Community Health

1
Community Health Epidemiology LMCC 2008 Review

• Part I Biostatistics Epidemiological Methods
• Part II Non-infectious Disease Epidemiology
• Part III Infectious Disease Epidemiology
• Dr. Allen Ross, M.D., Ph.D.
• Associate Professor
• Community Health
• Epidemiology

2
Part I Biostatistics Epidemiological Methods
3
Descriptive Statistics
4
Biological Variability

• All biological measurements are subject to
  variability
• It is important to be able to describe the
  occurrence of a biological factor e.g. height in
  a population
• The mean, median and mode are the three most
  important indices of central tendency
• For any symmetrical distribution mean, median and
  mode are equal

5
Mean

• Mean sum of the observed measurements
• number of observations
• The arithmetic average

6
Median

• Median that measurement below which half the
  measurements fall, the 50th percentile
• The length of hospital stay for nine patients
• 1, 1, 3, 4, 8, 9, 12, 13, 15
• the median is the middle number 8

7
Mode

• The most frequently occurring observation. If
  more than one value occurs frequently the
  distribution can be bimodal or multi-modal
• e.g. for values 1,4,3,1,2 the mode is 1
• for values 2,4,2,3,1,5,1 the distribution is
  bimodal as 1 2 occur most often

8

• Example
• To determine the average length of stay for six
  patients undergoing cholecystectomy. The length
  of stay in days for each patient is 1, 3, 2, 2,
  4, 5
• Qes. Calculate mean, median and mode
• a) Mean 122345 17/6 2.83
• 6
• b) Median 2.5 (the average of the 2 middle
  numbers for an even number of observations)
• c) Mode 2

9
The Normal Range

• Sometimes it is necessary to calculate a normal
  range e.g for hemoglobin levels, weigh-height
  charts
• This is usually done by calculating the mean /-
  2 standard deviations 95 under the curve
• Anything falling outside this is deemed abnormal

10
Problems with The Normal Range

• If the data is skewed these rules do not apply
• In medicine what is normal in the statistical
  sense may be abnormal clinically
• It is better to use a cut off that is clinically
  significant

11
Strength of Association

• Large relative risk or odds ratio
• Statistically significant (p value lt 0.05)

12
Hypothesis Testing

• Is the risk of leukemia associated with maternal
  irradiation in utero?
• Is the risk of a certain illness associated with
  a particular drug treatment in a previous illness
• Is the risk of death from lung cancer associated
  with smoking?

13
Hypothesis Testing

• The null hypothesis states there is no
  relationship between exposure and disease. RR 1
  or OR 1
• The alternative hypothesis states that there is a
  relationship between the exposure and the
  disease. RR 1 or OR 1

14
Type l Error (?)

• Stating that there is an effect when there really
  is not
• To mistakenly accept the experimental hypothesis
  and reject the null hypothesis
• ? is the probability of making a type 1 error and
  is p (usually lt.05)
• p is the probability of making a type 1 error

15
Type ll Error (?)

• Stating that there is not an effect or difference
  when there really is
• To fail to reject the null hypothesis when in
  fact H0 is false
• ? is the probability of making a
• type ll error
• 1- ? is also the power of a study

16
Testing for Significance using P-values

• The P - value indicates the likelihood of
  obtaining a result at least as extreme as that in
  the study by chance alone
• P value is set at lt 0.05 for medical research
• Dependent on the sample size
• Should not use P-value as a substitute for common
  sense
• Always determine if the association is clinically
  significant as well as statistically significant

17
Confidence Intervals

• Provides an interval range around the the odds
  ratio or the relative risk
• Represents the range within which the true
  magnitude of effect lies
• Usually set at the 95 level equivalent to Plt
  0.05
• Provides all the information of the P value
• If the interval does not contain 1 then the
  association between the variables is significant

18

• Example 1
• A study is designed to investigate the
  association between body fat and breast cancer.
  The results show a risk ratio of 6.0, however the
  95 confidence interval is (0.8 - 23.2).
• Since the interval includes 1, the results may be
  due to chance alone and the null hypothesis is
  accepted

19

• Example 2
• A study is designed to investigate the
  association between fluoride and decreased dental
  caries. The results show a risk ratio of 3.3 (95
  CI 2.2-4.0).
• Since the interval does not include 1, the null
  hypothesis is rejected and the result is found to
  be significant

20

• 95 CI (OR, RR) does not contain 1
• P lt 0.05
• Significant finding
• Reject the null hypothesis
• Outcome not do to chance
• 95 CI (OR, RR) contains 1
• P gt 0.05
• Not a significant finding
• Accept the null hypothesis
• Outcome may be do to chance

21
Question 1.

• The mean birth weight of first-born
  infants of 23 women who smoked more than one pack
  of cigarettes per day during pregnancy was 200 g
  lower than that of the first-born infants of 16
  women who never smoked. The difference was
  statistically significant at the 5 level (P lt
  0.05). This means which of the following?
• A) Smoking during pregnancy retards fetal growth
• B) The difference observed between mean birth
  weights was too large to have occurred by chance
  alone
• C) The difference observed between mean birth
  weights could have easily occurred by chance
  alone
• D) The number of patients studied was not
  sufficient to achieve a conclusive result
• E) Smoking during pregnancy does not influence
  fetal growth

22
Question 1.

• B) The difference observed between mean birth
  weights was too large to have occurred by chance
  alone

23
Question 2.

• Fifty known diabetics, all on insulin
  therapy, were compared with 50 non-diabetics. The
  diabetics showed a higher proportion of neurotic
  responses to a questionnaire (P lt 0.05). Which of
  the following could be ruled out as a viable
  explanation for this finding?
• A) Insulin therapy
• B) Chance
• C) Age
• D) Diet
• E) Medical complications of diabetes

