Releases: kassambara/survminer
survminer 0.4.9
Minor changes
- A new vignette added to show how to display interaction using ggforest() (#496).
- Since ggplot2 v3.3.0, the function
element_text()
issues a warning when vectorized arguments are provided, as in colour = c("red", "green", "blue"). This is a breaking change affecting the functionggsurvtable()
. To fix this, the functionggtext::element_markdown()
is now used in place ofelement_text()
to handle vectorized colors (issue #455 fixed by pull #503).
Bug fixes
survminer 0.4.8
Minor changes
- Maintenance update due to new broom 0.7.0 version by explicitly setting conf.int = TRUE in the call to tidy.coxph from
ggforest()
(pull 485).
survminer 0.4.6
New features
- A new function
surv_adjustedcurves
is extracted fromggadjustedcurves
. This function calculates adjusted survival curves but do not plot them. Its results may be useful for calculation of median survival or some other statistics. (@pbiecek, #423).
Minor changes
- Adapted to tidyr 1.0.0 (#424
survminer 0.4.5
Minor changes
- Adding variable with a group-agnostic approach (@jennybc, #414
cmprsk
is no longer needed for survminer installation. The package has been moved from Imports to Suggests. It's only used in documentations (@massimofagg, #394.
Bug fixes
- Now, in
ggflexsurvplot()
, the grouping variable can be factor or character vector (@andersbergren , #393 - Bug fixed for plotting confidence intervals for coxph using ggsurvplot (@kharknes, #393
survminer 0.4.4
Minor changes
- ggforest updated to take into account interactions and polynomial or spline terms (@fabian-s, #306, @fabian-s, #388
- Removed unnecessary call to
anova()
as requested (@pbiecek, #391
Bug fixes
-
When a factor variable name is the same as one of its level,
ggsurvplot()
failed (@KohSoonho, #387). Fixed now. -
ggsurvplot()
can now create correctly faceted survival curves (@uraniborg, #254, @BingxinS, #363) -
A typo fixed in the formula for weightened log-rank test (@MarcinKosinski, #336.
-
surv_summary()
can now handle the output ofsurvfit(cox.model, newdata)
when the optionconf.type = "none"
is specified by users (@HeidiSeibold, #335. -
ggadjustedcurves()
has now flipped labels forconditional
/marginal
to mach names from ’Adjusted Survival Curves’ by Terry Therneau, Cynthia Crowson, Elizabeth Atkinson (2015) (@pbiecek, #335.
Survminer 0.4.3
New features
- Now
ggsurvplot()
can be used to plot survreg model (@HeidiSeibold, #276, #325 ).
Minor changes
- Now,
ggforest()
simply returns a ggplot instead of drawing automatically the plot (@grvsinghal, #267).
Bug fixes
- Now, hiding strata names in risk table work when combining survfits (@krassowski, #317).
- Now,
axes.offset
argument is also applied to risk table (@dmartinffm, #243). - It is now possible to add
ggsurvplot
to powerpoint document using ReporteRs even if there is no risk table (@DrRZ, #314).
Survminer 0.4.1
New features
-
New function
ggflexsurvplot()
to create ggplot2-based graphs for flexible survival models. -
The function
ggadjustedcurves()
handles now argumentmethod
that defines how adjusted curves shall be calculated. Withmethod='conditional'|'marginal'
subpopulations are balanced with respect to variables present in the model formula. Withmethod='single'|'average'
the curve represents just the expected survival curves.
Major changes
- The function
ggcoxadjustedcurves()
is replaced byggadjustedcurves()
(#229).
