Hello everyone,
Upon learning that sascommunity.org is being decommissioned I decided to move my wiki page to this website as an article to help me continue to share the code. This macro has been around for years and has been constantly evolving to be my pocketknife of survival analysis whether it's graphing or generating tables. I have presented this macro at four separate conferences and have been freely sharing the macro with anyone who is interested.
Abstract
The research areas of pharmaceuticals and oncology clinical trials greatly depend on time-to-event endpoints such as overall survival and progression-free survival. One of the best graphical displays of these analyses is the Kaplan-Meier curve, which can be simple to generate with the LIFETEST procedure but difficult to customize. Journal articles generally prefer that statistics such as median time-to-event, number of patients, and time-point event-free rate estimates be displayed within the graphic itself, and this was previously difficult to do without an external program such as Microsoft Excel. The macro NEWSURV takes advantage of the Graph Template Language (GTL) that was added with the SG graphics engine to create this level of customizability without the need for backend manipulation. Taking this one step further, the macro was improved to be able to generate a lattice of multiple unique Kaplan-Meier curves for side by side comparisons or condensing figures for publications. The following is a paper describing the functionality of the macro and a description of how the key elements of the macro work.
What does the macro do?
Generates a graph
The original purpose of creating the macro was to make a journal quality Kaplan-Meier (KM) curve that included common survival statistics within the curve itself so that I did not have to manually add them to an image post-hoc. Below is an example using the dataset SASHELP.BMT:
The macro allows for a vast amount of optional customization to fit the user's needs, but also allows for simple macro calls to get the ball rolling.
Generates a table
I added the ability for the macro to take the survival statistics it was calculating and organize them into a clean summary table using the REPORT procedure.
Automatically calculates survival statistics
The macro automatically computes many commonly used survival statistics including the following:
Kaplan-Meier
Number of patients/events (PROC LIFETEST)
Median Time-to-Event w/95% Confidence Bounds (PROC LIFETEST)
Time-Point Event-Free Rates w/95% Confidence Bounds (PROC LIFETEST)
Unstratified/Stratified Logrank/Wilcoxon P-value (PROC LIFETEST)
Cumulative Incidence Analyses:
The methods used to compute this differ depending on SAS version.
Prior to SAS 9.4M3:
The code used to compute cumulative incidence was taken from the SAS autocall macro %CIF. This macro uses PROC IML to do most of the calculations, but since this is an optional add-on for some companies, the DATA STEP with array processing was used as a substitute. In order to calculate the p-value the matrix operations within PROC FCMP was used.
SAS 9.4M3+: Proc LIFETEST
Number of patients/events
Median Time-to-Event w/95% Confidence Bounds
Time-Point Event-Free Rates w/95% Confidence Bounds
Unstratified/Stratified Gray K-sample P-value
Patients-at-Risk CountsPatients-at-Risk Counts
Cox Proportional Hazards Regression
Hazards Ratio w/95% Confidence Bounds (PROC PHREG)
Wald Parameter P-values (PROC PHREG)
Wald/Score/Likelihood-Ratio Type 3 Test P-values (PROC PHREG)
Competing Risks (PROC PHREG - SAS 9.4+ Only)
Concordance index
This is calculated in data steps using the same code used in the survConcordance R package
There are parameters for customizing the automated analysis, including:
Stratification
Categorical and continuous adjusting factors for hazard ratios
Class variable options
Reference value
Order of values
Cumulative incidence variance calculations
Ability to subset with a WHERE clause without making a new data set
Ability to indicate censor or event value
Method for ties within Cox models
More plot annotations available
Confidence bounds as lines, color bands, or both
Reference lines that drop to the x-axis and/or y-axis
Can show either the median time-to-events or event-free rates
Why use this macro?
There are multitudes of survival based macros out there in the wild. Why should you choose to try this one instead of one of those or an internal macro?
The macro's middle name is customizability
Nearly all parts of the graph are customizable with multiple options.
