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EXMD504 > 2. Epidemiology of Cancer > Flashcards

2. Epidemiology of Cancer Flashcards

1
Q

what was the statement that received a lot of backlash from epidemiologists? why?

A

some scientists stated that most cancers are due to bad luck, i.e. from random mutations arising in normal cells

but epidemiologists know that most cancers are preventable

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2
Q

are rates of cancers constant over time?

A

no –> they change over time, can’t explain this with bad luck

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3
Q

can we explain the differences in cancer risk between different tissues? how?

A

YES - differences in cancer risk can be explained by the total number of stem cell divisions in those tissues

(i.e. correlation btwn lifetime risk and # of total stem cell divisions in a tissue)

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4
Q

can we explain differences in cancer risk between different people and between different populations? what does this mean?

A

NO - cancer is not due to bad luck bc cancer risk is due to population

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5
Q

what is R^2?

A

proportion of variation on Y axis that can be explained by variation on X axis

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6
Q

what is epidemiology?

A

study of patterns and causes of disease in a population

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7
Q

what is cancer surveillance?

A

burden of disease, incidence, and mortality trends

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8
Q

what is cancer risk?

A

assessing candidate etiologic factors

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9
Q

what is cancer prevention?

A

assessing efficacy and impact of screening, chemoprevention, etc.

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10
Q

what is cancer survival?

A

assessing prognostic factors, determinants of quality of life

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11
Q

2 ways to measure cancer occurence

A
  1. Number of cases
  2. Rate of cases
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12
Q

why is measuring the number of cases helpful?

A

look at number of new cases, new deaths –> for health system planning

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13
Q

what are the 2 types of rates we can measure?

A
  1. INCIDENCE RATE - new cancer cases in a population per person-years
  2. MORTALITY RATE - new cancer deaths in a population per person-years
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14
Q

what are the units of cancer rates?

A

cases per person-time

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15
Q

why is measuring cancer rates helpful?

A

accounts for population size and time frame so helpful for measuring risk and causality

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16
Q

how does cancer incidence change with age? why?

A

higher cancer cases in 65-69 year olds than 85-89 year olds but lower incidence rate

more 65-69 year olds than 85-89 year olds in general –> more diagnoses

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17
Q

how do incidence rates of cancer change in higher income countries?

A

higher incidence rates in higher income countries

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18
Q

how does age structure vary?

A
  1. varies over SPACE –> ppl live longer in higher income countries
  2. varies over TIME –> ppl are getting older
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19
Q

why do we need direct age standardization?

A

because age structure varies

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20
Q

how do we do direct age standardization?

A
  1. define a standard population age distribution
  2. calculate what cancer incidence rate WOULD HAVE BEEN if it had the same age distribution as the standard
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21
Q

what are the 2 standard population age distributions that we can use for direct age standardization? and their specific purposes

A
  1. 2011 census population in Canada –> to compare diff time points
  2. 1960 world population –> to compare diff countries
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22
Q

how do you calculate what cancer incidence rate WOULD HAVE BEEN if it had the same age distribution as the standard? ex. for 2011 census population (3 steps)

A
  1. calculate % of population in each age group in 2011
  2. calculate age-specific incidence rates of given year X
  3. multiply age-specific incidence rates by proportion of that age group in 2011 and sum over all age groups
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23
Q

after standardization:

A

all populations have the same standard age distribution so now we can compare populations with different age structures (time points or countries) to see differences in cancer risk

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24
Q

how do we see if the risk of cancer in Canada is increasing over time?

A

Canadian population has increased and gotten older so we expect more cancer cases but must adjust:
1) for changes in population size –> calculate crude incidence rate (# new cases divided by population size) –> this increases with time!
2) for changes in population age –> calculate age-standardized incidence rate (risk in 1992 if we were as old as we were in 2011 AND risk in 2019 if we were as young as we were in 2011)

this shows that rates are not changing much

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25
Q

what does ASIR stand for? how is it changing in Canadians?

A

ASIR = Age-standardized cancer incidence rates

number of cases increasing but incidence rate stays constant

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26
Q

what does ASMR stand for? how is it changing in Canadians?

A

ASMR = Age-standardized cancer mortality rates

number of mortalities increasing but mortality rate decreasing due to reduced lung/colorectal/breast cancer mortality

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27
Q

what do we have to consider to determine whether someone will survive cancer? why?

A

must adjust for non-cancer causes of death –> remove probability of dying from other causes

lets us compare diff cancer sites, etc in diff people

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28
Q

why are there different incidence rates of cancer in different countries?

A

unequal access to vaccines, treatments, screening

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29
Q

why is there a high liver cancer incidence rate in Mongolia and Egypt?

A

high Hep B prevalence in Mongolia due to unhygienic medical and dental practices

high Hep C prevalence in Egypt

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30
Q

with lung cancer and smoking, how does this demonstrate that cancer takes a long time to develop?

