HH (version 3.1-47)

ae.dotplot: AE (Adverse Events) dotplot of incidence and relative risk

Description

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.

Usage

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)

Arguments

ae

For ae.dotplot, either a data.frame containing the Adverse Event data in long format as described by the detail for xr below, or a data.frame containing the Adverse event data in wide format as described by the detail for aewide below. For logrelrisk, a data.frame containing the first 4 columns of xr described below.

…

For ae.dotplot, all the arguments listed in the calling sequence for ae.ddotplot.long and possibly standard panel function arguments.

For the other functions, just standard panel function arguments.

xr

• RAND: treatment as randomized (factor).

• 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.

• 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.

aewide

• Event: adverse event symptom name (factor).

• N.A, N.B: number of patients in treatment groups A and B.

• AE.A, AE.B: number of patients in treatment groups A and B for whom the event Event was observed.

• PCT.A, PCT.B: AE.A/N.A and AE.B/N.B as a percent.

• Relative.Risk: Relative risk defined as PCT.B divided by PCT.A.

• 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.

A.name, B.name

Names of treatment groups (in x$RAND).

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 ae.dotplot.

cex

The character expansion for the points in the left and right plots.

position.left, position.right

position of the left and right plots. This argument is use in S-Plus only, not in R. See the discussion of position in

key.y

Position of the key (legend) in the combined plot. This is the y argument of the key.

crit.value

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.

CI.percent

Confidence percent associated with the crit.value Defaults to 95. User is responsible for specifying both crit.value and CI.percent consistently.

x, y, groups, lwd

standard panel function arguments.

lower, upper

xr$logrelriskCI.lower and xr$logrelriskCI.upper inside the panel functions.

Value

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.

Details

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.

References

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

See Also

AEdotplot for a three-panel version that also has an associated shiny app.

Examples

# 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
##
## 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)
# }