Step Plot Curves and Confidence Bounds
Thickness, color, and pattern
Thickness, color, pattern, fill color, and transparency of band plot
Censor Indicating Scatter Plot
Size and color
Patients-at-Risk Block Plot
Size and weight of font
Location of block plot (Above x-axis or below x-axis)
Location of block plot labels (Left of block plot, above block plot, none)
Location and text of header
Match color to step plot curves
Display Statistics
Text size and weight
Statistics column header text
Which statistics are displayed and their order
Number of patients and number of events
Number of patients and number of events separately ###
Number of events/number of patients ###/###
Median time-to-event w/95% confidence bounds ###.# (###.#-###.#)
Hazard ratios w/95% confidence bounds ###.# (###.#-###.#)
Time-point event-free rates
Column for time-points (e.g. 60 days, 4 months, etc) which can be disabled
Column for event-free rates w/95% confidence bounds ###.# (###.#-###.#)
P-values
P-value format (#.####), values less than 0.0001 shown as >0.0001
Column for covariate level Wald p-values
Section for type 3 p-value of the class variable
Concordance index w/95% confidence bounds #.## (#.##-#.##)
Manually entered comments are available with the TABLECOMMENTS parameter
Titles/Footnotes
Text size and weight
Overall titles/footnotes for the image as well as individual titles/footnotes for each plot
Superscripts/subscripts/Unicode available
Axes
Y-axis can be set to proportions or percentages
X-axis can be transformed into other time units (days to months, etc.)
Automatic or manual labels
Automatic labels will be "Percent/Proportion with Event" for Y-axis and the time variable's label for the X-axis
Manual labels can be entered to override automatic labels
Label and tick value text size and weight
Top and right frames can be disabled
Axis colors
Image options
Can output any type of image
Includes special programming for TIFF files to be smaller file size
Can output or be included within nearly any ODS tags (RTF, EXCEL, PDF, HTML, POWERPOINT)
Height, width, dpi, anti aliasing
Axis colors and font colors
Background colors and background transparency
The macro runs clean
The NEWSURV macro is designed to run completely internally and will not change your options, does not have any global macro variables, and cleans up any temporary data sets that it makes
Includes thorough error checking that not only is designed to stop the macro before it crashes, but gives the user tips on what went wrong
For example if a macro option is used incorrectly (e.g. a variable doesn't exist) the macro error text will tell this to the user
If a parameter with multiple options is used incorrectly (invalid value), the macro will tell the user this and list the valid values
The results, log, and notes are turned off while the macro is running to keep the log, listing and results windows clean
The macro runs multiple models and can create multiple graphs in one image
Multiple statistical models can be run with one macro call for the statistical table
Multiple graphs can be created within one image
Each graph can have different options including time variables, class variables, and methods
Easy to create a paneled image for manuscripts
The macro is mostly backwards compatible back to SAS 9.2
The macro was written in SAS 9.2 and most of the options and techniques are still compatible with the older versions (9.2/9.3) of SAS. These features include creating multiple graphs, calculating the concordance index, and running cumulative incidence models.
Thoroughly documented
The beginning of a macro has extensive documentation on each parameter including valid values and how to properly use each one.
Examples of Key Parameters
Below are the examples that were included in the sascommunity.org webpage.
