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Unit 2: Measures of Disease Occurrence

Unit 2: Measures of Disease Occurrence. Unit 2 Learning Objectives: Understand counts, ratios, proportions, and rates. Define, calculate, and interpret incidence. Understand the use of person-time denominators. Distinguish between cumulative incidence and incidence rate.

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Unit 2: Measures of Disease Occurrence

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  1. Unit 2: Measures of Disease Occurrence

  2. Unit 2 Learning Objectives: • Understand counts, ratios, proportions, and rates. • Define, calculate, and interpret incidence. • Understand the use of person-time denominators. • Distinguish between cumulative incidence and incidence rate. • Define, calculate, and interpret prevalence. • Distinguish between point and period prevalence.

  3. Unit 2 Learning Objectives (cont.): • Understand special types of incidence and prevalence measures. • Understand the interrelationship between incidence, prevalence, and duration of disease. • Differentiate the use of incidence and prevalence measures. • Become familiar with methods used in survival analysis.

  4. Assigned Readings: Textbook (Gordis): Chapter 3, pages 32-58 (Measuring occurrence of morbidity and mortality Chapter 6, pages 96-112 (Person years and survival analysis)

  5. Quantitative Measures of Health Status Measures of health status convey information about the occurrence of disease. They include: • Counts • Proportions • Ratios • Rates

  6. Counts • Simplest/most frequently performed measure in epidemiology • Refers to the number of cases of a disease or other health phenomenon being studied i.e. cases of influenza in Allegheny county in January, 2002 i.e. Number of persons involuntarily referred for psychiatric crisis intervention • Useful for allocation of health resources • Limited usefulness for epidemiologic purposes without knowing size of the source population

  7. Counts – Limited Interpretation New Cases Reporting Locationof DiseasePeriodPopulation City A 20 1998 100 City B 100 1998 1000 Annual Rate of Occurrence City A: 20 / 100 = 1 / 5 City B: 100 / 1000 = 1 / 10

  8. Proportions • Persons included in the numerator are always included in the denominator: A Proportion: -------- A + B • Indicates the magnitude of a part, related to the total. • In epidemiology, tells us the fraction of the population that is affected.

  9. Proportions - Example P = A / (A + B) = (1,400 / 11,050) = 0.127

  10. Proportions • Numerical value of a proportion: 0 to 1.0 • Linked to probability theory (i.e. risk of developing disease) • For ease of usage, can multiply a proportion by 100 to get a percentage • Example: p = 0.127 = 12.7%

  11. Ratios • Like a proportion, is a fraction, BUT without a specified relationship between the numerator and denominator • Example: Occurrence of Major Depression Female cases = 240 240 ------------------------ = ---- 2:1 female to male Male cases = 120 120

  12. Rates • A ratio in which TIME forms part of the denominator • Epidemiologic rates contain the following elements: • disease frequency (in the numerator) • unit size of population • time period during which an event occurs

  13. Rates – Example Calculate crude annual death rate in the US: Annual death count Crude death rate = ----------------------- x 1,000 Reference population (during midpoint of year) Death count in U.S. during 1990: 2,148,463 U.S. population on June 30, 1990: 248,709,873 2,148,463 Crude death rate = -------------- x 1,000 = 8.64 per 1,000 248,709,873

  14. Discussion Question 1 What does a crude annual death rate of 8.64 per 1,000 mean?

  15. Discussion Question 1 • It means that over the course of a year: • About 9 persons in 1,000 died. • About 864 persons per 100,000 died. • The risk of dying was about 0.9% (see below) • 2,148,463 • Crude death rate = -------------- = 0.0086 x 100 = 0.86% • 248,709,873

  16. Incidence The development of new cases of a disease that occur during a specified period of time in previously disease-free or condition-free (“at risk”) individuals.

  17. Incidence Incidence quantifies the “development” of disease --- Most fundamental measure of disease frequency and leads to the development of the concept of risk (i.e transition from non-diseased to diseased state) - Cumulative incidence (CI) (“Incidence proportion”) - Incidence rate (IR) (“Incidence density”)

  18. Cumulative Incidence (CI) PROPORTION of individuals who become diseased during a specified period of time (e.g. all new cases during 1998) Range: 0 to 1.0 Also referred to as “incidence proportion.”

