ggkmrisktable: Create a Kaplan-Meier plot with risk table

In ggquickeda: Quickly Explore Your Data Using 'ggplot2' and 'table1' Summary Tables

Create a Kaplan-Meier plot with risk table

Description

Produces a km plot with a facettable risk table in ggplot2

Usage

ggkmrisktable(
  data = lung_long,
  time = "time",
  status = "DV",
  endpoint = "Endpoint",
  groupvar1 = "Endpoint",
  groupvar2 = "expname",
  groupvar3 = "none",
  exposure_metrics = c("age", "ph.karno"),
  exposure_metric_split = c("median", "tertile", "quartile", "none"),
  exposure_metric_soc_value = -99,
  exposure_metric_plac_value = 0,
  color_fill = "exptile",
  linetype = "exptile",
  xlab = "Time of follow_up",
  ylab = "Overall survival probability",
  nrisk_table_plot = TRUE,
  nrisk_table_variables = c("n.risk", "pct.risk", "n.event", "cum.n.event", "n.censor"),
  nrisk_table_breaktimeby = NULL,
  nrisk_table_textsize = 4,
  nrisk_position_scaler = 0.2,
  nrisk_position_dodge = 0.2,
  nrisk_offset = 0,
  nrisk_filterout0 = FALSE,
  km_logrank_pvalue = FALSE,
  km_logrank_pvalue_pos = c("left", "right"),
  km_trans = c("identity", "event", "cumhaz", "cloglog"),
  km_ticks = TRUE,
  km_band = TRUE,
  km_conf_int = 0.95,
  km_conf_type = c("log", "plain", "log", "log-log", "logit", "none"),
  km_conf_lower = c("usual", "peto", "modified"),
  km_median = c("none", "median", "medianci", "table"),
  km_median_table_pos = c("left", "right"),
  km_median_table_order = c("default", "reverse"),
  km_yaxis_position = c("left", "right"),
  facet_formula = NULL,
  facet_ncol = NULL,
  facet_strip_position = c("top", "top", "top", "top"),
  theme_certara = TRUE
)

Arguments

data	Data to use with multiple endpoints stacked into time, status, endpoint name
time	name of the column holding the time to event information default to time
status	name of the column holding the event information default to DV
endpoint	name of the column holding the name/key of the endpoint default to Endpoint
groupvar1	name of the column to group by, default Endpoint
groupvar2	name of the column to group by in addition to groupvar1, default expname
groupvar3	name of the column to group by in addition to groupvar1 and groupvar2, default "none"
exposure_metrics	name(s) of the column(s) to be stacked into expname exptile and split into exposure_metric_split
exposure_metric_split	one of "median", "tertile", "quartile", "none"
exposure_metric_soc_value	special exposure code for standard of care default -99
exposure_metric_plac_value	special exposure code for placebo default 0
color_fill	name of the column to be used for color/fill default to exptile
linetype	name of the column to be used for linetype default to exptile
xlab	text to be used as x axis label
ylab	text to be used as y axis label
nrisk_table_plot	TRUE
nrisk_table_variables	one or more from: "n.risk", "pct.risk", "n.event, "cum.n.event, "n.censor"
nrisk_table_breaktimeby	NULL
nrisk_table_textsize	4
nrisk_position_scaler	0.2
nrisk_position_dodge	0.2, negative values will reverse the order
nrisk_offset	0
nrisk_filterout0	FALSE
km_logrank_pvalue	FALSE
km_logrank_pvalue_pos	"left" or "right"
km_trans	one of "identity","event","cumhaz","cloglog"
km_ticks	TRUE
km_band	TRUE
km_conf_int	0.95
km_conf_type	default one of "log", "plain", "log-log", "logit", "none"
km_conf_lower	one of "usual", "peto", "modified"
km_median	add median survival information one of "none", "median", "medianci", "table"
km_median_table_pos	when table is chosen where to put it "left" or "right
km_median_table_order	when table is chosen the order of the entries "default" or "reverse"
km_yaxis_position	where to put y axis on "left" or "right
facet_formula	facet formula to be used otherwise ~ groupvar1 + groupvar2 + groupvar3
facet_ncol	NULL if not specified the automatic waiver will be used
facet_strip_position	position in sequence for the variable used in faceting default to c("top","top","top","top")
theme_certara	apply certara colors and format for strips and default colour/fill

