ae.dotplot | R Documentation |
A two-panel display of the most
frequently occurring AEs in the active arm of a clinical
study. The first panel displays their incidence by
treatment group, with different symbols for each
group. The second panel displays the relative risk
of an event on the active arm relative to the
placebo arm, with 95% confidence intervals for a 2\times2
table.
By default, the AEs are ordered by
relative risk so that events with the largest
increases in risk for the active treatment are
prominent at the top of the display. See the Details section for
information
on changing the sort order.
ae.dotplot(ae, ...)
ae.dotplot.long(xr,
A.name = levels(xr$RAND)[1], B.name = levels(xr$RAND)[2],
col.AB = c("red","blue"), pch.AB = c(16, 17),
main.title = paste("Most Frequent On-Therapy Adverse Events",
"Sorted by Relative Risk"),
main.cex = 1,
cex.AB.points = NULL, cex.AB.y.scale = 0.6,
position.left = c(0, 0, 0.7, 1), position.right = c(0.61, 0, 0.98, 1),
key.y = -0.2, CI.percent=95)
logrelrisk(ae, A.name, B.name, crit.value=1.96)
panel.ae.leftplot(x, y, groups, col.AB, ...)
panel.ae.rightplot(x, y, ..., lwd=6, lower, upper, cex=.7)
panel.ae.dotplot(x, y, groups, ..., col.AB, pch.AB, lower, upper) ## R only
aeReshapeToLong(aewide)
ae |
For |
... |
For For the other functions, just standard panel function arguments. |
xr |
|
aewide |
|
A.name , B.name |
Names of treatment groups (in |
col.AB , pch.AB , cex.AB.points |
color, plotting character and character expansion for the individual points on the left plot. |
cex.AB.y.scale |
Character expansion for the left tick labels (the symptom names). |
main.title , main.cex |
Main title and character expansion for the
combined plot in |
cex |
The character expansion for the points in the left and right plots. |
position.left , position.right |
|
key.y |
Position of the key (legend) in the combined plot. This
is the |
crit.value |
Critical value used to compute confidence intervals
on the log relative risk. Defaults to 1.96. User is responsible
for specifying both |
CI.percent |
Confidence percent associated with the
|
x , y , groups , lwd |
standard panel function arguments. |
lower , upper |
|
The second panel shows relative risk of an event on the active arm
(treatment B)
relative to the placebo arm (treatment A), with 95% confidence
intervals for a 2\times2
table. Confidence intervals on the log
relative risk are calculated using the asymptotic standard error
formula given as Equation 3.18 in Agresti A., Categorical Data
Analysis. Wiley: New York, 1990.
By default the ae.dotplot
function sorts the events by relative risk.
To change the sort order, you must redefine the ordering of the
ordered factor PREF
. See the examples below.
logrelrisk
takes an input data.frame of the form x
described in the argument list and returns a data.frame consisting of
the input argument with additional columns as described in the
argument xr
. The result column of symptom names PREF
is
an ordered factor, with the order specified by the relative risk.
ae.leftplot
returns a "trellis"
object containing a
horizontal dotplot of the percents against each of the symptom names.
ae.rightplot
returns a "trellis"
object containing a
horizontal plot on the log scale of the relative risk confidence
intervals against each of the symptom names.
ae.dotplot
calls both ae.leftplot
and ae.rightplot
and combines their plots into a single display with a single set of
left axis labels, a main title, and a key. The value returned
invisibly is a list of the full left trellis object and the right
trellis object with its left labels blanked out. Printing the value
will not usually be interesting as the main title and key are not
included.
It is better to call ae.dotplot
directly, perhaps with a change
in some of the positioning arguments.
Richard M. Heiberger <rmh@temple.edu>
Ohad Amit, Richard M. Heiberger, and Peter W. Lane. (2008) “Graphical Approaches to the Analysis of Safety Data from Clinical Trials”. Pharmaceutical Statistics, 7, 1, 20–35. https://onlinelibrary.wiley.com/doi/10.1002/pst.254
AEdotplot
for a three-panel version that also has
an associated shiny app.
## variable names in the input data.frame aeanonym
## RAND treatment as randomized
## PREF adverse event symptom name
## SN number of patients in treatment group
## SAE number of patients in each group for whom the event PREF was observed
##
## Input sort order is PREF/RAND
data(aeanonym)
head(aeanonym)
## Calculate log relative risk and confidence intervals (95% by default).
## logrelrisk sets the sort order for PREF to match the relative risk.
aeanonymr <- logrelrisk(aeanonym) ## sorts by relative risk
head(aeanonymr)
## construct and print plot on current graphics device
ae.dotplot(aeanonymr,
A.name="TREATMENT A (N=216)",
B.name="TREATMENT B (N=431)")
## export.eps(h2("stdt/figure/aerelrisk.eps"))
## This looks great on screen and exports badly to eps.
## We recommend drawing this plot directly to the postscript device:
##
## trellis.device(postscript, color=TRUE, horizontal=TRUE,
## colors=ps.colors.rgb[
## c("black", "blue", "red", "green",
## "yellow", "cyan","magenta","brown"),],
## onefile=FALSE, print.it=FALSE,
## file=h2("stdt/figure/aerelrisk.ps"))
## ae.dotplot(aeanonymr,
## A.name="TREATMENT A (N=216)",
## B.name="TREATMENT B (N=431)")
## dev.off()
## To change the sort order, redefine the PREF factor.
## For this example, to plot alphabetically, use the statement
aeanonymr$PREF <- ordered(aeanonymr$PREF, levels=sort(levels(aeanonymr$PREF)))
ae.dotplot(aeanonymr,
A.name="TREATMENT A (N=216)",
B.name="TREATMENT B (N=431)",
main.title="change the main title to reflect the new sort order")
## Not run:
## to restore the order back to the default, use
relrisk <- aeanonymr[seq(1, nrow(aeanonymr), 2), "relrisk"]
PREF <- unique(aeanonymr$PREF)
aeanonymr$PREF <- ordered(aeanonymr$PREF, levels=PREF[order(relrisk)])
ae.dotplot(aeanonymr,
A.name="TREATMENT A (N=216)",
B.name="TREATMENT B (N=431)",
main.title="back to the original sort order")
## smaller artifical example with the wide format
aewide <- data.frame(Event=letters[1:6],
N.A=c(50,50,50,50,50,50),
N.B=c(90,90,90,90,90,90),
AE.A=2*(1:6),
AE.B=1:6)
aewtol <- aeReshapeToLong(aewide)
xr <- logrelrisk(aewtol)
ae.dotplot(xr)
## End(Not run)
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