24
Question 2.

• B) Chance

25
Question 3.

• As part of a routine physical examination,
  uric acid was measured for a 35 year-old male and
  found to be 7.8 mg/dl. The normal range for
  uric acid for that laboratory is 3.4 to 7.5
  mg/dl. If this individual is asymptomatic, which
  of the following is a viable explanation?
• A) His level is within 2 standard deviations of
  the mean for healthy individuals
• B) His level is below the 97.5th percentile for
  health individuals
• C) He is among the small proportion of healthy
  individuals who yield high serum uric acid
  readings on a given test
• D) The normal range was derived from a positively
  skewed distribution
• E) The normal range was derived from a negatively
  skewed distribution

26
Question 3.

• C) He is among the small proportion of healthy
  individuals who yield high serum uric acid
  readings on a given test

27
Question 4.

• The following regression equation was
  developed from a study of 16 newly diagnosed
  diabetics who received phenformin for a period of
  one year
• L -34
  0.29 W
• where L is the patients weight loss one
  year after therapy began and W is the patients
  initial weight. Which of the following could be
  deduced from this information?
• A) All patients last at least 34 pounds during
  the first year of therapy
• B) The regression line has a positive slope
• C) The correlation is very strong
• D) Patients who weighed more that others at the
  beginning of therapy lost more weight, on the
  average, during the first year of therapy
• E) The regression line has negative slope

28
Question 4.

• B) The regression line has a positive slope

29
Vital Statistics, Rates, Standardisations
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Incidence

• One of the most important rates in epidemiology
• Measures the rate at which people without a
  disease develop the disease during a specific
  period of time
• One of two common ways of comparing frequency of
  disease in populations (the second is prevalence)
• A measure of risk
• Can be described as cumulative incidence or
  incidence density

31
Cumulative Incidence

• New cases occurring in a given period x 10n
• Population at risk during the same time period
• Incidence Density
• New cases of a disease in a given period x 10n
• Total person-time of observation

32
Oral contraceptive and bacteriuria in a community
based studyNEJM 299536, 1978

• Population 2390 women aged 16-49 years who were
  free from bacteriuria
• 482 were OC users in 1973
• Second survey 1976 showed that 27 had developed
  bacteriuria
• Cumulative incidence 27 / 482 5.6

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Calculation of Person-years for Incidence Density
Cases Total time Subject A
------------------- 2
years Subject B -------------X
1 years Subject C
----------------------- 2 years Subject D
----------------------------------X 3
years x developed disease -- time
followed Incidence Density 2 / 8
25 per 100 person-years
34
A Prospective Study of post-menopausal hormones
and coronary heart diseaseNEJM 3131044, 1985
Population 32,317 postmenopausal women Cases of
coronary heart disease 90 Time period
105,786.2 person-years Incidence density 90 /
105,786.2 person-years
85.1 / 105 person-years
35
Issues in Calculation of Incidence

• The denominator should not include those not at
  risk but it is often impossible to exclude
  persons based on risk
• e.g. the incidence of endometrial cancer should
  be calculated excluding women s/p hysterectomy
• Incidence of endometrial cancer 1960-1973 was
  underestimated by 45

36
Prevalence Rate

• The second most common measure of disease
  frequency
• The proportion of persons in the population who
  have a particular disease at a specific point in
  time (point prevalence) or over a specified
  period of time (period prevalence)
• All cases during a given time period x 10n
• Population at risk during the same time period

37
Point vs. Period Prevalence

• Point Prevalence examines prevalence at a single
  point in time
• Period Prevalence examines prevalence over a
  longer period e.g. a year

38
Framingham Heart Study Prevalence Study to
determine the rate of cataract in the population
Population individuals 52 to 85 years of age
2477 persons examined 310 individuals with
cataract Prevalence number with cataract
total population
310/ 2477 12.5
39
Risk Ratio / Relative Risk

• RR estimates the magnitude of an association b/w
  exposure and disease and indicates the likelihood
  of developing the disease in the exposed vs.
  non-exposed
• RR of 1 indicates identical risk in the two
  groups gt1 increased risk lt 1 decreased risk
• RR used in cohort studies not case-control
  studies

40
The following table demonstrates the rates of
pellagra in two groups, males and females

• Risk of illness among females a/ (ab)
  46/1484 .031
• Risk of illness among males c/ (cd) 18/1419
  .013
• Risk Ratio Ie / Io .031 / .013 2.4
• The risk of pellagra in females is 2.4 times
  higher than the risk in males

41
Attributable Risk

• The absolute effect of the exposure or the excess
  risk of disease in those exposed vs. not exposed
• AR Ie - Io
• Ie is incidence in the exposed
• Io is incidence in un-exposed

42
Attributable Proportion

• The measure of the public health impact of a
  causative factor
• Also called the attributable risk percent
• AR / Ie
• Risk for the exposed group - Risk for the
  unexposed group x 100
• Risk for the exposed group

43
Death Rates and Rate Ratios from lung cancer by
daily cigarette consumption ( Doll and Hill
1951-1961)
44
Calculate attributable proportion in smokers of
1-14 cigarettes/day Identify the exposed group
rate 0.57 per 1000/ year Identify the unexposed
group rate 0.07 per 1000 / year calculate the
attributable proportion 0.57- 0.07 x 100
0.877 x 100 87.7 0.57 Therefore 88 of
lung cancers in smokers of 1-14 cigarettes/day
are attributable to smoking
45
Mortality Frequency Measures

• A mortality rate is a measure of the frequency of
  occurrence of death in a defined population
  during a specified interval
• Mortality Rate
• Deaths occurring in a given time period x 10n
• Size of the population among which the deaths
  occurred

