ae.dotplot {HH} | 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 2x2 table. 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.
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 = "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) panel.ae.dotplot(x, y, groups, ..., col.AB, pch.AB, lower, upper) ## R only aeReshapeToLong(aewide)
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$RAND ). |
col.AB, pch.AB, cex.AB.points |
color, plotting character and character expansion for the individual points on the left plot. |
cex.AB.y.scale |
Character expansion for the left tick labels (the symptom names). |
main.title, main.cex |
Main title and character expansion for the
combined plot in ae.dotplot . |
position.left, position.right |
position of the left and
right plots. This argument is use in S-Plus only, not in R.
See the discussion of position in
print.trellis in R,
print.trellis in S-Plus. |
key.y |
Position of the key (legend) in the combined plot. This
is the y argument of the key . See
key in S-Plus, and the discussion of the
key argument to xyplot in xyplot in
R. |
crit.value |
Critical value used to compute confidence intervals
on the log relative risk. Defaults to 1.96. User is responsible
for specifying both crit.value and CI.percent
consistently. |
CI.percent |
Confidence percent associated with the
crit.value Defaults to 95. User is responsible for
specifying both crit.value and CI.percent
consistently. |
x, y, groups, lwd |
standard panel function arguments. |
lower, upper |
xr$logrelriskCI.lower and
xr$logrelriskCI.upper inside the panel functions. |
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 2x2 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.
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 obect 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. http://www3.interscience.wiley.com/journal/114129388/abstract
## 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 aeanonym <- read.table(hh("datasets/aedotplot.dat"), header=TRUE, sep=",") aeanonym[1:4,] ## Calculate log relative risk and confidence intervals (95 ## logrelrisk sets the sort order for PREF to match the relative risk. aeanonymr <- logrelrisk(aeanonym) aeanonymr[1:4,] ## 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() ## 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)