ggkmrisktable {ggquickeda}

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)