46
Mortality Rates
Deaths occurring in a given time period x
10n Size of the population among which the deaths
occurred

• The denominator is usually the midpoint
  population
• There are multiple measures of mortality such as
  crude death rates, cause specific death rates,
  infant mortality rates, death to case ratio

47
Infant Mortality Rates

• The number of deaths in the first year after live
  birth about 10 million infants per year
  world-wide
• Globally the rates range from 5-6 deaths/1000
  live births to 150 deaths/live births
• High infant mortality is strongly linked to low
  birth weight (lt2500g) in rich countries
• In poor countries the association is complex
  other associations include GDP,
  education/literacy, availability of healthcare
  e.g facilities and personnel

48
Calculation of Infant Mortality Rates

• Example
• In 1988, 38,910 infants died and 3.9 million
  children were born.
• The IMR (number of deaths among children less
  than 1 year old)
• 38910 / 3.9 million
• 9.98 per 1000

49
IMR

• Japan, Sweden, Finland 5/1000 live births
• UK 8/1000 live
  births
• Afghanistan 150/1000 live births
• Canada 5/1000 live births
• African-Americans are twice as likely to die as
  white infants

50
Mortality Rates

• Crude mortality rates reflect both specific
  mortality rates and population composition
• Age-specific rates
• Age-adjusted or standardized mortality (a
  weighted mortality rate that accounts for
  population composition) is used when comparing
  regions or countries

51
Adjusted Mortality Rates

• Because Crude mortality rates reflect both
  specific mortality rates and population
  composition, 2 populations can only be compared
  when using age specific mortality rates and
  age-adjusted rates

52
Age-Specific Mortality Rates

• Age is a continuous variable that has a profound
  effect on mortality rates
• The mortality rates are listed for each age
  category. This allows direct comparison between
  states or countries
• Florida has a higher crude mortality rate than
  Alaska, yet when using age-specific rates the
  rates of death are noted to be similar
• It is always advisable to look at the mortality
  rates closely are they crude, age-specific or
  adjusted?

53
Age-Adjusted Mortality Rates

• It can be tedious to compare every age-specific
  rate across towns, countries etc.
• The age-adjusted rate is a mathematical way to
  apply the age-specific rates to a standardized
  population with a fixed numbers in each strata.
  This allows easy comparison of rates.

54
Cause-Specific Mortality

• Mortality rates for any specific disease may be
  stated for the entire population or any subgroup
• Deaths assigned to the specified disease per
  year x 105
• Population at mid-year
• Crude 1980 cancer mortality rate 416,481 /
  226,546,000 yr
• 
  183.8/105/year

55
Case-Fatality Rate

• The probability of death among diagnosed cases
• Deaths assigned to the disease in a certain year
  x 100
• Total cases of that illness in the same year
• e.g. In 1981-82 200 cases of Reyes syndrome were
  reported in the USA for individuals lt18 y and 70
  died. Thus, CFR 70 / 200 x 100 35

56
Proportionate Mortality Ratio (PMR)

• Proportion of the overall mortality that may be
  ascribed to a specific cause.
• PMR Deaths assigned to the disease in a certain
  year x 100
• Total deaths in the population in the same
  year
• e.g. PMR of heart disease was 37 in 1985 in the
  USA vs. 22 for cancer

57
Question 5.

• A study covering records of 150 consecutive
  unselected female patients with
  hyperparathyroidism at a hospital revealed that
  43 were under 45 years old and 107 were 45 years
  or older. The author concluded from these data
  that in women, the incidence of
  hyperparathyroidism is higher in the menopausal
  and postmenopausal age groups than it is in the
  pre-menopausal age groups.
• (a) this conclusion is correct
• (b) this conclusion is incorrect because the
  comparison was not based on proper rates
• (c) this conclusion is incorrect because there
  was improper interpretation of statistical
  significance
• (d) this conclusion is correct if the author had
  compared like with like
• (e) this conclusion is incorrect because
  observer bias may account for the results

58
Question 5.

• (b) this conclusion is incorrect because the
  comparison was not based on proper rates

59
Question 6.

• Suppose that you are investigating the
  possible association between cigarette smoking
  and cancer of the lung, and you obtain the
  following rates of death from lung cancer among
  Canadian males age 35 and over, related to
  smoking habits
• cigarette smokers - 2.0 per 1,000 per year
• non-smokers - 0.2 per 1,000 per year
• Based on the above observation, which of the
  following statements is correct?
• (a) the relative risk is 1.8 per 1,000 per year,
  and the attributable risk is 10.0
• (b) the relative risk is 10.0 and the
  attributable risk is 2.2 per 1,000 per year
• (c) the relative risk is 10.0 and the
  attributable risk is 1.8 per 1,000 per year
• (d) the relative risk is 0.1 and the
  attributable risk is 1.8 per 1,000 per year
• (e) none of the above

60
Question 6.

• (c) the relative risk is 10.0 and the
  attributable risk is 1.8 per 1,000 per year

61
Question 7.

• The following data were obtained from a
  study in which 200 renal cancer cases and 200
  controls were interviewed on their previous
  employment in a certain industry.
• 
  Renal Cancer Cases Controls
• Previously employed in this industry
  22 20
• No previous employment in this industry
  178 180
• Total
  200 200
  
• The observed difference in proportion in those
  previously employed in this industry between the
  two groups is not statistically significant at
  the 5 level. This means that
• (a) the study was not properly done
• (b) comparability of cases and controls has been
  confirmed
• (c) the observed difference might be
  statistically significant at the 1 level
• (d) the observed difference might be readily
  explained by sampling variation
• (e) none of the above