Minor changes
-
The grouping variable to the
ggadjustedcurves()
function is now passed as a name (character) of grouping variable not as a vector with values of grouping variable. -
New argument
font.family
inggsurvtable()
to change the font family in the survival tables - such as risk, cummulative events and censoring tables. For example font.family = "Courier New" (@Swechhya, #245). -
Now, in
ggsurvplot()
the data argument should be strictly provided (@dnzmarcio, #235)
Bug fixes
ggforest()
no longer tries to bolt a table full of text to the coefficient plot (@mmoisse, #241), instead the annotations are done via ggplot2::annotate, see example at: @fabian-s, #264
survminer 0.4.0
New features
New options in ggsurvplot()
-
New argument
test.for.trend
added inggsurvplot()
to perform a log-rank test for trend. logical value. Default is FALSE. If TRUE, returns the test for trend p-values. Tests for trend are designed to detect ordered differences in survival curves. That is, for at least one group. The test for trend can be only performed when the number of groups is > 2 (#188). -
New argument
add.all
added now inggsurvplot()
to add he survival curves of (all) pooled patients onto the main survival plot stratified by grouping variables. Alias of theggsurvplot_add_all()
function (#194). -
New argument
combine = TRUE
is now available in theggsurvplot()
function to combine a list of survfit objects on the same plot. Alias of the ggsurvplot_combine() function (#195). -
The standard convention of ggplot2 is to have the axes offset from the origin. This can be annoying with Kaplan-Meier plots. New argument
axes.offset
added non inggsurvplot()
. logical value. Default is TRUE. If FALSE, set the plot axes to start at the origin (c(0,0)) (#196). -
The function
ggsurvplot()
can take a list of survfit objects and produces a list of ggsurvplots (#204). -
New argument
facet.by
added now inggsurvplot()
to draw multi-panel survival curves of a data set grouped by one or two variables. Alias of theggsurvplot_facet()
function (#205). -
New argument
group.by
added now inggsurvplot()
to create survival curves of grouped data sets. Alias of theggsurvplot_group_by()
function. -
In
ggsurvplot()
, one can specify pval = TRUE/FALSE as a logical value. Now, it's also possible to specify the argumentpval
as a numeric value (e.g.: pval = 0.002), that will be passed to the plot, so that user can pass any custom p-value to the final plot (@MarcinKosinski, #189) or one can specify it as a character string (e.g.: pval = "p < 0001") (@MarcinKosinski, #193). -
New argument
xscale
inggsurvplot()
: numeric or character value specifying x-axis scale.- If numeric, the value is used to divide the labels on the x axis. For example, a value of 365.25 will give labels in years instead of the original days.
- If character, allowed options include one of c("d_m", "d_y", "m_d", "m_y", "y_d", "y_m"), where d = days, m = months and y = years. For example, xscale = "d_m" will transform labels from days to months; xscale = "m_y", will transform labels from months to years (#166).
-
New arguments
censor.shape
andcensor.size
to change the shape and the shape of censors (#186 & #187). -
New argument
conf.int.alpha
added inggsurvplot()
. Numeric value specifying fill color transparency. Value should be in [0, 1], where 0 is full transparency and 1 is no transparency.
New functions
-
New function
surv_group_by()
added to create a grouped data set for survival analysis. -
New function
ggsurvplot_df()
added. An extension to ggsurvplot() to plot survival curves from any data frame containing the summary of survival curves as returned the surv_summary() function. Might be useful for a user who wants to use ggsurvplot for visualizing survival curves computed by another method than the standard survfit.formula function. In this case, the user has just to provide the data frame containing the summary of the survival analysis. -
New function
surv_median()
added to easily extract median survivals from one or a list of survfit objects (#207). -
New function
surv_pvalue
() added to compute p-value from survfit objects or parse it when provided by the user. Survival curves are compared using the log-rank test (default). Other methods can be specified using the argument method. -
New function
surv_fit
() added to handle complex situation when computing survival curves (Read more in the doc: ?surv_fit). Wrapper arround the standardsurvfit
() [survival] function to create survival curves. Compared to the standard survfit() function, it supports also:- a list of data sets and/or a list of formulas,
- a grouped data sets as generated by the function surv_group_by,
- group.by option
Major changes
- The
ggforest()
function has changed a lot. Now presents much more statistics for each level of each variable (extracted withbroom::tidy
) and also some statistics for thecoxph
model, like AIC, p.value, concordance (extracted withbroom::glance
) (#178)
Minor changes
-
Now,
ggcompetingrisks()
supports theconf.int
argument. Ifconf.int=TRUE
andfit
is an object of classcuminc
then confidence intervals are plotted withgeom_ribbon
. -
Now,
ggsurvplot()
supports thesurvfit()
outputs when used with the argumentstart.time
. -
Now, the default behaviour of
ggsurvplot()
is to round the number at risk using the optiondigits = 0
(214). -
pairwise_survdiff()
has been improved to handle a formula with multiple variables (213). -
The argument
color
are updated allowing to assign the same color for same groups accross facets (#99 & #185).- If the number of strata/group (n.strata) = 1, the expected value is the color name. For example color = "blue".
- If n.strata > 1, the expected value is the grouping variable name. By default, survival curves are colored by strata using the argument color = "strata", but you can also color survival curves by any other grouping variables used to fit the survival curves.
