4 Formatting data

For all of the function to run, the data must be in the long format. This means that each event must be on a new row. An event would be a single point, a line segment, or an arrow. If a study unit has multiple events occur they must be recorded over multiple rows. Often times data is given in the long format (eg. One row per patient).

4.1 Long data

Here is an example data.frame in the long format.


wide_example <- structure(list(ID = c("ID:001", "ID:002", "ID:003"), Date.begin.Treatment = structure(c(14307, 
14126, 15312), class = "Date"), AE = structure(c(16133, 14491, 
NA), class = "Date"), SAE = structure(c(16316, NA, 16042), class = "Date"), 
    Death.date = structure(c(16499, NA, 17869), class = "Date"), 
    Response1 = c("SD", "SD", NA), Response1.Start = structure(c(14745, 
    14345, NA), class = "Date"), Response1.End = structure(c(15111, 
    14418, NA), class = "Date"), Response2 = c("CR", "PR", NA
    ), Response2.Start = structure(c(15768, 14674, NA), class = "Date"), 
    Response2.End = structure(c(16133, 14856, NA), class = "Date"), 
    Response3 = c(NA, "CR", NA), Response3.Start = structure(c(NA, 
    14856, NA), class = "Date"), Response3.End = structure(c(NA, 
    15587, NA), class = "Date"), Last.follow.up = structure(c(16499, 
    17048, 17869), class = "Date")), class = "data.frame", row.names = c(NA, 
-3L))

ID	Date.begin.Treatment	AE	SAE	Death.date	Response1	Response1.Start	Response1.End	Response2	Response2.Start	Response2.End	Response3	Response3.Start	Response3.End	Last.follow.up
ID:001	2009-03-04	2014-03-04	2014-09-03	2015-03-05	SD	2010-05-16	2011-05-17	CR	2013-03-04	2014-03-04	NA	NA	NA	2015-03-05
ID:002	2008-09-04	2009-09-04	NA	NA	SD	2009-04-11	2009-06-23	PR	2010-03-06	2010-09-04	CR	2010-09-04	2012-09-04	2016-09-04
ID:003	2011-12-04	NA	2013-12-03	2018-12-04	NA	NA	NA	NA	NA	NA	NA	NA	NA	2018-12-04

All of the dates need to be converted to time. For each patient the Date.begin.Treatment is the starting point (Time 0)

date_cols <- c("Date.begin.Treatment","AE","SAE",'Death.date','Response1.Start', 'Response1.End','Response2.Start', 'Response2.End',
               'Response3.Start' ,'Response3.End' ,'Last.follow.up') # Getting the columns with dates
wide_example[date_cols] <- lapply(wide_example[date_cols], as.numeric) # Converting to numbers 
wide_example[date_cols] <- round((wide_example[date_cols]-wide_example$Date.begin.Treatment)/365.25,1) #Calcuating the time in years since the start of treatment
knitr::kable(wide_example)

ID	AE	SAE	Death.date	Response1	Response1.Start	Response1.End	Response2	Response2.Start	Response2.End	Response3	Response3.Start	Response3.End	Last.follow.up
ID:001	5	5.5	6	SD	1.2	2.2	CR	4.0	5	NA	NA	NA	6
ID:002	1	NA	NA	SD	0.6	0.8	PR	1.5	2	CR	2	4	8
ID:003	NA	2.0	7	NA	NA	NA	NA	NA	NA	NA	NA	NA	7

The wide data can be used to create the bars of the swimmer plot

plot <- swimmer_plot(df=wide_example,id='ID',end='Last.follow.up',col='black',fill='grey')
plot