A

historically, cigarette consumption increased then 20 years later we saw a big increase in lung cancer mortality

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31
Q

how has stomach cancer mortality changed? why?

A

DECREASED!
- reduced salt consumption (bc ppl stopped using salting to preserve food when fridge was invented)
- reduced Helicobacter pylori prevalence

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32
Q

what are the 4 etiologic factors we assess when looking at cancer risk factors?

A
  1. causes of cancer
  2. why do only some ppl develop cancer
  3. what increases/decreases risk of cancer
  4. what epidemiological study designs allow us to discover the causes and risk factors of cancer
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33
Q

describe Ochsner’s assessment of lung cancer and smoking throughout history (6)

A
  1. lung cancer was very rare
  2. then WWI caused increased tobacco consumption
  3. thus Ochsner hypothesized that lung cancer was caused by smoking
  4. great depression caused reduction of cigarette consumption
  5. once lung cancer mortality rates were recorded, Ochsner found correlation btwn sale of cigarettes and incidence of lung cancer –> but this was not causation!
  6. then in 1950s, 2 major epidemiological studies were released to show correlation but smoking habits didn’t change
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34
Q

why is it not helpful to just look at whether lung cancer cases are in smokers?

A

this doesn’t tell you whether smokers are more likely to get lung cancer

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35
Q

what do analytical studies measure?

A

measure association btwn exposure and health outcome

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36
Q

what group do analytical studies require?

A

control group

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37
Q

what are the 2 types of analytical studies and examples

A
  1. EXPERIMENTAL –> clinical trial
  2. OBSERVATIONAL –> cohort, case-control, ecological (decreasing strength)
38
Q

what is causal inference?

A

looking at COUNTERFACTUALS

39
Q

what are counterfactuals?

A

what would happen if you go back in time and remove the risk factor?

40
Q

looking at counterfactuals from a study of lung cancer and smoking, what would you see if smoking caused lung cancer?

A

the counterfactual, absence of smoking, would not cause lung cancer

with smoking, would cause lung cancer

41
Q

looking at counterfactuals from a study of lung cancer and smoking, what would you see if smoking did not cause lung cancer?

A

the counterfactual, absence of smoking, would cause lung cancer

with smoking, would cause lung cancer

42
Q

are counterfactuals possible? why do we use them?

A

not actually possible but helpful to figure out the type of study

43
Q

can we observe causal effects? why?

A

NEVER –> can only infer

bc we cannot observe the counterfactual

44
Q

how can we infer causal effects for lung cancer and smoking?

A

compare outcomes in smokers and non-smokers to estimate causal effect

45
Q

how would you design a clinical trial to see if smoking leads to lung cancer?

A

randomization of 1 smoking group and 1 control group –> then control risk of lung cancer

BUT THIS IS NOT ETHICAL!

46
Q

what is the benefit of clinical trials for cancer research?

A

for cancer treatments and screening

47
Q

what are the 5 downsides of clinical trials for cancer research?

A
  1. unethical to randomize potentially harmful exposure
  2. can’t randomize exposure
  3. need large population
  4. long trial
  5. limited number of comparisons can be made
48
Q

why can we not randomize exposure for clinical trials for cancer studies?

A

exposure could be the environment –> can’t control this

and even if it were ethical to make someone smoke, can’t control whether someone smokes or not over long time

49
Q

why do we need a large population for clinical trials in cancer studies?

A

cancers have low incidence

50
Q

what is a case control study?

A

compare ppl with disease (cases) and without disease (controls) and see if they were exposed in the past

51
Q

what is the odds ratio/risk ratio?

A

measure of ASSOCIATION or correlation btwn exposure and outcome

52
Q

how do you calculate odds ratio/risk ratio?

A

(odds of exposure in CASES)/(odds of exposure in CONTROLS)

53
Q

what does it mean when RR = 1

A

exposed and unexposed ppl have same risk of disease

54
Q

what does it mean when RR > 1

A

exposed ppl have higher risk

55
Q

what does it mean when RR < 1

A

exposed ppl have lower risk

56
Q

is RR a measure of associaton or causation?

A

ASSOCIATION

57
Q

what is the example of Graham and Wynder’s case control study for smoking and lung cancer?

A

surveyed ppl with and without cancer about their smoking habits

58
Q

What did Graham and Wynder find in their case-control study? What was the criticism?

A

people who smoked had higher odds of having lung cancer

criticism bc retrospective study –> could be something else contributing

59
Q

are retrospective or prospective studies better?

A

prospective

60
Q

what is a cohort study? retrospective or prospective?

A

PROSPECTIVE

subjects have exposure now, then follow to see if they develop disease

61
Q

what do cohort studies use instead of randomization?

A

relies on natural variation in a population to see differences in exposure

62
Q

describe Doll and Hill’s cohort study and results

A

sent questionnaire to doctors about their smoking habits

followed doctors for 50 years to check for lung cancer deaths –> higher lung cancer mortality if heavier smoker

63
Q

what is the problem with observational data?