62
Question 7.

• (d) the observed difference might be readily
  explained by sampling variation

63
Question 8.

• The association between Pancreatic Carcinoma
  and Serum Factor 42 (SF42) is assessed in a
  case-control study with the results reported as
  Risk Ratio 2.87 (Plt0.01). The best
  interpretation of this statement is
• (a) There is no association between pancreatic
  carcinoma and SF42
• (b) SF42 causes pancreatic carcinoma
• (c) There is an association but is probably
  coincidental and therefore deserves no further
  consideration
• (d) There is evidence of an association between
  pancreatic carcinoma and SF42
• (e) It is impossible to draw any inference about
  association because the data were obtained from a
  case-control study

64
Question 8.

• (d) There is evidence of an association
  between pancreatic carcinoma and SF42

65
Question 9.

• The following table demonstrates the
  rates of cholera in two groups, males and
  females. How many more times likely are females
  at risk of getting cholera than males.
•  Yes
  No Total
• Female 40 60
  100
• Male 20
  40 60
• Note 40/60 0.67 40/100 0.4 60/100
  0.6 20/40 0.50 20/60 0.33 40/60 0.67
  0.4/0.33 1.21 0.67/0.6 1.12 0.50/0.33
  1.51 0.50/0.4 1.25 0.67/0.33 2.03
• A) 1.21
• B) 1.12
• C) 1.51
• D) 1.25
• E) 2.03

66
Question 9.

• A) 1.21

67
Question 10-14.

• A cohort is conducted to evaluate the
  relationship between exposure to solid foods at
  an early age and the development of asthma. In
  the study, 1000 infants who had solid food
  introduced before 4 months of age are compared to
  1,000 infants who had solid food introduced after
  6 months of age. The results are shown below.
• Introduction of Health Status
• Solid Food Asthma No Asthma Total
  
• Early 200 800
  1000
• Late 100 900
  1000
• Total 300 1700
  2000

68
Question 10.

• What is the risk of asthma in the group that had
  early introduction of solid foods?
• 0.10
• 0.15
• 0.20
• 0.25
• 0.35

69
Question 10.

• C. 0.20

70
Question 11.

• What is the risk of asthma in the group that had
  late introduction of solid foods?
• 0.10
• 0.15
• 0.20
• 0.25
• 0.35

71
Question 11.

• A. 0.10

72
Question 12.

• What is the risk ratio (early introduction of
  solids versus late) for the occurrence of asthma?
• 0.05
• 0.50
• 1.0
• 2.0
• 3.0

73
Question 12.

• D. 2.0

74
Question 13.

• The point estimate for the risk ratio (2) in the
  last question indicates that the risk of asthma
  associated with early introduction of solids is
• Decreased
• Increased
• Not affected
• Cannot be determined

75
Question 13.

• B. Increased

76
Question 14.

• The 95 confidence interval for the point
  estimate is 1.4 to 4.5. The correct
  interpretation of the results is
• A statistically a significant association exists
  between early introduction of solids and
  increased risk for the development of asthma at
  the level of P lt 0.05.
• A statistically a significant association exists
  between early introduction of solids and
  decreased risk for the development of asthma at
  the level of P lt 0.05.
• It can be concluded with 95 confidence that
  early introduction of solids is protective for
  the development of asthma.
• Breast feeding is an important intervention to
  prevent the development of asthma.
• The risk of asthma is not statistically
  significantly different between early and late
  introduction of solids foods at the level of P lt
  0.05.

77
Question 14.

• A statistically a significant association exists
  between early introduction of solids and
  increased risk for the development of asthma at
  the level of P lt 0.05.

78
Question 15-19.

• A cohort study is performed to evaluate the
  relationship between inflammation as measured by
  high C-reactive protein and the occurrence of
  myocardial infarction among women. In the study,
  500 subjects with high C-reactive protein and 500
  subjects with normal C-reactive protein are
  studied over a 20-year period.
• During the study, 50 of the women with high
  C-reactive protein and 15 of the women with
  normal C-reactive protein develop a newly
  diagnosed myocardial infarction.

79
Question 15.

• The incidence (per 10,000 person years) for
  myocardial infarction among women with a high
  C-reactive protein is
• 15
• 25
• 30
• 50
• 60

80
Question 15

• D. 50

81
Question 16.

• The incidence rate (per 10,000 person years) for
  a myocardial infarction for a person with normal
  C-reactive protein is
• 15
• 25
• 30
• 50
• 60

82
Question 16.

• 15

83
Question 17.

• The incidence rate ratio for myocardial
  infarction is
• 0.9
• 1.0
• 2.3
• 3.3
• 5.0

84
Question 17.

• D. 3.3

85
Question 18.

• The risk difference is
• 0.005
• 0.007
• 0.07
• 0.05
• 1.0

86
Question 18.

• C. 0.07

87
Question 19.

• The attributable risk percent is
• 25
• 35.5
• 50
• 70
• 90

88
Question 19.

• D. 70

89
Study Designs
90
Study Design

• Rank strongest to weakest study design
• Experimental study (strongest)
• Prospective cohort study
• Historical cohort study
• Case-control study
• Cross-sectional study
• Case-series
• Case report

91
Descriptive Studies

• Correlational Studies
• Case Reports Case Series
• Cross-sectional Surveys

92
Descriptive Studies

• Describe patterns of disease in relation to
  variables such as person, place and time
• Allow efficient allocation of health resources
• Less expensive than analytic studies because they
  use information already collected e.g. vital
  statistics, health survey data etc.
• Used to formulate research questions
• Can not use this study to test hypotheses !

