Flashcards in Survival analysis Deck (13)

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1

## What information is required for each individual in survival analysis?

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a length of time after study enrolment during which no event occurred (until a fixed end-date)

a binary indicator of whether the end-point of that time period corresponds to an event or just the end of the observation period for that individual

2

## Describe the distribution of survival times and what this means

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usually positively skewed

better to use medians and IQRs than means and SDs

3

## What is meant by a censored observation?

### Individual observations where we do not know what happened after the end of the study are described as being right-censored

4

## Describe the Kaplan-Meier Plot

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graphs cumulative probability of survival against time as a step function

The plot is useful when used to compare two or more groups

5

## How is the cumulative probability of survival calculated?

### (1-dk/rk) x (previous cumulative frequency)

6

## Describe the log-rank test

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used to test differences in survival times between two or more groups

This is a non-parametric test

Ho; there's no difference in the groups' survival times

7

## Describe the Cox proportional hazards model

### a widely used method in cohort studies and clinical trials that allows times to be modelled in terms of continuous and categorical variables

8

## What is the hazard function h(t)

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The probability of an individual dying in time (t)

We model the effect of an exposure on the hazard rate compared to the background hazard rate

9

## What is the proportional hazards assumption?

### anything changing the value of the hazard function does so by the same magnitude, whatever the value of t

10

## How is the hazard ratio / relative hazard calculated?

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h(t)/Ho(t)

where Ho(t) is the background hazard function, for which all other explanatory variables are equal to zero. h(t) is the hazard function in the exposed group

11

## Describe the proportional hazards model

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it is semi-parametric

makes no assumptions about the shape of the distribution of the survival times but need to keep the proportional hazards assumption

12

## Describe multi-variate cox models

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include multiple covariates in the same model at the same time

we investigate the independent effect of those covariates on the outcomes.

similar to a regression - used to reduce the impact of confounding variables

13