Add secondary malignancy plots
This adds some plots to show data for the secondary malignacies.
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.RData
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.RData
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.Rhistory
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.Rhistory
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survival_*
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*.png
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*.csv
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*.csv
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@ -10,6 +10,11 @@ survival.R
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Source this file and call one of the plot functions to show plot in R.
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Source this file and call one of the plot functions to show plot in R.
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`sma_plot_file_surv()` will save all plots to files.
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`sma_plot_file_surv()` will save all plots to files.
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secmal.R
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--------
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This file contains the secondary malignancy plots. You can call the
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functions in R or `sma_plot_file_secmal()` to save them to files.
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plot_survival.R
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plot_survival.R
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---------------
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---------------
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Special script to generate all plots and save them in files.
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Special script to generate all plots and save them in files.
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87
secmal.R
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secmal.R
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# Secondary malignancies calculations
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#
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# License: GPL version 3
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# Jens Mathis Sauer (c) 2020
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source("utils.R")
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sma_init()
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# Setup survival object
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surv_sec <- Surv(time = secmal$time_at_risk, event = secmal$time_at_risk_status)
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# plot cummulative events
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sma_plot_secmal_event <- function() {
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ggsurvplot(survfit(surv_sec ~ 1), data = secmal, xscale = "d_y",
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title = "Secondary malignacies",
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fun = "event",
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break.time.by = sma_break.time.by,
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surv.median.line = "hv",
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risk.table = "nrisk_cumevents",
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ggtheme = theme_bw())
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}
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# plot cummulative hazard
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sma_plot_secmal_haz <- function() {
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ggsurvplot(survfit(surv_sec ~ 1), data = secmal, xscale = "d_y",
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title = "Secondary malignacies",
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fun = "cumhaz",
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break.time.by = sma_break.time.by,
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risk.table = "abs_pct",
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ggtheme = theme_bw())
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}
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# plot cummulative events per sex
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sma_plot_secmal_event_sex <- function() {
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ggsurvplot(survfit(surv_sec ~ sex, data = secmal), data = secmal, xscale = "d_y",
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title = "Secondary malignacies",
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fun = "event",
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break.time.by = sma_break.time.by,
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surv.median.line = "hv",
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risk.table = "nrisk_cumevents",
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pval = TRUE,
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ggtheme = theme_bw())
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}
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# plot cummulative hazard per sex
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sma_plot_secmal_haz_sex <- function() {
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ggsurvplot(survfit(surv_sec ~ sex, data = secmal), data = secmal, xscale = "d_y",
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title = "Secondary malignacies",
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fun = "cumhaz",
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surv.median.line = "hv",
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break.time.by = sma_break.time.by,
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risk.table = "abs_pct",
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pval = TRUE,
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ggtheme = theme_bw())
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}
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# plot cummulative events per diagnosis
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sma_plot_secmal_event_dx <- function() {
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ggsurvplot(survfit(surv_sec ~ diagnosis, data = secmal), data = secmal, xscale = "d_y",
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title = "Secondary malignacies",
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fun = "event",
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break.time.by = sma_break.time.by,
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risk.table = "nrisk_cumevents",
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pval = TRUE,
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ggtheme = theme_bw())
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}
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# plot cummulative hazard per diagnosis
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sma_plot_secmal_haz_dx <- function() {
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ggsurvplot(survfit(surv_sec ~ diagnosis, data = secmal), data = secmal, xscale = "d_y",
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title = "Secondary malignacies",
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fun = "cumhaz",
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break.time.by = sma_break.time.by,
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risk.table = "abs_pct",
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pval = TRUE,
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ggtheme = theme_bw())
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}
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# Write secondary malignancy plots to files
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sma_plot_file_secmal <- function() {
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sma_plot_file("secmal_event.png", png, sma_plot_secmal_event)
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sma_plot_file("secmal_haz.png", png, sma_plot_secmal_haz)
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sma_plot_file("secmal_event_sex.png", png, sma_plot_secmal_event_sex)
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sma_plot_file("secmal_haz_sex.png", png, sma_plot_secmal_haz_sex)
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sma_plot_file("secmal_event_dx.png", png, sma_plot_secmal_event_dx)
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sma_plot_file("secmal_haz_dx.png", png, sma_plot_secmal_haz_dx)
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}
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