Examples

library(tidyr)
# Example 1
lung_long <-  survival::lung |>
 dplyr::mutate(status = ifelse(status==1,0,1)) |>
 tidyr::gather(Endpoint,DV,status) |>
 dplyr::filter(!is.na(ph.karno))|>
 dplyr::filter(!is.na(pat.karno))|>
 dplyr::filter(!is.na(ph.ecog))
lung_long$ph.ecog <- ifelse(lung_long$ph.ecog>1,2,lung_long$ph.ecog)
lung_long$ph.ecog <- as.factor(lung_long$ph.ecog )
lung_long$ph.ecog <- as.factor(lung_long$ph.ecog )
lung_long$facetdum <- "(all)"

ggkmrisktable(data = lung_long, time= "time", status ="DV",
             exposure_metrics =c("age","ph.karno"),
             exposure_metric_split = "tertile",
             color_fill = "exptile",
             linetype = "expname",
             groupvar1 = "Endpoint",
             groupvar2 = "exptile",
             xlab = "Time of follow_up",
             ylab ="Overall survival probability",
             nrisk_table_variables = c("n.risk","n.event"),
             km_median = "medianci",
             km_band = FALSE,
             nrisk_table_breaktimeby = 200,
             facet_ncol = 3)
#Example 2
ggkmrisktable(data = lung_long, time= "time", status ="DV",
             exposure_metrics =c("age","ph.karno"),
             exposure_metric_split = "quartile",
             color_fill = "exptile",
             linetype = "none",
             groupvar1 = "Endpoint",
             groupvar2 = "exptile",
             xlab = "Time of follow_up",
             ylab ="Overall survival probability",
             nrisk_table_variables = c("cum.n.event","pct.risk","n.censor"),
             km_median = "medianci",
             km_band = TRUE,
             km_trans = "event",
             nrisk_table_breaktimeby = 200,
             facet_ncol = 3,
             facet_formula = ~expname)
## Not run: 
#Example 3
ggkmrisktable(data = lung_long, time = "time", status = "DV",
             exposure_metrics =c("ph.karno","pat.karno"),
             exposure_metric_split = "median",
             color_fill = "exptile",
             linetype = "exptile",
             groupvar1 = "Endpoint",
             groupvar2 = "expname",
             xlab = "Time of follow_up",
             ylab ="Overall survival probability",
             nrisk_table_variables = c("n.event"),
             km_trans = "event",
             km_median = "table",
             km_median_table_pos = "right",
             km_logrank_pvalue = TRUE,
             km_band = TRUE,
             nrisk_table_breaktimeby = 200,
             facet_ncol = 3,
             facet_formula = ~expname)
#Example 4
ggkmrisktable(data=lung_long,
             exposure_metrics = c("ph.karno","age"),
             exposure_metric_split = "median",
             time = "time",
             status ="DV",
             color_fill = "ph.ecog",
             linetype = "ph.ecog",
             groupvar1 = "Endpoint",
             groupvar2 = "expname",
             groupvar3 = "exptile",
             nrisk_filterout0 = FALSE,
             nrisk_table_breaktimeby = 200,
             km_logrank_pvalue = TRUE,
             km_median = "table",
             km_median_table_pos = "left",
             facet_formula = ~expname+exptile)
#Example 5

ggkmrisktable(data=lung_long,
             exposure_metrics = c("ph.karno","age"),
             exposure_metric_split = "none",
              color_fill = "facetdum",
             linetype = "none",
             nrisk_table_variables = c("n.risk", "pct.risk", "n.event", "cum.n.event", "n.censor"),
              km_median = "table",
              nrisk_position_scaler = 0.1
             )             
             

## End(Not run)

ggquickeda documentation built on June 22, 2024, 11:30 a.m.