Dataset for Examples
Make the dataset with the following code (also in macro documentation)
proc format;
value grpLabel 1='ALL' 2='AML low risk' 3='AML high risk';
run;
data BMT;
input DIAGNOSIS Ftime Status Gender@@;
label Ftime="Days";
format Diagnosis grpLabel.;
datalines;
1 2081 0 1 1 1602 0 1
1 1496 0 1 1 1462 0 0
1 1433 0 1 1 1377 0 1
1 1330 0 1 1 996 0 1
1 226 0 0 1 1199 0 1
1 1111 0 1 1 530 0 1
1 1182 0 0 1 1167 0 0
1 418 2 1 1 383 1 1
1 276 2 0 1 104 1 1
1 609 1 1 1 172 2 0
1 487 2 1 1 662 1 1
1 194 2 0 1 230 1 0
1 526 2 1 1 122 2 1
1 129 1 0 1 74 1 1
1 122 1 0 1 86 2 1
1 466 2 1 1 192 1 1
1 109 1 1 1 55 1 0
1 1 2 1 1 107 2 1
1 110 1 0 1 332 2 1
2 2569 0 1 2 2506 0 1
2 2409 0 1 2 2218 0 1
2 1857 0 0 2 1829 0 1
2 1562 0 1 2 1470 0 1
2 1363 0 1 2 1030 0 0
2 860 0 0 2 1258 0 0
2 2246 0 0 2 1870 0 0
2 1799 0 1 2 1709 0 0
2 1674 0 1 2 1568 0 1
2 1527 0 0 2 1324 0 1
2 957 0 1 2 932 0 0
2 847 0 1 2 848 0 1
2 1850 0 0 2 1843 0 0
2 1535 0 0 2 1447 0 0
2 1384 0 0 2 414 2 1
2 2204 2 0 2 1063 2 1
2 481 2 1 2 105 2 1
2 641 2 1 2 390 2 1
2 288 2 1 2 421 1 1
2 79 2 0 2 748 1 1
2 486 1 0 2 48 2 0
2 272 1 0 2 1074 2 1
2 381 1 0 2 10 2 1
2 53 2 0 2 80 2 0
2 35 2 0 2 248 1 1
2 704 2 0 2 211 1 1
2 219 1 1 2 606 1 1
3 2640 0 1 3 2430 0 1
3 2252 0 1 3 2140 0 1
3 2133 0 0 3 1238 0 1
3 1631 0 1 3 2024 0 0
3 1345 0 1 3 1136 0 1
3 845 0 0 3 422 1 0
3 162 2 1 3 84 1 0
3 100 1 1 3 2 2 1
3 47 1 1 3 242 1 1
3 456 1 1 3 268 1 0
3 318 2 0 3 32 1 1
3 467 1 0 3 47 1 1
3 390 1 1 3 183 2 0
3 105 2 1 3 115 1 0
3 164 2 0 3 93 1 0
3 120 1 0 3 80 2 1
3 677 2 1 3 64 1 0
3 168 2 0 3 74 2 0
3 16 2 0 3 157 1 0
3 625 1 0 3 48 1 0
3 273 1 1 3 63 2 1
3 76 1 1 3 113 1 0
3 363 2 1
;
run;
Four Variables:
FTIME: Survival time
STATUS: Survival status (0=Alive, 1=Death, 2=Other Failure)
DIAGNOSIS: Type of disease (1='ALL' 2='AML low risk' 3='AML high risk')
Gender: Patient's gender (0=Female, 1=Male)
Example 1: Basic Macro Call
%newsurv(DATA=bmt, TIME=FTIME, CENS=STATUS, CEN_VL=0, SUMMARY=0);
This is basic macro call using almost only required parameters. The graph is plotted with censor markers and confidence bounds by default, and displays number of patients, number of events, and median time to event within the graph. The following parameters are introduced:
DATA: The dataset to be used by the macro. This dataset will not be modified by the macro.
TIME: The variable within DATA that contains the patients time-to-event values. Must be numeric.
CENS: The variable within DATA that contains the patients event status. Must be numeric.
CEN_VL: The value of the CENS varaible that contains the censor value. Must be a numeric value.
SUMMARY: This parameter determines if the table summary is displayed along with the plot. 1 is Yes and 0 is No.
Example 2: Plotting Multiple Curves with a CLASS Parameter
%newsurv(DATA=bmt, TIME=FTIME, CENS=STATUS, CEN_VL=0, SUMMARY=0, CLASS=DIAGNOSIS, CLASSREF=ALL,CLASSORDER=1 3 2);
This example shows how to add a CLASS parameter to produce grouped survival curves. Doing so also adds hazard ratios and a p-value to the plot statistical summary table. The example shows how to use other parameters related to the CLASS variable. The following new parameters are introduced:
CLASS: Variable used to group the plots. Can be character or numeric.
CLASSREF: Level of the CLASS variable that is to be used as the reference for the hazard ratios. The value specified must be one of the formatted values of the CLASS variable. If not specified then the last value alphabetically is used.
CLASSORDER: Reorders the CLASS levels within the plot. The values are sorted alphabetically by formatted values by default. They are reordered by entering a numbered list. In this example 1 3 2 is used which specifies the first, then third, then second alphabetical levels. Ordering by 1 2 3 would match the default.
