevalence. • If a test is NOT sensitive, it will fail to detect disease in some diseased subjects. FALSE-NEGATIVE • If a test is NOT specific, it will falsely identify disease in those without the disease. FALSE-POSITIVE