93
Correlational/ Ecological Studies

• First step in investigating a possible
  exposure-disease relationship
• Can be done quickly and inexpensively using
  existing data such as
• vital statistics, hospital discharge data,
  product consumption
  data, environmental data

94
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95
Cigarette Smoking and geographical variation in
CHD mortality in the US (J Chronic Dis.
20769,1967)
96
The Relation of Alcohol to CHD and
Mortality Implication for Public Health Policy.
J Pub Health Policy 1198,1980
97
National Mortality Rates for Coronary Heart
Disease and Malignant Growths of the Intestine,
Excluding Rectum (WHO List 1969)
98
The Relation of Alcohol to CHD and Mortality
Implication for Public health Policy. J Pub
Health Policy 1198,1980
99
Analytic study showing that the relationship
between alcohol and CHD is not linear as
suggested by the correlational study
100
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101
Limitations of Correlational Studies

• Inability to link exposure with disease
• Inability to control for confounders
• Correlational data represent average exposure
  levels, not individual values
• Outliers can have a strong effect on the
  correlation coefficient
• May not reveal complex associations
• Can not prove an etiologic association !
• Ecologic fallacy

102
Case Reports

• Describe the experience of a single patient or
  group of patients with the same diagnosis
• The commonest type of study published
• Document unusual medical occurrences
• May lead to the identification of a new disease

103
Examples of Case Reports...

• 1974 3 cases of angiosarcoma of the liver among
  workers at a vinyl chloride plant
• 1980 5 cases of Pneumocystic carinii pneumonia
  (PCP) in young gay men
• 1981 case series of Toxic Shock Syndrome in
  young women
• 1981 Multiple cases of Kaposis Sarcoma in gay
  men

104
Toxic Shock Syndrome in The United States
105
Problems with Case Reports

• They can not test for the presence of a valid
  statistical association
• Based on the experience of only one or a few
  patients
• The presence of a risk factor may only be
  coincidental
• There is no comparison group

106
Case Series of Oral Contraceptive Use and
Hepatocellular Carcinoma (Age 26-35)
No.
107

• Case series shows that 4 X as many women with
  hepatocellular carcinoma are oral contraceptive
  users
• Because there is no comparison group it is
  impossible to determine if the rate of OCP use is
  any different from that in the healthy population
• No conclusion can be made from this study
  regarding the association between OCP and
  hepatocellular carcinoma

108
Cross-Sectional Surveys

• Also called Prevalence Surveys
• Exposure and disease are measured simultaneously
• Provides a snapshot of the population
• Examples include NHANES HHANES

109
Benefits of Cross-Sectional Surveys

• Used to provide information on prevalence of
  disease and health outcomes
• Allows administrators to assess health status and
  needs of the population
• Used to formulate hypotheses

110
Problems with Cross-Sectional Surveys

• Surveys gather prevalent not incident data
• Can not determine whether exposure preceded or
  resulted from disease chicken or egg dilemma
• Results will reflect determinants of survival as
  well as etiology
• Usually can not be used to test a hypothesis

111
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112
Cross-sectional survey of coronary heart disease
among white farm owners age 40-74 by occupational
physical activity.
113
The data show an association between inactivity
and CHD...Is this because inactivity leads to
heart disease or because CHD leads to inactivity?
114
Analytic Studies

• Descriptive data provide the first clues in the
  investigation of a cause-effect relationship,
  i.e. hypothesis generation
• Once the hypothesis is formulated the next step
  is to test it
• The analytic studies allow further analysis,
  testing and ultimately the rejection or
  acceptance of the hypothesis

115
Types of Analytic Studies

• Observational
• Case-control
• Retrospective cohort
• Prospective cohort
• Experimental
• Randomized Control Trial
• Meta-Analysis

116
Case-control Studies

117
Case-control Study

• Also called a retrospective study
• People diagnosed as having a disease (cases) are
  compared with persons who do not have the disease
  (controls)
• The purpose is to determine if the two groups
  differ by exposure

118
Case-control Study
PAST
PRESENT
Look for past exposure to the risk factor in
cases and controls
Select cases and controls
119
Why Use the Case-control Study Design?

• Chronic diseases e.g. cancer and CVD have long
  latency periods. A cohort investigation into
  chronic disease may take too long
• Rare diseases (low population incidence) can not
  be analyzed easily using cohort approach

120
Odds Ratio Relative Risk
Case Control
a
b
Yes No
Risk factor
c
d
RR a/(ab) c/(cd)
If a disease is rare (low prevalence), then a and
c will approach zero, leading to an approximation
of OR
ad bc
121
Analysis of Case-control Studies
Case Control
a
b
Yes No
OR ad bc
Risk factor
c
d
122
Case-control Study and the Odds Ratio

• Incidence can not be derived in a case-control
  study
• The odds ratio (estimate of relative risk) can
  only be calculated if
• The disease has a low incidence (5 or less)
• The control group is representative of the
  general population with respect to frequency of
  the exposure

123
Hepatoma (usual prevalence 1.5 per million)
Hepatitis B 500,000
1 case found (2x usual prevalence)
No hepatitis 500,000
0 cases (expected prevalence)
30 years follow-up
Cohort study approach Cost of study 20
million Results of study not significant
124
Hepatoma (usual prevalence 1.5 per million)
Case Control
40
30
Yes
Hepatitis B
20
10
No
Case-control study approach Cost of study
50,000 Results of study significant OR 2.67
125
The Benefits of Case-Control Design

• For rare diseases the case-control approach is
  the most cost efficient
• It is more likely to produce significant results
  when studying diseases of low prevalence
• Allows for the evaluation of a wide range of
  potential etiologic exposures
• Results available in a timely fashion

126
The Problems of Case-Control Design

• Disease and exposure have already occurred at the
  time of the study - creates a dilemma with
  temporal association
• Strong potential for bias
• Confounding
• Difficulties choosing appropriate controls