Example 3: Modifying the Axes and Curves
%newsurv(DATA=bmt, TIME=FTIME, CENS=STATUS, CEN_VL=0, SUMMARY=0, CLASS=DIAGNOSIS, CLASSREF=ALL,CLASSORDER=1 3 2,
COLOR=black red green, PATTERN=solid, LINESIZE=3pt, SYMBOLSIZE=10pt,
XDIVISOR=30.44, XMAX=100, XINCREMENT=10, XLABEL=Months, YTYPE=PPT, YLABEL=Proportion Alive);
This example shows how to change the X and Y axis scale and labels as well as the attributes of the Kaplan-Meier curves. The x-axis is changed from days to months (this does not affect the original dataset) and the tick values are determined by XMAX and XINCREMENT. The y-axis is changed to proportion using the YTYPE parameter. The Kaplan-Meier curves can have their colors, patterns, thickness, and censor symbols modified. The following new parameters are all introduced:
COLOR: Provides a list of colors that will be applied to the lines in the order of the CLASS variable. If only one color is provided then that color is used for all lines. Default is black.
PATTERN: Provides a list of patterns that will be applied to the lines in the order of the CLASS variable. If only one pattern is provided then that pattern is used for all lines. Numbers between 1 and 42 can be used as well as certain keywords like SOLID. The default is AUTO, which makes all lines solid when colors are specified and different patterns when only one color is provided.
LINESIZE: Provides the thickness of the graph lines. Must be a number followed by pt. Default is 1pt.
SYMBOLSIZE: Provides the size of the censor symbols. Must be a number followed by pt. Default is 3pt.
XDIVISOR: Converts the time variable to other units by dividing by a scalar value. Does not affect the original dataset.
XMAX: Determines the maximum value of the x-axis based on final converted units. Computed automatically by default.
XINCREMENT: Determines the tick value increment of the x-axis of final converted units. Computed automatically by default.
XLABEL: Determines the label of the X-axis. Default is the time variable label.
YTYPE: Determines if the Y-axis is in percentages or proportions. Default is PPT (Percent).
YLABEL: Determines the label of the Y-axis. Default is either Percentage with Event or Proportion with Event.
Example 4: Modifying the Statistics Table and Showing Event-free Rates
%newsurv(DATA=bmt, TIME=FTIME, CENS=STATUS, CEN_VL=0, SUMMARY=0, CLASS=DIAGNOSIS, CLASSREF=ALL,CLASSORDER=1 3 2,
COLOR=black red green, PATTERN=solid, LINESIZE=3pt, SYMBOLSIZE=10pt,
XDIVISOR=30.44, XMAX=100, XINCREMENT=10, XLABEL=Months, YTYPE=PPT, YLABEL=Proportion Alive,
TIMELIST=20 40,TIMEDX=months,DISPLAY=legend timelist);
This example demonstrates changing which statistics are shown within the plot table and how to display Kaplan-Meier time-point event-free rates. One or more event-free rates can be specified, and they will be displayed vertically. The column that shows the time-point can be disabled when displaying only one time-point. The following new parameters are all introduced:
DISPLAY: Controls which statistics are displayed within the plot summary table. Items are displayed in the same order that they are listed within the macro variable. The default changes depending on what kind of plot is being displayed.
TIMELIST: Enter list of one or more time-points in the final X-axis units to calculate time-point event-free rates. Can be a simple list of numbers (xx xx xx xx) or a list in loop format (xx to xx by xx).
TIMEDX: This parameter will be used to display the units within the time-point estimates. For example, entering Months will add the text Months after each time-point number within the plot.
Example 5: Adding Patients-at-Risk
%newsurv(DATA=bmt, TIME=FTIME, CENS=STATUS, CEN_VL=0, SUMMARY=0, CLASS=DIAGNOSIS, CLASSREF=ALL,CLASSORDER=1 3 2,
COLOR=black red green, PATTERN=solid, LINESIZE=3pt, SYMBOLSIZE=10pt,
XDIVISOR=30.44, XMAX=100, XINCREMENT=10, XLABEL=Months, YTYPE=PPT, YLABEL=Proportion Alive,
RISKLIST=0 to 100 by 10,RISKLOCATION=BOTTOM,RISKCOLOR=1);
This example gives a basic demonstration of adding the patients-at-risk counts to the bottom of the plot. There are many options to customize the location of the labels, headers, where the table is printed, and even what type of numbers are shown. The following new parameters are all introduced:
RISKLIST: Enter list of one or more time-points in the final X-axis units to display the current patients-at-risk. Can be a simple list of numbers (xx xx xx) or a list in loop format (xx to xx by xx). Does not have to be the same as TIMELIST and does not have to match X-axis tick marks.
