Support functions for the AEdotplot.
# S3 method for data.frame
AEdotplot(xr, ...,
conditionVariable=NULL,
conditionName=deparse(substitute(xr)),
useCondition=!is.null(conditionVariable),
sub=list(conditionName, cex=.7)) # S3 method for AElogrelrisk
AEdotplot(xr,
A.name=paste(levels(xr$RAND)[1], " (n=", xr$SN[1], ")", sep=""),
B.name=paste(levels(xr$RAND)[2], " (n=", xr$SN[2], ")", sep=""),
col.AB=c("red","blue"), pch.AB=c(16,17),
main=if (sortbyRelativeRisk)
list("Most Frequent On-Therapy Adverse Events Sorted by Relative Risk",
cex=1)
else
list("Most Frequent On-Therapy Adverse Events", cex=1),
cex.AB.points=NULL, cex.AB.y.scale=.6, cex.x.scale=.6,
panel.widths=c(.55, .22, .23),
key.y=-.2, CI.percent=95,
conditionName=deparse(substitute(xr)),
sortbyRelativeRisk=TRUE,
...,
sub=list(conditionName, cex=.7),
par.strip.text=list(cex=.7))
# S3 method for AEtable
AEdotplot(xr, ..., useCondition=TRUE,
sub="sub for AEsecond")
# S3 method for AEdotplot
print(x, ...,
main=attr(x, "main"),
sub=attr(x,"sub"),
ae.key=attr(x, "ae.key"),
panel.widths=attr(x,"panel.widths"),
AEtable=TRUE)
# S3 method for AEdotplot
c(..., panel.widths=attr(aedp[[1]], "panel.widths"),
par.strip.text=list(cex=.7))
AElogrelrisk(ae,
A.name=levels(ae$RAND)[1],
B.name=levels(ae$RAND)[2],
crit.value=1.96,
sortbyRelativeRisk=TRUE, ...,
sortbyVar=c("PREF", ## Event name
"PCT", ## Percent
"SN", ## Number of Patients
"SAE", ## Number of Observed Events
"relrisk", ## Relative Risk (RR)
"ase.logrelrisk", ## Asymptotic Standard Error(log(RR))
"relriskCI.lower", ## Confidence Interval Bounds
"relriskCI.upper"),
sortbyVarBegin=1) ## 1 for A treatment, 2 for B treatment
AEmatchSortorder(AEstandard,
AEsecond,
AEsecond.AEtable=attr(AEsecond, "AEtable"),
levels.order=
lapply(attr(AEstandard,"AEtable"),
function(AEsubtable) levels(AEsubtable$PREF)),
main.second=list(paste("Most Frequent On-Therapy Adverse Events",
"Sorted to Match First Table"),
cex=1))
# S3 method for AEdotplot
update(object, ...)
For AElogrelrisk, a data.frame containing at least the
first 4 columns of xr.
For the formula method documented in
AEdotplot, a formula of the form
AE ~ nAE/nTRT | OrgSys, where the condition variable is
optional.
For the formula method only, the variable names are not restricted.
For the other methods, xr is a data.frame containing the Adverse
Event data in long format. It must have variables named
RAND: treatment as randomized (factor with exactly two levels).
PREF: adverse event symptom name (factor).
SN: number of patients in treatment group.
SAE: number of patients in each group for whom the event
PREF was observed.
If the xr object is a AElogrelrisk object, then it must
also have variables
PCT: SAE/SN as a percent.
relrisk: Relative risk defined as PCT for the B
treatment divided by PCT for the A treatment.
logrelrisk: natural logarithm of relrisk.
ase.logrelrisk: asymptotic standard error of logrelrisk.
logrelriskCI.lower, logrelriskCI.upper: confidence interval for
logrelrisk.
relriskCI.lower, relriskCI.upper: back transform of the CI for
the log relative risk into the relative risk scale.
logical. If TRUE, then make the
Adverse Events an ordered factor ordering by relative risk.
If FALSE, then make the
Adverse Events an ordered factor retaining the order of the input levels.
Vector of same length as number of rows in
xr, it may be one of the columns in xr in which case
its full name in the form xr$varname must be used. It will be used to
split the data.frame into partitions.
It may be used to partition the plot,
for example by organ system or by gender.
Character. Name to be used in left.strip.
logical. If FALSE, then a non-NULL
ConditionVariable won't be used.
object to be printed.
Vector of three non-negative numerics that sum to 1. These are the widths of each of the three panels in the output plot. The left panel contains the AE names as y-tick labels and the Percent plot. The middle panel contains the Relative Risk plot. The right panel contains a table of the numerical values of number of patients for each treatment, number of adverse events for each treatment, and relative risk. Setting the third value to 0 suppresses the table of numerical values from the display.
logical. For the print.AEdotplot function.
If TRUE (the default), display all three panels. If
FALSE, then display only the Percent and Relative Risk plots.
Main title and subtitle for the combined plot
in AEdotplot.
Main title for second plot whose sort order has been changed to match the first plot.
Names of treatment groups (in x$RAND).
color, plotting character and character expansion for the individual points on the left plot.