127
Matching

• If cases and controls are matched by usual
  confounders e.g. age, sex, SES, smoking, alcohol
  etc then these factors will be equal in both
  groups and will not confound the association
  between the variables
• But, it can be very difficult and expensive to
  find a perfect match for each case

128
Analysis of a Matched Case-control Study
Control Exposed Unexposed
Case Exposed Unexposed
b
a
d
c
OR b/c
129
Matched-pair case-control study of exogenous
estrogens and endometrial cancer NEJM.
2931164,1975.
Control Exposed Unexposed
Case Exposed Unexposed
113
39
150
15
OR b / c 113 / 15 7.5
130
Cohort Studies
131
Cohort Studies

• Also called
• Longitudinal studies
• Follow-up studies
• Incidence Studies
• Prospective Studies

132
Cohort Studies

• The second major type of observational study
• Individuals are followed on the basis of presence
  or absence of risk factors
• Individuals are then followed over time to
  determine if they develop a specific outcome /
  disease

133
Cohort Studies
100 with disease
Cohort free of disease 2000 participants
1,900 without disease
Now ---------------------------------------------
Future
134
Prospective Cohort Study

• Initiation of study occurs before occurrence of
  disease
• Groups of exposed and unexposed individuals are
  monitored over time to assess the development of
  disease
• The incidence of disease in both groups is
  compared
• Potential confounders documented

135
Prospective Cohort
Select cohort classify as to exposure to factor
Follow to see if disease develops
Present
Future
136

• One hundred children known to have been
  exposed to high levels of lead during the first
  12 months of life were followed for 15 years 40
  developed an affective disorder. A similar group
  of 100 children not exposed to lead were followed
  over the same time period. 5 of these children
  developed an affective disorder.
• What is the incidence of affective disorders
  among those exposed to high lead levels?
• What is the relative risk for those exposed
  compared to those with no exposure?

137

• Affective Disorder
• present
  absent
• exposed
• not exposed
• What is the incidence of affective disorders
  among those exposed to high lead levels?
• 40/100 40 or 0.40
• What is the relative risk for those exposed
  compared to those with no exposure?
• 40/100 ? 5/100 8

40
60
5
95
138
Advantages of Cohort Studies

• The temporal sequence between exposure and
  disease is clearly established
• Well suited for assessing the effects of rare
  exposures
• Incidence of disease can be calculated
• Can examine multiple effects of a single exposure
• True estimate of risk can be calculated
• Natural history of disease can be studied

139
Disadvantages of Cohort Studies

• Usually involve large numbers of individuals over
  many years, therefore expensive (average 10,000
  per participant)
• Subject to attrition (loss of follow up)
• Subject to outcome bias - knowledge of exposure
  can influence ascertainment of disease outcome

140
Nested Case-control Studies

• A case-control study can be inserted into a
  cohort study
• When enough individuals have developed the
  outcome of interest, they can be compared to
  controls
• This allows interim evaluation of the association
  between the variables

141
Intervention Studies
142
Intervention Studies

• Known as the clinical trial
• The gold standard in clinical research
• Similar to a cohort study in that individuals are
  enrolled on the basis of exposure
• Unlike cohort studies the exposure is allocated
  by the investigator
• The main difference between observational and
  intervention studies is that individuals have no
  control over the exposure they receive

143
Design...intervention

• Parallel
• patients are randomized to each of the
  intervention and non-intervention arms for the
  duration of the experiment
• Cross-over
• patients spend an equivalent amount time in the
  intervention and non-intervention arms
• Factorial
• suitable for studying the effects of more than
  one intervention
• especially suited for possibly synergistic
  interventions

144
Design...Parallel Intervention
145
Design...Cross-over
146
Design...Factorial
147
Types of Intervention Studies

• Therapeutic
• Determine the ability of an agent or procedure to
  diminish symptoms, prevent recurrence or decrease
  death from disease. The disease is already
  present e.g. most drug trials
• Simvastatin Study
• Preventive
• Evaluation of whether the agent or procedure
  decreases the development of disease in those
  free from disease e.g. most vaccine trials and
  behavior modification
• MR FIT Study

148
Issues With Intervention Studies

• Ethics
• The active assignment to a treatment or procedure
  means that the study must be ethical i.e. can not
  assign to treatments known to be harmful or
  withhold beneficial treatment
• Feasibility
• It may not be possible to do certain studies if
• the procedure is widespread (MVI and nurses
• in NHS)
• Cost
• 15 - 25 K per participant

149
Conducting a Clinical Trial

• Formulate the hypothesis
• Select participants random assignment, choose
  sample size
• The power is the ability of a statistical test to
  detect differences among comparison groups
• The greater the sample size, the greater the power

150
Efficacy vs. Effectiveness

• Efficacy is the ability of a treatment to work in
  the trial or study setting (in a
  volunteer/compliant study population with active
  follow-up)
• Effectiveness is the ability of the treatment to
  work under realistic circumstances. Takes into
  account patient compliance, acceptability of
  treatment and patient diversity

151
Allocation of Study Regimens

• Assignment to treatment groups should occur after
  the study population is chosen and informed
  consent obtained
• Randomization tables and computer generated
  randomization used most frequently
• Block randomization used when you wish to
  maintain equal numbers of e.g. women and men in
  each group
• Triple blinded vs. double blinded vs. single
  blinded trials

152
Block Randomization
Study population n1200 (100 women 1100 men)
100 women
1100 men
Randomization occurs after assignment into
blocks male and female
Drug A
Drug A
Drug B
Drug B
n50 n50
n550 n550
153
Reasons for Randomization