A

didn’t randomize subjects for confounding factors –> ex. environment may play a role

64
Q

describe the cohort study that looked at whether coffee causes cancer and the problem with the study

A

followed coffee drinkers to see if they develop cancer –> found INCREASED risk with more coffee

but confounding factors! coffee drinking strongly correlated with smoking –> cannot determine if coffee or smoking is causing the cancer

65
Q

how can we control for smoking being a confoundng effect? and the results

A

STRATIFICATION –> separate data into groups based on smoking habits to adjust for smoking

look only at ppl who don’t smoke –> no significant relative risk btwn coffee drinkers and non-coffee drinkers

look only at ppl who currently smoke –> no significant relative risk btwn coffee drinkers and non-coffee drinkers

therefore, coffee doesn’t not increase the risk of cancer mortality

66
Q

what is information bias? when does this happen?

A

error due to incorrect measurement of exposure and/or health outcome

ex. when ppl make mistakes in questionnaires

67
Q

5 general steps for determining that HPV causes cervical cancer?

A
  1. HSV was prime candidate
  2. found HPV DNA in cervical cancer tumours –> now need epidemiological evidence
  3. case-control study using NAH to detect HPV but method not sensitive enough!
  4. case-control study using PCR to detect HPV with very good sensitivity
  5. determined HPV does cause cervical cancer
68
Q

what did the HPV and cervical cancer show us?

A

that you need strong epidemiological studies, not just lab studies!

69
Q

describe cohort study to see if NSAIDS reduce the incidence rates of colorectal cancer and the method of measuring time

A

see if they develop colorectal cancer after using NSAIDS

used PERSON-YEARS –> denominator of how long you follow the women, total number of years across all women

70
Q

why did we need to control for age in the NSAIDS and colorectal cancer study?

A

some women had been using aspirin for >20 years so they were older than the other women

71
Q

what were the results of the NSAIDS and colorectal cancer study?

A

using aspirin for more years = lower risk of colorectal cancer

72
Q

after the observational cohort study, what did researchers do? and the results

A

did clinical trials –> randomized patients with and without aspirin, then see colorectal cancer rates

saw reduced cancer incidence and mortality –> therefore the observational data supports this experimental data

73
Q

what are 4 things we consider when assessing preventative measures?

A
  1. what exposures cause the most cancers?
  2. are risk exposures modifiable
  3. can we screen for cancer?
  4. does screening reduce cancer incidence/mortality?
74
Q

what is the population attributable fraction (PAF)?

A

the proportion of cancer cases that are attributable to a specific exposure

75
Q

what 2 things does PAF depend on?

A
  1. RR measured in cohort/case control study
  2. prevalence of exposure measured with surveys
76
Q

what happens to PAF if prevalence of exposure and RR are higher?

A

PAF is higher –> therefore more cancer cases caused by this exposure

77
Q

if RAF = 95% for lung cancer cases and smoking what does this mean?

A

95% of lung cancer cases are attributable to smoking

78
Q

how do we determine PAF using a graph?

A

Y = PAF
X = prevalence of exposure

with pre-defined curves for different RR values

if we know RR and prevalence of exposure, match up the point on the line to find PAF

79
Q

what is screening? who do we screen?

A

examining ASYMPTOMATIC people to identify disease/disease precursor before it becomes symptomatic

80
Q

do we screen to diagnose ppl?

A

no!! diagnosis only when they have symptoms

81
Q

what are 2 requirements for screening?

A
  1. must be preclinical –> undiagnosed, asymptomatic but detectable
  2. must be benefit of this early treatment over late treatment
82
Q

describe the study set-up for colorectal cancer screening

A

randomized control trial of flexible sigmoidoscopy screening

83
Q

why do we need a lot of ppl for screening studies?

A

all asymptomatic so very few will have cancer

84
Q

in screening studies do we follow them for long or short time? why?

A

follow for long time –> takes long time for screening to be effective

85
Q

describe the results of colorectal cancer screening study

A

at the beginning, more cases in intervention group bc we are actively looking for the cancer

then later, intervention goes below control bc they can remove the polyp and prevent cancer

86
Q

describe the results of ovarian cancer screening study

A

incidence is higher for intervention group bc the screening detects the actual cancer, not pre-cancer so maybe over-diagnosis

may be slightly higher mortality rate

87
Q

why is it more harmful to screen for ovarian cancer?

A

over-diagnosis –> maybe some ppl would have remained asymptomatic

but then they receive harmful cancer treatment

88
Q

what does the canadian task force on preventive health care determine about screening?

A

evaluates systematic review evidence to develop consensus recommendations for preventive interventions

89
Q

which 4 cancers is screening recommended?

A
  1. Colorectal cancer
  2. cervical cancer
  3. lung cancer (if heavy smoker)
  4. breast cancer
90
Q

which 2 cancers is screening not recommended?

A
  1. pelvic exams for non-cervical cancers
  2. prostate cancer

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