For example, in the following script, survival curves are colored by the grouping variable sex
in all facets:
library(survminer)
library(survival)
fit <- survfit( Surv(time, status) ~ sex + rx + adhere,
data = colon )
ggsurv <- ggsurvplot(fit, data = colon,
color = "sex",
legend.title = "Sex",
palette = "jco")
ggsurv$plot + facet_grid(rx ~ adhere)
-
Now, the function
pairwise_survdiff()
checks whether the grouping variable is a factor. If this is not the case, the grouping variable is automatically converted into a factor. -
ggsurvplot()
: Now, log scale is used for x-axis when plotting the complementary log−log function (argument `fun = "cloglog") (#171). -
Now, the argument
palette
inggsurvplot()
ccan be also a numeric vector of length(strata); in this case a basic color palette is created using the functiongrDevices::palette()
. -
The
%+%
function insurvminer
has been replaced by%++%
to avoid breaking theggplot2::%+%
function behavior when using survminer (#199 and #200). -
New argument
fun
added inggcoxadjustedcurves()
(@meganli, #202). -
The function
theme_classic2()
removed.
Bug fixes
-
Columns/Rows are now correctly labeled in
pairwise_survdiff
() display (@mriffle, #212). -
Now, the
pairwise_survdiff()
function works when the data contain NAs (@emilelatour , #184). -
Now,
ggsurvplot()
fully supports different methods, in the survMisc package, for comparing survival curves (#191).
survminer 0.3.1
Minor changes
- The example section of the
ggcoxdiagnostics()
function and the vignette fileInformative_Survival_Plots.Rmd
have been updated so thatsurvminer
can pass CRAN check under R-oldrelease. - New example dataset
BMT
added for competing risk analysis. - New data set
BRCAOV.survInfo
added, used in vignette files
Bug fixes
survminer 0.3.0
New features
New options in ggsurvplot()
-
Additional
data
argument added to theggsurvplot()
function (@kassambara, #142). Now, it's recommended to pass to the function, the data used to fit survival curves. This will avoid the error generated when trying to use theggsurvplot()
function inside another functions (@zzawadz, #125). -
New argument
risk.table.pos
, for placing risk table inside survival curves (#69). Allowed options are one of c("out", "in") indicating 'outside' or 'inside' the main plot, respectively. Default value is "out". -
New arguments
tables.height, tables.y.text, tables.theme, tables.col
: for customizing tables under the main survival plot: (#156). -
New arguments
cumevents
andcumcensor
: logical value for displaying the cumulative number of events table (#117) and the cumulative number of censored subject (#155), respectively. -
Now,
ggsurvplot()
can display both the number at risk and the cumulative number of censored in the same table using the optionrisk.table = 'nrisk_cumcenor'
(#96). It's also possible to display the number at risk and the cumulative number of events using the optionrisk.table = 'nrisk_cumevents'
. -
New arguments
pval.method
andlog.rank.weights
: New possibilities to compare survival curves. Functionality based onsurvMisc::comp
. -
New arguments
break.x.by
andbreak.y.by
, numeric value controlling x and y axis breaks, respectively. -
Now,
ggsurvplot()
returns an object of class ggsurvplot which is list containing the following components (#158):- plot: the survival plot (ggplot object)
- table: the number of subjects at risk table per time (ggplot object). Returned only when risk.table = TRUE.
- cumevents: the cumulative number of events table (ggplot object). Returned only when cumevents = TRUE.
- ncensor.plot: the number of censoring (ggplot object). Returned only when ncensor.plot = TRUE or cumcensor = TRUE.
- data.survplot: the data used to plot the survival curves (data.frame).
- data.survtable: the data used to plot the tables under the main survival curves (data.frame).
Themes
-
New function
theme_survminer()
to change easily the graphical parameters of plots generated with survminer (#151). A theme similar to theme_classic() with large font size. Used as default theme in survminer functions. -
New function
theme_cleantable()
to draw a clean risk table and cumulative number of events table. Remove axis lines, x axis ticks and title (#117 & #156).