• Reduces bias - no selection, recall or
  interviewer bias should occur (double blinded)
• Reduces confounding (known confounders) - should
  have equal numbers of potential confounders in
  all groups if the sample size is big enough
• Randomization also reduces effect of unknown
  confounders

154
Analysis of Data

• Similar statistics used for cohort analysis
• Intention to treat (preserve random allocation,
  simulates real world experience)- determines
  effectiveness
• Explanatory only analyse those who actually
  take treatment - determines efficacy, but
  vulnerable to bias

155
Intention to Treat
Study population
Drug A 1000
Placebo 1000
500 compliant
500 non-compliant
1000 compliant
250 cured
250 cured
Intention to treat means that the cure rate for
Drug A is calculated as 250/1000 25 The cure
rate for placebo arm is 250/1000 25
Drug A has no effect
156
Explanatory
Study population
Drug A 1000
Placebo 1000
1000 compliant
500 compliant
500 noncompliant
250 cured
250 cured
Explanatory analysis means that the cure rate for
Drug A is calculated as 250/500 50 The cure
rate for placebo arm is 250/1000 25
Drug A is twice as effective as
placebo
157

• Important
• Analyses in the medical literature (drug trials)
  should always be analyzed and reported by
  intention to treat method
• Sometimes the explanatory method is used, however
  the investigators should also show the results
  analyzed by intention to treat

158
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159
Phases of Clinical Trials

• Phase 1Initial testing in humans following
  animal studies. Identify dose limiting
  toxicities, tolerated doses, describe
  pharmacology (metabolism, excretion)
• Phase 11 testing in subjects with disease to
  determine activity and therapeutic efficacy.
  Validate toxicity and dosage data
• Phase 111 Randomized trials for comparison

160
Post-licensing Evaluation

• Safety and efficacy of drug
• Disease surveillance
• Adverse effects

161
Experimental Studies

• Advantages
• intervention possible
• graded intervention if desired
• randomization
• truest test of causation
• minimization of bias
• high internal validity
• possible to examine multiple outcomes

• Disadvantages
• resource intensive
• time and cost
• compliance
• ethical issues
• possibility of type 1 and 2 errors remain
• conflicting results between RCT
• generalizability

162
Systematic Reviews Meta-Analysis
163
What is a Systematic Review?

• Systematic Review
• Based on protocol
• Involves critical appraisal
• Synthesis of the data
• Meta-analysis
• Statistical combination of data

164
Systematic vs. Narrative Reviews
165
Why do a Systematic Review?

• To examine the quality of the evidence
• To summarize the treatment benefit in a given
  therapeutic area provide the best estimate of
  its direction and magnitude
• To resolve discordance between trials
• To investigate reasons for the discordance

166
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167
Meta-analysis

• Statistical combination of the results of
  multiple studies, weighed by the inverse of the
  variance of the estimate in each study (larger
  sample sizes receive more weight)
• Dichotomous outcomes RR, OR
• Continuous outcomes Weighted mean difference,
  standardized mean difference

168
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169
Question 20.

• Radiologists have claimed that the survival
  rates after cancer surgery are improved by
  pre-operative radiation of the cancer. We plan a
  randomized clinical trial to perform the
  following comparison in operable patients. One
  group of patients will receive surgery
  immediately. The other group will receive a
  course of intensive radiotherapy for a month,
  followed by a month of recovery. At the end of
  the second month, surgery will be performed in
  those patients who are still operable. The
  results will be compared in those patients who
  received surgery alone versus who received
  radiotherapy plus surgery
• (a) the comparison between patients who received
  surgery alone and those who received radiotherapy
  plus surgery cannot be a comparable study because
  it is not possible to carry out a double blind
  study
• (b) the study achieved the comparison of like
  with like because random allocation was employed
• (c) the comparison is valid because it would be
  unethical to perform surgery on in-operable cases
  following the pre-operative radiotherapy
• (d) for valid comparison, the radiotherapy plus
  surgery group should include all the patients
  allocated to this regime, including those who
  became in-operable following the pre-operative
  radiotherapy
• (e) none of the above

170
Question 20.

• (d) for valid comparison, the radiotherapy
  plus surgery group should include all the
  patients allocated to this regime, including
  those who became in-operable following the
  pre-operative radiotherapy

171
Question 21.

• Epidemiologic studies of the role of a
  suspected causal factor of a disease may be
  observational or experimental. The essential
  difference between experimental and observational
  studies is that in experimental investigations
• (a) the study and control groups are equal in
  size
• (b) the study is a cohort study
• (c) the characteristics of interest are
  quantitative variables measured objectively
• (d) the investigator determines who shall be
  exposed to the suspected factor and who shall not
• (e) controls are used

172
Question 21.

• (d) the investigator determines who shall be
  exposed to the suspected factor and who shall not

173
Question 22.

• A double-blind study of a vaccine is one in
  which
• A) The study group receives the vaccine and the
  control group receives a placebo
• B) Neither observer nor subjects know the nature
  of the placebo
• C) Neither observer nor subjects know which
  subject receives the vaccine and which receives a
  placebo
• D) Neither the study group nor the control group
  knows the identity of the observers
• E) The control group does not know the identity
  of the study group

174
Question 22.

• C) Neither observer nor subjects know which
  subject receives the vaccine and which receives a
  placebo

175
Questions 23-32.

• A randomized, double-blind, placebo-controlled
  clinical trial is conducted to determine whether
  memantine, an NMDA antagonist, can reduce
  clinical deterioration in patients with
  Alzheimers disease. Among 252 patients
  randomized in equal numbers to memantine or a
  placebo, the groups were similar at baseline with
  respect to demographic characteristics and level
  of dementia. The study was 28 weeks, with 29
  experimental patients and 42 controls not
  completing the study. Based upon cognitive,
  functional, and behavioral assessment, 29 of the
  patients treated with memantine and 10 of
  controls demonstrated a predefined favorable
  clinical response. Serious adverse events
  occurred among 13 of patients on memantine and
  18 of controls.

