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Pharmacy Biostatistics > Survival Analyses > Flashcards

Survival Analyses Flashcards

1
Q

Survival Analyses

A

Model ‘TIME TO EVENT’ data
Directly incorporates time into the analysis to show level of decay over time

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2
Q

Survival Data are inherently censored meaning what?

A

Not fully observed, the time to an event is unknown

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3
Q

When is survival analysis useful?

A

When follow-up is either incomplete or variable

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4
Q

Examples of Censoring are what?

A
  1. Loss to follow-up
  2. Study withdrawal
  3. An event occurs outside of the study period
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5
Q

Left Censoring

A

Before the study begins

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6
Q

Right Censoring

A

After the study ends

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7
Q

Interval Censoring

A

Missing observations during the study period itself

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8
Q

What type of outcome is seen in Survival Analysis?

A

Binary/Dichotomous
Yes/No outcome

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9
Q

Do Linear and Logistic Regression include censoring?

A

NO

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10
Q

What is Hazard Ratio?

A

First derivative of survival function, captures instantaneous slope

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11
Q

What is Survival Function?

A

Kaplan Meier: what is reported in the RCT
1:1 Comparison

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12
Q

What is Hazard Function?

A

Instantaneous risk of event at a certain time
-Can be used when non-randomized aka controlling for a variable so the data will not be skewed

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13
Q

Survival Analysis overall can be used for what?

A
  1. Account for censoring
  2. Compare survival times between 2 or more groups
  3. Assess relationships between hazard ratios and several covariates
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14
Q

What can be involved in Survival Analyses?

A
  1. Descriptive Statistics
  2. Bivariate Statistics
  3. Multivariate Statistics
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15
Q

Descriptive Analysis includes what?

A
  1. Average Survival
  2. Average Hazard Rate
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16
Q

What are the two most common methods in estimating the Survivor Curve?

A
  1. Kaplan Meier KM
  2. Cox Proportional Hazards Regression (COX Regression)
17
Q

Kaplan Meier KM Method

A

The KM survival curve is a graphical method of summarizing the probability of survival over time estimated from a sample
GENERATES A STAIR STEP survival curve

18
Q

Inferring KM

A

Separate KM curves can be estimated so statistically significant differences between the groups can be calculated via LOG RANK TEST (type of chi-square)

19
Q

Log Rank Test

A

Used to compare two survival curves
If there is a significant difference, one group will be viewed as having significantly greater survival times

20
Q

What is the main limitation of the Log Rank Test?

A

UNIVARIABLE, meaning it does NOT account for confounding by other covariates or effect modification

21
Q

Is confounding by other covariates a problem in randomized clinical trials?

A

NO, randomization is intended to uniformly distribute covariates across groups

22
Q

What is the most common multivariable extension of the log-rank test?

A

COX Regression

23
Q

Does COX Regression produce a stair step survival curve?

A

NO

24
Q

COX Regression is the MAIN method for RCT trials since it is the most common what?

A

Multivariable extension of the log rank test

25
Q

COX Regression builds on what?

A

Builds upon the concept of a hazard

26
Q

Hazard is defined as what?

A

The risk that a specific event will occur at any given time

27
Q

Hazard Rate

A

Number of events that occur per interval of time

28
Q

Hazard Function

A

Collection of an individual’s hazard for an event over time

29
Q

COX Regression mathematically what?

A

Separates the baseline hazard function from time-independent covariates

30
Q

The KEY assumption for COX Regression is what?

A

Proportional Hazards, must test if the assumption holds via various statistical diagnostics

31
Q

Proportional Hazards

A

Predictors have a constant proportional effect on the outcome
-If the assumption is violated, it means a given predictor usually has a time dependent proportional effect

32
Q

Strengths of COX and KM

A
  1. A formalized multivariable approach to incorporate time-dependent censoring
  2. COX regressions can incorporate several covariates
  3. Hazard ratios are a type of relative risk measure
33
Q

Hazard Ratio Meanings

A
  1. Hazard Ratio <1 = increased predictor leads to decreased hazard
  2. Hazard Ratio = 1 = no statistical difference
  3. Hazard Ratio >1 = increased predictor leads to increased hazard
34
Q

Limitations of COX and KM

A
  1. Does not automatically accommodate predictor variables that change over time

Pharmacy Biostatistics (17 decks)

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