RISKLOCATION: Determines where the patients-at-risk will be drawn. Default is BOTTOM, which displays the numbers below the X-axis. Specifying INSIDE would put the numbers under the curve above the X-axis.
RISKCOLOR: Determines if the patients-at-risk numbers are colored to match the Kaplan-Meier curves. Default is 0 (no). Specifying 1 will color the numbers, and can potentially make matching the numbers to the curves visually easier.
Other useful options:
PARHEADER: Determines the header used above the patients-at-risk table. If left blank then will not be drawn.
PARHEADERALIGN: Determines where the header will be drawn. Options are LEFT, CENTER, RIGHT, and LABELS. Specifying LABELS will place the header above the labels to the left of the numbers.
RISKLABELLOCATION: Determines where the labels for the numbers are drawn. Options are LEFT, ABOVE and null. Specifying LEFT draws the labels to the left. Specifying ABOVE draws the labels above the numbers in their own row which is useful for long labels. Specifying nothing will cause the labels to not be drawn. This can be useful when pairing with RISKCOLOR.
PARDISPLAY (New): Determines what numbers are shown in the patients-at-risk table. One or more items can be listed. Options are PAR (Patients-at-risk), NCENS (Number of cumulative censors), and NEVENTS (Number of cumulative events). Two combinations, PAR_NCENS and PAR_NEVENTS are also allowed.
Example 6: Cumulative Incidence
%newsurv(DATA=bmt, TIME=FTIME, CENS=STATUS, CEN_VL=0, SUMMARY=0, CLASS=DIAGNOSIS, CLASSREF=ALL,CLASSORDER=1 3 2,
COLOR=black red green, PATTERN=solid, LINESIZE=3pt, SYMBOLSIZE=10pt,
METHOD=CIF, EV_VL=1);
This example shows how to plot cumulative incidence instead of Kaplan-Meier curves. The following new parameters are all introduced:
METHOD: Determines which method is used to generate the curves. Options are KM (Kaplan-Meier) or CIF (Cumulative Incidence Function).
EV_VL: Determines which value of the status variable is the event of interest. Non-event and non-censor values are considered other events.
Example 7: Multiple Plots
%newsurv(DATA=bmt, TIME=FTIME, CENS=STATUS, CEN_VL=0, SUMMARY=0, CLASS=DIAGNOSIS, CLASSREF=ALL,CLASSORDER=1 3 2,
COLOR=black red green, PATTERN=solid, LINESIZE=3pt, SYMBOLSIZE=10pt,
METHOD=KM|CIF, EV_VL=1, SREVERSE=1|0, NMODELS=2, ROWS=2, AUTOALIGN=BOTTOMRIGHT|TOPRIGHT);
This example shows how to produce multiple plots in a lattice diagram. Any options that will be different between plots have the | (capital \) delimiter to designate different settings per option. Any options without a | delimiter will keep the same settings across all models. This example also demonstrates the difference when plotting CIF versus 1-Survival. The following new parameters are all introduced:
SREVERSE: Determines if Survival or 1-Survival is plotted. 1-Survival is not the same as CIF. Default is 0 (Survival) and 1 indicates 1-Survival.
NMODELS: Determines how many models will be run. Default is 1.
ROWS: Determines how many rows will be in the graph lattice. Default is 1.
AUTOALIGN: Determines where the statistical summary table is shown within the plot. Default is TOPRIGHT. Can be anchored to any of the 9 primary points of the plot (TOPRIGHT, TOP, TOPLEFT, LEFT, CENTER, RIGHT, BOTTOMRIGHT
Example 8: Reference Lines
%newsurv(DATA=bmt, TIME=FTIME, CENS=STATUS, CEN_VL=0, SUMMARY=0, CLASS=DIAGNOSIS, CLASSREF=ALL,CLASSORDER=1 3 2,
COLOR=black red green, PATTERN=solid, LINESIZE=3pt, SYMBOLSIZE=10pt,
REFLINES=medians,REFLINEAXIS=both);
This example shows how to add reference lines. Reference lines can highlight two different items: medians and time-point estimates. The reference lines can be dropped to either axis. The following new parameters are all introduced:
REFLINES: Determines which statistic is used for the reference lines. Either MEDIANS or TIMEPOINTS are allowed. If TIMEPOINTS is specified then all time-points in TIMELIST are shown.