176
Question 23.

• The similarity of treatment groups with respect
  to baseline characteristic most likely occurred
  because of
• Use of intention-to-treat analysis
• The placebo effect
• Use of randomization
• Use of blinding
• Use of informed consent

177
Question 23.

• C. Use of randomization

178
Question 24.

• One control in ten had a clinical response. This
  is best explained by
• Use of intention-to-treat analysis
• The placebo effect
• Use of randomization
• Use of blinding
• Use of informed consent

179
Question 24.

• B. The placebo effect

180
Question 25.

• Neither the patients no clinicians who evaluated
  them knew individual treatment assignments. This
  may be described as
• Use of intention-to-treat analysis
• The placebo effect
• Use of randomization
• Use of blinding
• Use of informed consent

181
Question 25.

• D. Use of blinding

182
Question 26.

• The risk of not responding clinically among the
  memantine patients was
• 0.10
• 0.29
• 0.71
• 0.79
• 0.90

183
Question 26.

• C. 0.71

184
Question 27.

• The risk of not responding clinically among
  controls was
• 0.10
• 0.29
• 0.71
• 0.79
• 0.90

185
Question 27.

• E. 0.90

186
Question 28.

• The risk ratio of not responding clinically among
  the patients treated with memantine compared to
  the corresponding reference risk among controls
  was
• 0.10
• 0.29
• 0.71
• 0.79
• 0.90

187
Question 28.

• D. 0.79

188
Question 29.

• The risk ratio of a serious adverse effect among
  patients treated with memantine compared to the
  corresponding reference risk among control was
• 0.13
• 0.18
• 0.72
• 0.82
• 0.87

189
Question 29.

• C. 0.72

190
Question 30.

• The results suggest that compared to with
  controls, patients treated with memantine have
• Better clinical response and fewer serious
  adverse effects
• Better clinical response but more serious adverse
  effects
• Worse clinical response but fewer serious adverse
  effects
• Worse clinical response and more serious adverse
  effects
• The same clinical response but few serious
  adverse effects

191
Question 30.

• A. Better clinical response and fewer serious
  adverse effects

192
Question 31.

• Although more controls than patients treated with
  memantine failed to complete the study, all
  patients were analyzed according to the original
  assignment. This best described as
• Use of intention-to-treat analysis
• The placebo effect
• Use of randomization
• Use of blinding
• Use of informed consent

193
Question 31.

• A. Use of intention-to-treat analysis

194
Question 32.

• Some patients may have enrolled with cognitive
  deficits great enough to impair their
  understanding of the purpose and risk of the
  study. In these instances, caregivers represented
  the patients in accepting the risks and benefits
  of the study. This process is best described as
• Use of intention-to-treat analysis
• The placebo effect
• Use of randomization
• Use of blinding
• Use of informed consent

195
Question 32.

• E. Use of informed consent

196
Question 33.

• A study is conducted in a country to evaluate the
  prevalence of type 2 diabetes
• Case-control study
• Cohort study
• Clinical trial
• Cross-sectional survey
• Meta-analysis
• Ecologic study

197
Question 33.

• D. Cross-sectional survey

198
Question 34.

• Patients with newly developed breast cancer are
  asked about previous dietary intake or fat. Their
  responses are compared to patients admitted to
  hospital for plastic surgery procedures.
• Case-control study
• Cohort study
• Clinical trial
• Cross-sectional survey
• Meta-analysis
• Ecologic study

199
Question 34.

• A. Case-control study

200
Question 35.

• Two hundred patients with rheumatoid arthritis
  are randomly assigned to 6 months of a new
  anti-inflammatory drug or standard care
• Case-control study
• Cohort study
• Clinical trial
• Cross-sectional survey
• Meta-analysis
• Ecologic study

201
Question 35.

• C. Clinical trial

202
Question 36.

• A study evaluates the per-capita intake of
  calcium and the prevalence of hypertension in 8
  different countries.
• Case-control study
• Cohort study
• Clinical trial
• Cross-sectional survey
• Meta-analysis
• Ecologic study

203
Question 36.

• F. Ecologic study

204
Question 37.

• The results of several case-control studies of
  the association between exposure to rug shampoo
  and the development of Kawasaki disease are
  examined to produce a summary conclusion.
• Case-control study
• Cohort study
• Clinical trial
• Cross-sectional survey
• Meta-analysis
• Ecologic study

205
Question 37.

• E. Meta-analysis

206
Question 38.

• In 1945, 1,000 women were identified who
  worked in a factory painting radium dials on
  watches. The incidence of bone cancer in these
  women up to 1975 was compared to that of 1,000
  women who worked as telephone operators in 1945.
  Twenty of the radium dial painters and four of
  the telephone operators developed bone cancer
  between 1945 and 1975. This study is an example
  of a
• (a) cohort study
• (b) experimental study
• (c) clinical trial
• (d) cross-sectional study
• (e) case-control study

207
Question 38.

• (a) cohort study

208
Question 39.

• A hypothetical study of 500 patients
  hospitalized with a pathological confirmed
  diagnosis of a Ca breast. For each case a
  control patient without cancer of the breast was
  selected and matched by race and five year age
  group. Both cases and controls were provided
  with a questionnaire which included a question on
  history of x-ray exposure. This is an example
  of
• (a) an experimental study
• (b) a cohort study
• (c) a case control study
• (d) a clinical trial
• (e) a cross sectional study

209
Question 39.

• (c) a case control stu