Survival Analysis User Guide -...
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InVivoStat User Guides – Survival Analysis Version 4.0 December 2019
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Survival Analysis
User Guide
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Contents
1 Introduction ......................................................................................... 3
2 Dataset format ..................................................................................... 4
3 Analysis procedure .............................................................................. 5 3.1 Select the analysis module ........................................................................................................ 5 3.2 Select the dataset to be analysed ............................................................................................... 5 3.3 Select the response to analyse and terms to include in the statistical model ............................ 5 3.4 Select the analysis results ......................................................................................................... 6 3.5 Run the analysis ........................................................................................................................ 6
4 Output results ...................................................................................... 7
5 Controlling the output ........................................................................ 7
6 Test dataset example output .............................................................. 9 6.1 InVivoStat options .................................................................................................................... 9 6.2 Sample output ......................................................................................................................... 10
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1 Introduction
The Survival Analysis module in InVivoStat is available from the Statistics
drop-down menu entitled ‘Survival Analysis’. The user interface is:
The Survival Analysis module allows the user to calculate the Kaplan-Meier non-
parametric maximum likelihood estimates of the survival functions, produce a plot of
the survival curves and also perform a log-rank (or Mantel-Haenszel) test to compare
the survival times.
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2 Dataset format
The Survival Analysis module requires three input variables, the survival times
(Response variable), the categorisation variable (Treatment factor) and a variable
defining whether the observation is censored or not (Censorship variable). The values
of the censorship variables are either 1 (denoting an uncensored observation) or 0
(denoting a censored observation). An example is given below:
Event time Censorship Treatment
2 1 Low dose
4 0 Control
5 0 Control
5 0 Low dose
6 0 Top dose
7 1 Control
7 1 Low dose
8 1 Mid dose
8 0 Mid dose
8 1 Mid dose
8 0 Top dose
9 1 Low dose
12 1 Control
12 1 Mid dose
13 1 Control
13 0 Low dose
15 1 Low dose
15 1 Mid dose
16 1 Mid dose
16 0 Mid dose
17 1 Control
22 0 Low dose
22 1 Mid dose
23 1 Low dose
24 1 Mid dose
24 0 Mid dose
25 1 Low dose
25 0 Mid dose
26 1 Low dose
27 1 Control
28 1 Mid dose
30 1 Control
30 1 Low dose
30 1 Mid dose
30 1 Top dose
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3 Analysis procedure
The steps required to perform an analysis are described in this section.
3.1 Select the analysis module
The analysis begins by selecting the
Survival Analysis module from the
drop-down list of available modules:
Additional Analysis →
Survival Analysis
3.2 Select the dataset to be
analysed
Once the module is selected, the dataset
is chosen from the drop-down list of
available datasets.
Click ‘Submit’.
3.3 Select the response to
analyse and terms to
include in the statistical
model
Once the dataset has been selected, the
user selects the response variable to
analyse by clicking on the Response
box and selecting the response variable
to analyse.
Similarly, the user should select the
Treatment factor and the Censorship
variable that respectively define the
response categories and the censorship
status of the observations.
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3.4 Select the analysis results
There are several results that are
available. These are selected before
running the analysis and include:
1) Summary results
Produces a summary of the data,
including a confidence interval around
the median ‘response’.
2) Survival plot
Produces the plot of the Kaplan-Meier
survival curves.
3) Compare survival curves
Produces a table summarising the log-
rank test to compare the survival curves.
4) Significance level
The significance level default is 0.05, or
5%, although this can be changed.
3.5 Run the analysis
Click ‘Submit’ to run the analysis.
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4 Output results
Analysis information
InVivoStat identifies the response being analysed, the treatment factor and the
censorship variable.
Summary results
The summary results table includes the median (defined by the intersection on the
survival plot of a horizontal line at 0.5 and the survival curve) and its confidence
interval (not included on survival plot for clarity). If the intersection is not a point,
then we use the smallest point of intersection, e.g., if the survival curve were exactly
equal to 0.5 over an interval, then the smallest value is quoted.
Comparing survival curves
This table summarises the log-rank test to compare the survival curves.
Kaplan-Meier survival plot
Generates the Kaplan-Meier survival plot including markers to identify censored
observations.
References
A list of references for the methods applied in the analysis.
5 Controlling the output
The user has the ability to control various aspects of the output. These are available in
the ‘Output Options’ dialogue:
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Users can manipulate various plot
characteristics including line size, fonts
and marker size/type.
The user has control over all text
included on the plots, for example text
position, size and font.
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The user has control over the colour
scheme employed by InVivoStat,
including an option to produce all plots
in black & white.
Further information on these options can be found in the Getting Started User Guide.
6 Test dataset example output
6.1 InVivoStat options
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6.2 Sample output
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