REFLINEAXIS: Determines which axis the reference lines are drawn to. Options are X, Y or Both.
Other options:
REFLINEMETHOD: Determines if reference lines are drawn from the KM curves or across the whole plot. Default is DROP. Options are DROP and FULL.
Example 9: Confidence Intervals
%newsurv(DATA=bmt, TIME=FTIME, CENS=STATUS, CEN_VL=0, SUMMARY=0, CLASS=DIAGNOSIS, CLASSREF=ALL,CLASSORDER=1 3 2,
COLOR=black red green, PATTERN=solid, LINESIZE=3pt, SYMBOLSIZE=10pt,
PLOTCI=1);
This example shows how to add confidence intervals. Confidence intervals are automatically added for graphs with no CLASS variable. Confidence intervals can be added as a filled background, as lines, or both. By default only a filled background is used similar to the LIFETEST procedure. The following new parameters are all introduced:
PLOTCI: Determines if confidence intervals are drawn. Default is 2, which makes confidence intervals if no CLASS variable is provided, but no confidence intervals if a CLASS variable is provided. Options are 1 to force confidence interval and 0 to disable confidence interval.
Expansion Macros
Adjusted Survival
Multivariate models are often necessary in survival analysis in order to account for confounding factors. Adjusting for other factors can dramatically change outcomes such as hazard ratio. When outcomes are dramatically changed in a multivariate model it can be inappropriate to plot the unadjusted curves. There are numerous methods available for creating adjusted survival curves, and none are the correct method for all situations. Thus there was a need to have a series of macros that could create the high quality plots of NEWSURV, but with the appropriate methodologies for adjusted survival curves. These macros were designed to adjust survival curves using either the direct adjustment or inverse weights methodologies. A third macro, NEWSURV_DATA, allows the user to pre-calculate their own survival curves and then plot them with the customization of NEWSURV.
NEWSURV_ADJ_DIRECT
The NEWSURV_ADJ_DIRECT macro calculates the adjusted survival curves based off of the predicted survival curves created by the PHREG procedure. This is described in more detail in the PharmaSUG 2017 paper.
NEWSURV_ADJ_INVWTS
The NEWSURV_ADJ_INVWTS macro calculates weights from the LOGISTIC procedure that it then supplies to the LIFETEST procedure WEIGHTS statement.This is described in more detail in the PharmaSUG 2017 paper.
NEWSURV_DATA
The NEWSURV_DATA macro allows the user to specify their own dataset with time and survival variables that have been previously calculated in order to produce a highly customizable journal quality image. This allows the user to use their own adjustment or calculation method not available in the NEWSURV macros.
Example 10: Adjusted Survival Curves
%newsurv_adj_invwts(DATA=bmt, TIME=FTIME, CENS=STATUS, CEN_VL=0, SUMMARY=0,
CLASS=DIAGNOSIS, CLASSREF=ALL,CLASSORDER=1 3 2,
COLOR=black red green,LINESIZE=3pt, SYMBOLSIZE=10pt, CLASSCOV=gender);
This example shows how to make adjusted survival curves using the inverse weights methods. The macro parameters are mainly similar to NEWSURV. The following new parameters are all introduced:
CLASSCOV: Specifies discrete covariates to adjust the survival curves, hazard ratios, and p-values by. This is also available in NEWSURV, but will not adjust the actual curves.
Other options:
CONTCOV: Specifies continuous covariates to adjust the survival curves, hazard ratios and p-values by. This is also available in NEWSURV, but will not adjust the actual curves.
PLOT_UNADJUST: Determines if the unadjusted survival curves are drawn. Default is 1 (Yes).
Macros and options provided by SAS
Editor's note: we added this mention of SAS-provided macros/options for completeness.
In addition to the thorough options provided here and documented in @JeffMeyers papers, SAS also provides guidance and code for customizing the Kaplan Meier survival plot.
See the special chapter in the SAS/STAT User's Guide.
Download the source code for SAS macros
Note that these options/macros work only with the more recent versions of SAS.
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