Flashcards in Epi Class 3 Deck (15):

1

## Why use age-adjusted rates when comparing two populations?

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A comparison of crude mortality rates (total mortality rate for a population) may be inaccurate due to different population age structures.

• Age standardization removes the effect of age among populations being compared.

• Population rates can be compared if they have been adjusted to the same standard population.

• (Note that the summary rate created by age adjustment is “fictional” – that is, not the true experience of the population.)

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## Direct Age Adjustment (Age Standardization)

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*PREFERRED METHOD. Can only be used when we know what age people died*

What is the expected number of events in the standard population given the rate in the study population?

• Use when comparing large, well-defined study populations.

• Method: Apply age-group-specific mortality (or morbidity) rates to the standard population to determine total age-adjusted population death rate for the study population(s).

• Interpretation:

– The use of age-specific rates removes the effect of different age distributions among the populations being compared.

– Summary age-adjusted rates from different

populations can be compared if the populations have been adjusted to the same standard population

– The summary age-adjusted rate = rate per total standard population per time period

3

## How To perform Direct Age Adjustment

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1. Measure age-specific rates in the populations being compared

2. Choose a standard population

- A large, established population (example: U.S. Census data used as the standard population for a study comparing two U.S. states) [preferred method]

- One of the study populations

- A pool of the study populations

3. Apply the age-specific disease/death rate in one of the study populations to the age distribution of the standard population to calculate the adjusted rate in the study population.

Age Group: Age-specific rate (study population) x Age distribution (standard population)= Product

4

## Indirect Age Adjustment

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*Use when you don't know the ages of the people who died*

What is the expected number of events in the study population given the rate in the standard population?

• Use when you have limited information on the study population and the study population is small (so age-specific rates are unstable).

• The study population should usually be a sub-set of the standard population used.

• Method: Calculate a Standardized Mortality (or Morbidity) Ratio (SMR)

• For indirect adjustment the final measure is not a summary rate – it is a ratio.

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## How To Perform Indirect Age Adjust:

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1. Select an appropriate standard population for the study population.

2. Use the age distribution of the study population and the age-specific rates from the standard population to calculate the SMR

Age Group 1-> Age distribution: number of people (study population) x Age-specific rates (standard population) =Number of expected deaths

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## SMR

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Standardized Mortality (or Morbidity) Ratio

Total number of OBSERVED deaths

-------------------------------------------- =SMR

Total number of EXPECTED deaths

SMR = 1: No difference between the study population and the standard population.

SMR > 1: The study population is experiencing a higher than expected death (or disease) rate: EXCESS disease.

SMR < 1: The study population is experiencing a lower than expected death (or disease) rate: REDUCED disease.

7

## Survival Probability (3 kinds)

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1. Cumulative Survival

2. Conditional Probability

3. Cumulative Probability

8

## Cumulative Survival

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Direct calculation

½ of people diagnosed with a certain condition will die within one year after diagnosis. The probability of surviving one year is ½ (=0.50). In other words, the cumulative survival probability for one year is ½ (=0.5).

P(survive 1 year) = 0.50

9

## Conditional Probability

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Uses likelihood of an earlier event in calculation

½ of people who survive the first year die during the second year after diagnosis. The probability of surviving two years given that the person survived the one year is ½ (=0.50). Because this probability relies on a previous event (survival of one year) – that is, it has a “given” – it is called a conditional probability.

P(survive 2 years | survive 1 year) = 0.50

10

## Cumulative Probability

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The probability of a person surviving 2 years from diagnosis is the product of the probability that the person survived the first year times the probability that the person survived the second year given that the person survived the first year. This is a cumulative probability.

P(survive 2 years from start) =

P(survive 1 year)*P(survive 2 years | survive 1 year) = 0.5*0.5 = 0.25

11

## Survival Analysis Methods

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1. 5-Year Survival Rate

2. Kaplan-Meier Method (Example 4)

3. Life Tables (Example 3)

4. Median Survival: The length of time that half the study population survives

- Less affected by outliers (extremes)

- Only requires observation of half of deaths of study population

5. Relative Survival Rate: Compares survival with disease to the survival expected without disease

6. Cox Proportional Hazards Regression: An advanced statistical technique for assessing survival (don't need to learn)

12

## How are Life Tables and Kaplan-Meier analysis similar?

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1. They both remove lost cases from the denominator.

2. They do not need all cases enrolled at the same time

3. Survival is the primary statistic being measured.

13

## How are Life Tables and Kaplan-Meier analysis different?

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Life Tables perform follow up at the end of a calendar year.

Kaplan-Meier follows up with everyone as soon as a death occurs.

14

## Why are age adjustments used?

### It allows a fairer comparison of two locations

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