Character expansion for the left tick labels (the Adverse Effects names).
Character expansion for the x-axis tick labels.
Position of the key (legend) in the combined plot. This
is the y argument of the key.
See the discussion of the key argument to xyplot in
xyplot
is a key as described in xyplot.
Arguments
that force the Adverse Events in the panels of AEsecond to
have the same sort order levels.order of PREF as the
panels of AEstandard. AEstandard and AEsecond
are two "AEdotplot" objects with the same set of panels and
the same Adverse Events in corresponding panels.
AEsecond.AEtable is the AEtable object from
AEsecond. levels.order is the new order for
AEsecond; normally the same order as in AEprimary.
Critical value used to compute confidence intervals
on the log relative risk. Defaults to 1.96. User is responsible
for specifying both crit.value and CI.percent
consistently.
Confidence percent associated with the
crit.value Defaults to 95. User is responsible for
specifying both crit.value and CI.percent
consistently.
For AEdotplot and AEdotplot.data.frame,
all the arguments listed in the
calling sequence for AEddotplot.AErelrisk..
For c.AEdotplot, one or more "AEdotplot" objects.
For print.AEdotplot, the … arguments are ignored.
Specify which variable will be used to provide the sort order in the plot. The names are the internal names for the variables.
1 for A treatment, 2 for B treatment.
An AEdotplot object. The update method
updates the components of each of the constituent trellis
objects. It does not update the "main" and "sub"
attributes (nor any other attribute) of the AEdotplot object.
Default value for strip labels. See
xyplot
for details.
The primary interest is in the display of the plot.
The function returns
an AEdotplot object which is a list of three trellis
objects,
one for the the Percent plot, one for the Relative Risk plot, and one
for
the Text plot containing the table of input values. The object has
attributes
main and sub hold the main and subtitles. Each must
be a list containing the text in the first component.
ae.key is a key as described in
xyplot.
n.events is a vector containing the number of events in
each subpanel.
panel.widths is a vector of relative widths of the three components
of
the graph. The numbers must sum to one. Zero values are permitted.
The first width includes the left axis and the Percent plot. The second
is the Relative Risk plot, and the third is the plot of the table
values.
AEtable is a table containing the data plotted on its row.
The first panel is an ordinary dotplot of the percent of AE observed for each treatment by AE.
The second panel shows relative risk of an event on the Treatment B arm
(usually the active compound)
relative to the Treatment A arm (usually the placebo), with 95% confidence
intervals for a
By default the AEdotplot function sorts the events by relative risk.
To retain the sort order implied by the levels of the AE
factor, specify the argument sortbyRelativeRisk=FALSE.
To control the sort order, make the AE factor in the input dataset
an ordered factor
and specify the levels in the order you want.
The third panel shows the numerical values of the number and percent
of observed events on each arm and the relative risk.
The display of third panel can be suppressed by specifying the
panel.widths argument.
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
# NOT RUN {
## 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
## OrgSys Organ System
##
## Input sort order is PREF/RAND
data(aeanonym)
head(aeanonym)
## variable names are hard-wired in the program
## names(aeanonym) <- c("RAND", "PREF", "SAE", "SN", "OrgSys")
## Calculate log relative risk and confidence intervals (95<!-- % by default). -->
## AElogrelrisk sets the sort order for PREF to match the relative risk.
aeanonymr <- AElogrelrisk(aeanonym) ## PREF sorted by relative risk
head(aeanonymr)
class(aeanonymr$PREF)
levels(aeanonymr$PREF)
AEdotplot(aeanonym)
AEdotplot(aeanonym, sort=FALSE)
AEdotplot(aeanonym, conditionVariable=aeanonym$OrgSys)
aefake <- rbind(cbind(aeanonym, group="ABC"), cbind(aeanonym, group="DEF"))
aefake$SAE[67:132] <- sample(aefake$SAE[67:132])
aefake$OrgSys.group <- with(aefake, interaction(OrgSys, group))
## fake 2
KEEP <- aefake$OrgSys %in% c("GI","Resp")
<!-- %% KEEP <- aefake$OrgSys %in% c("GI","Resp") -->
AEfakeGR <- AEdotplot(aefake[KEEP,], conditionVariable=aefake$OrgSys.group[KEEP],
sub=list("ABC and DEF have different sort orders for PREF", cex=.7))
AEfakeGR ## ABC and DEF have different sort orders for PREF
AEfakeGR1 <- AEdotplot(aefake[KEEP & (1:132) <= 66,],
conditionVariable=aefake$OrgSys.group[KEEP & (1:132) <= 66])
AEfakeGR2 <- AEdotplot(aefake[KEEP & (1:132) >= 67,],
conditionVariable=aefake$OrgSys.group[KEEP & (1:132) >= 67])
AEfakeGR1
AEfakeGR2
AEfakeMatched <- AEmatchSortorder(AEfakeGR1, AEfakeGR2)
update(do.call(c, AEfakeMatched),
main="ABC sorted by Relative Risk; DEF matches ABC order")
# }
# NOT RUN {
## Please see ?AEdotplot for examples using the formula method
##
## Many more examples are in demo("AEdotplotManyExamples")
# }
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