  19. Cumulative Incidence (CI) No. of new cases of disease during a given period CI = -------------------------------------------------------------- Total population at risk during the given period Example: During a 1-year period, 10 out of 100 “at risk” persons develop the disease of interest. 10 CI = ----- = 0.10 or 10.0% 100

  20. Cumulative Incidence (CI) • To accurately calculate cumulative incidence, we need to follow the entire population for the specified time interval. Often times, this does not fully occur. • Cumulative incidence provides an estimate of the probability (risk) that an individual will develop a disease during a specified period of time.

  21. Cumulative Incidence (CI) • Keep in mind that over any appreciable period of time, it is usually technically impossible to measure risk. • This is because if a population is followed over a period of time, some people in the population will die from causes other than the outcome under study • The phenomenon of being removed from a study through death from other causes is referred to as ”competing risks”.

  22. Incidence Rate (IR) No. new cases of disease during a given period IR = ----------------------------------------------------------- Total “person-time” of observation Range = 0 to Infinity Since the number of cases is divided by a measure of time of observation, rather than people, this helps address the problem of competing risks.

  23. Incidence Rate (IR) What is person time? When we observe a group of individuals for a period of time in order to ascertain the DEVELOPMENT of an event…. - The actual time each individual is observed will most likely vary.

  24. Discussion Question 2 In a 2-year study of the development of disease X, why might the actual time each individual is observed vary?

  25. Discussion Question 2 • Because: • Subjects may be recruited at different times • Subjects may emigrate • Subjects may choose to leave study • Subjects may die • Subjects may get the disease we are studying

  26. Person-Time Each subject contributes a specific person-time of observation (days, months, years) to the denominator PersonFollow-up Time on StudyPerson Yrs. 1 <-------------------------------------> 2 2 <--------------------------------------D 2 3 <-----------------WD 1 4 <-------------------------------------------------------> 3 5 <-------------------------------------> 2 1995 1996 1997 1998 Jan. Jan. Jan. Jan.

  27. Person-Time PersonFollow-up Time on StudyPerson Yrs. 1 <-------------------------------------> 2 2 <--------------------------------------D 2 3 <-----------------WD 1 4 <-------------------------------------------------------> 3 5 <-------------------------------------> 2 1995 1996 1997 1998 Jan. Jan. Jan. Jan. Study Period: 3 Years Study Participants: 5 Person Years of Observation: 10 Average Duration of Follow-Up: 2.0 Years

  28. Incidence Rate (IR) No. new cases of disease during a given period IR = ------------------------------------------------------------ Total “person-time” of observation So, 1 case IR = ----------- = 1 case per 10 years follow-up 10 years Whereas, 1 case CI = ------------ = 0.20 = 20.0% 5 persons

  29. Comparison of IR and CI If we multiply by 0.2, the IR of 1 case per 10 years is equivalent to 0.2 cases per 2 years: which suggests a 20% risk of disease development within 2 years of follow-up. Whereas, the CI risk estimate of 20% (1 case per 5 persons) was based on a period of 3 years of follow-up. The CI calculation of risk of disease development differs from the IR calculation, in part, because it assumed that for incomplete follow-up, no cases of disease occurred.

  30. Discussion Question 3 Previously, we said that the incidence rate can range from 0 to infinity! How can this be?

  31. Discussion Question 3 Consider the following: McDonald’s shooting lasting 1/2 hour with 50 patrons in the restaurant. 29 survivors: at risk period of 1/2 hr = 14.5 personhrs. 21 deaths: at risk period of avg. 1/4 hr = 5.25 person hrs. =21 deaths / 20 person hours This translates to 919,800,000 / 100,000 person years Therefore, as time increases, IR approaches infinity.

  32. Incidence Rate (IR) NOTE: The selection of the time unit for the denominator is arbitrary, and is not directly interpretable: Example: 100 cases / person year can also be expressed as: 10,000 cases / person century 8.33 cases / person month 1.92 cases / person week 0.27 cases / person day

  33. Incidence Rate (IR) • Incidence rate: - Incidence density - Force of morbidity • Measure of the instantaneous rate of development of disease in a population

  34. Comparison of IR and CI In general: Risk estimates derived from IR and CI calculations will be similar when: • Follow-up loss is minimal • The disease of interest occurs infrequently. CI is most useful if interest centers on the probability than an individual will become ill over a specified period of time. IR is preferred if interest centers on how fast the new cases are occurring in the population.

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