# Fit survival curves
require("survival")
fit<- survfit(Surv(time, status) ~ sex, data = lung)
# Survival curves
require("survminer")
ggsurvplot(fit, data = lung, risk.table = TRUE,
tables.theme = theme_cleantable()
)
New functions
- New function
+.ggsurv()
to add ggplot components -theme()
,labs()
- to an object of class ggsurv, which is a list of ggplots. (#151). For example:
# Fit survival curves
require("survival")
fit<- survfit(Surv(time, status) ~ sex, data = lung)
# Basic survival curves
require("survminer")
p <- ggsurvplot(fit, data = lung, risk.table = TRUE)
p
# Customizing the plots
p %+% theme_survminer(
font.main = c(16, "bold", "darkblue"),
font.submain = c(15, "bold.italic", "purple"),
font.caption = c(14, "plain", "orange"),
font.x = c(14, "bold.italic", "red"),
font.y = c(14, "bold.italic", "darkred"),
font.tickslab = c(12, "plain", "darkgreen")
)
-
New function
arrange_ggsurvplots()
to arrange multiple ggsurvplots on the same page (#66). -
New function
ggsurvevents()
to calculate and plot the distribution for events (both status = 0 and status = 1); withtype
parameter one can plot cumulative distribution of locally smooth density; with normalised, distributions are normalised. This function helps to notice when censorings are more common (@pbiecek, #116). -
New function
ggcoxadjustedcurves()
to plot adjusted survival curves for Cox proportional hazards model (@pbiecek, #133 & @markdanese, #67). -
New function
ggforest()
for drawing forest plot for the Cox model. -
New function
pairwise_survdiff()
for multiple comparisons of survival Curves (#97). -
New function
ggcompetingrisks()
to plot the cumulative incidence curves for competing risks (@pbiecek, #168.
Helper functions
New heper functions ggrisktable()
, ggcumevents()
, ggcumcensor()
. Normally, users don't need to use these function directly. Internally used by the function ggsurvplot()
.
ggrisktable()
for plotting number of subjects at risk by time. (#154).ggcumevents()
for plotting the cumulative number of events table (#117).ggcumcensor()
for plotting the cumulative number of censored subjects table (#155).
Major changes
-
New argument
sline
in theggcoxdiagnostics()
function for adding loess smoothed trend on the residual plots. This will make it easier to spot some problems with residuals (like quadratic relation). (@pbiecek, #119). -
The design of
ggcoxfunctional()
has been changed to be consistent with the other functions in the survminer package. Now,ggcoxfunctional()
works with coxph objects not formulas. The arguments formula is now deprecated (@pbiecek, #115). -
In the
ggcoxdiagnostics()
function, it's now possible to plot Time in the OX axis (@pbiecek, #124). This is convenient for some residuals like Schoenfeld. Thelinear.predictions
parameter has been replaced withox.scale = c("linear.predictions", "time", "observation.id")
.
Minor changes
-
New argument
tables.height
inggsurvplot()
to apply the same height to all the tables under the main survival plots (#157). -
It is possible to specify
title
andcaption
forggcoxfunctional
(@MarcinKosinski, #138) (font.main
was removed as it was unused.) -
It is possible to specify
title
,subtitle
andcaption
forggcoxdiagnostics
(@MarcinKosinski, #139) andfonts
for them. -
It is possible to specify global
caption
forggcoxzph
(@MarcinKosinski, #140). -
In
ggsurvplot()
, more information, about color palettes, have been added in the details section of the documentation (#100). -
The R package
maxstat
doesn't support very well an object of classtbl_df
. To fix this issue, now, in thesurv_cutpoint()
function, the input data is systematically transformed into a standard data.frame format (@MarcinKosinski, #104). -
It's now possible to print the output of the survminer packages in a powerpoint created with the ReporteRs package. You should use the argument newpage = FALSE in the
print()
function when printing the output in the powerpoint. Thanks to (@abossenbroek, #110) and (@zzawadz, #111). For instance:
require(survival)
require(ReporteRs)
require(survminer)
fit <- survfit(Surv(time, status) ~ rx + adhere, data =colon)
survplot <- ggsurvplot(fit, pval = TRUE,
break.time.by = 400,
risk.table = TRUE,
risk.table.col = "strata",
risk.table.height = 0.5, # Useful when you have multiple groups
palette = "Dark2")
require(ReporteRs)
doc = pptx(title = "Survival plots")
doc = addSlide(doc, slide.layout = "Title and Content")
doc = addTitle(doc, "First try")
doc = addPlot(doc, function() print(survplot, newpage = FALSE), vector.graphic = TRUE)
writeDoc(doc, "test.pptx")
- Now, in
ggcoxdiagnostics()
, the optionncol = 1
is removed from the functionfacet_wrap()
. By default,ncol = NULL
. In this case, the number of columns and rows in the plot panels is defined automatically based on the number of covariates included in the cox model.
Bug fixes
-
Now, risk table align with survival plots when legend = "right" (@jonlehrer, #102).
-
Now,
ggcoxzph()
works for univariate Cox analysis ([#103](ht...