The document discusses measuring disease processes and outcomes. It describes the induction period as the time from causal exposure to biological onset of disease, and the latent period as the time from biological onset to detection. It notes that the timing of disease processes and detection can vary between individuals, and discusses how this relates to measures like length bias and lead time bias. The document also defines epidemiological measures such as prevalence, incidence, risk, and rates.

1. Measures – measuring diseases
• Disease process and measuring disease
– Induction period = time from causal action to
biological onset
– Latent period = time from biological onset to disease
detection
Biologic onset Detectable by
screening
Symptoms
develop
DeathCausal action

2. Measures – measuring diseases
• Disease process and measuring disease
– Timing of disease process may differ between
individuals
– Timing of detection may differ between individuals
Biologic onset Detectable by
screening
Symptoms
develop
DeathCausal action

3. Measures – measuring diseases
Biologic onset Detectable by
screening
Symptoms
develop
DeathCausal action
Biologic onset
• Disease process and measuring disease
– Timing of disease process may differ between
individuals
Detectable by
screening
Symptoms
develop
Death
Causal action
A
B
JC: mention length bias

4. Measures – measuring diseases
• Disease process and measuring disease
– Timing of detection may differ between individuals
Biologic onset Detectable by
screening
Symptoms
develop
DeathCausal action
Biologic onset Detectable by
screening
Symptoms
develop
DeathCausal action
A
B
JC: mention lead time bias

5. Measures – measuring diseases
• Defining disease outcome for a study
– Have to consider underlying disease process and
potential variations in that process
– Have to consider how disease is being detected
• This will influence what your measure of
disease is capturing

6. Measures – measuring diseases
• Example: prevalence of cancer (proportion with
disease at a particular time) will miss cases of
aggressive cancers

7. Epidemiologic measures
• Prevalence vs. incidence
– Prevalence = proportion of the population with a
disease
– Incidence = frequency of development of new cases
of disease in a population
• New case is usually the first occurrence of a
disease for a non-diseased person

8. Epidemiologic measures
• Risk vs. rate
• Risk = the probability of developing disease over a
specified time period
– Population measure that is often interpreted at the individual
level
– Must specify the time period for the risk to be meaningfully
interpreted (X-year risk)
– Example: 10 year risk of mortality among men diagnosed with
prostate cancer is 0.1 or 1/10 men diagnosed with prostate
cancer die within 10 years

9. Epidemiologic measures
• Risk vs. rate
• Rate (average) = average change in disease status per
unit of time over a time period relative to the size of the
candidate population (incidence density)
• Example: There are 78 new cases of lyme disease per
100,000 population per year in CT (estimated in 2008)
• Interpreted at population level
• A rate, so time is in the denominator

10. Epidemiologic measures
• Risk vs. rate
• Rate (instantaneous) = the instantaneous potential for
change in disease status per unit of time at time t
relative to the size of the candidate (i.e., disease-free)
population at time t (hazard)
• The instantaneous rate (hazard) of lyme disease on
August 31, 2008 in CT is ?
– Instantaneous rates cannot be directly calculated from
epidemiologic data because they are defined for an infinitely
small time interval
– We can estimate average rates for smaller time intervals when
we have sufficient data