nomogram.crr: Draw a Nomogram

In jixccf/QHScrnomo: Construct nomograms for competing risk models

Description

Draws a partial nomogram that can be used to manually obtain predicted values from a regression model that was fitted with rms in effect.

Usage

nomogram.crr(
  fit,
  failtime = NULL,
  ci = TRUE,
  ...,
  adj.to,
  lp = TRUE,
  lp.at,
  lplabel = "Linear Predictor",
  fun.at,
  fun.lp.at,
  funlabel = "Predicted Value",
  fun.side,
  interact = NULL,
  intercept = 1,
  conf.int = FALSE,
  col.conf = c(1, 12),
  conf.space = c(0.08, 0.2),
  conf.lp = c("representative", "all", "none"),
  est.all = TRUE,
  abbrev = FALSE,
  minlength = 4,
  maxscale = 100,
  nint = 10,
  label.every = 1,
  force.label = FALSE,
  xfrac = 0.35,
  cex.axis = 0.85,
  cex.var = 1,
  col.grid = FALSE,
  vnames = c("labels", "names"),
  varname.label = TRUE,
  varname.label.sep = "=",
  ia.space = 0.7,
  tck = -0.009,
  lmgp = 0.4,
  omit = NULL,
  naxes,
  points.label = "Points",
  total.points.label = "Total Points",
  total.sep.page = FALSE,
  total.fun,
  verbose = FALSE,
  total.min,
  total.max,
  mikeomit = NULL
)

Arguments

fit	a competing risks regression model fit that was created with function crr.fit.
failtime	the expected failure time for calculating cumalative incidence.
ci	logical flag to output cumulative incidence or event free probability if setting FALSE.
...	settings of variables to use in constructing axes. If datadist was in effect, the default is to use pretty(total range, nint) for continuous variables, and the class levels for discrete ones. For legend.nomabbrev, ... specifies optional parameters to pass to legend. Common ones are bty = "n" to suppress drawing the box. You may want to specify a non-proportionally spaced font (e.g., courier) number if abbreviations are more than one letter long. This will make the abbreviation definitions line up (e.g., specify font = 2, the default for courier). Ignored for print.
adj.to	If you didn't define datadist for all predictors, you will have to define adjustment settings for the undefined ones, e.g. adj.to=list(age=50, sex="female").
lp	Set to FALSE to suppress creation of an axis for scoring X beta.
lp.at	If lp=TRUE, lp.at may specify a vector of settings of X beta. Default is to use pretty(range of linear predictors, nint).
lplabel	label for linear predictor axis. Default is "Linear Predictor".
fun.at	function values to label on axis. Default fun evaluated at lp.at. If more than one fun was specified, using a vector for fun.at will cause all functions to be evaluated at the same argument values. To use different values, specify a list of vectors for fun.at, with elements corresponding to the different functions (lists of vectors also applies to fun.lp.at and fun.side).
fun.lp.at	If you want to evaluate one of the functions at a different set of linear predictor values than may have been used in constructing the linear predictor axis, specify a vector or list of vectors of linear predictor values at which to evaluate the function. This is especially useful for discrete functions. The presence of this attribute also does away with the need for nomogram to compute numerical approximations of the inverse of the function. It also allows the user-supplied function to return factor objects, which is useful when e.g. a single tick mark position actually represents a range. If the fun.lp.at parameter is present, the fun.at vector for that function is ignored.
funlabel	label for fun axis. If more than one function was given but funlabel is of length one, it will be duplicated as needed. If fun is a list of functions for which you specified names (see the final example below), these names will be used as labels.
fun.side	a vector or list of vectors of side parameters for the axis function for labeling function values. Values may be 1 to position a tick mark label below the axis (the default), or 3 for above the axis. If for example an axis has 5 tick mark labels and the second and third will run into each other, specify fun.side=c(1,1,3,1,1) (assuming only one function is specified as fun).
interact	When a continuous variable interacts with a discrete one, axes are constructed so that the continuous variable moves within the axis, and separate axes represent levels of interacting factors. For interactions between two continuous variables, all but the axis variable must have discrete levels defined in interact. For discrete interacting factors, you may specify levels to use in constructing the multiple axes. For continuous interacting factors, you must do this. Examples: interact=list(age=seq(10,70,by=10), treat=c("A","B","D")).
intercept	for models such as the ordinal logistic model with multiple intercepts, specifies which one to use in evaluating the linear predictor.
conf.int	confidence levels to display for each scoring. Default is FALSE to display no confidence limits. Setting conf.int to TRUE is the same as setting it to c(0.7, 0.9), with the line segment between the 0.7 and 0.9 levels shaded using gray scale.
col.conf	colors corresponding to conf.int. Use fractions for gray scale (for UNIX S-PLUS).
conf.space	a 2-element vector with the vertical range within which to draw confidence bars, in units of 1=spacing between main bars. Four heights are used within this range (8 for the linear predictor if more than 16 unique values were evaluated), cycling them among separate confidence intervals to reduce overlapping.
conf.lp	default is "representative" to group all linear predictors evaluated into deciles, and to show, for the linear predictor confidence intervals, only the mean linear predictor within the deciles along with the median standard error within the deciles. Set conf.lp="none" to suppress confidence limits for the linear predictors, and to "all" to show all confidence limits.
est.all	To plot axes for only the subset of variables named in ...{}, set est.all=FALSE. Note: This option only works when zero has a special meaning for the variables that are omitted from the graph.
abbrev	Set to TRUE to use the abbreviate function to abbreviate levels of categorical factors, both for labeling tick marks and for axis titles. If you only want to abbreviate certain predictor variables, set abbrev to a vector of character strings containing their names.
minlength	applies if abbrev=TRUE. Is the minimum abbreviation length passed to the abbreviate function. If you set minlength=1, the letters of the alphabet are used to label tick marks for categorical predictors, and all letters are drawn no matter how close together they are. For labeling axes (interaction settings), minlength=1 causes minlength=4 to be used.
maxscale	default maximum point score is 100
nint	number of intervals to label for axes representing continuous variables. See pretty.
label.every	Specify label.every=i to label on every ith tick mark.
force.label	set to TRUE to force every tick mark intended to be labeled to have a label plotted (whether the labels run into each other or not)
xfrac	fraction of horizontal plot to set aside for axis titles
cex.axis	character size for tick mark labels
cex.var	character size for axis titles (variable names)
col.grid	If col.grid=1, no gray scale is used, but an ordinary line is drawn. If 0<col.grid<1, a col (gray scale) of col.grid is used to draw vertical reference lines for major axis divisions and col.grid/2 for minor divisions. The default is col.grid=FALSE, i.e., reference lines are omitted. Specifying col.grid=TRUE is the same as specifying a gray scale level of col.grid=.2 (5 for Windows S-PLUS).
vnames	By default, variable labels are used to label axes. Set vnames="names" to instead use variable names.
varname.label	In constructing axis titles for interactions, the default is to add "(interacting.varname=level)" on the right. Specify varname.label=FALSE to instead use "(level)".
varname.label.sep	If varname.label=TRUE, you can change the separator to something other than = by specifying this parameter.
ia.space	When multiple axes are draw for levels of interacting factors, the default is to group combinations related to a main effect. This is done by spacing the axes for the second to last of these within a group only 0.7 (by default) of the way down as compared with normal space of 1 unit.
tck	see tck under par
lmgp	spacing between numeric axis labels and axis (see par for mgp)
omit	vector of character strings containing names of variables for which to suppress drawing axes. Default is to show all variables.
naxes	maximum number of axes to allow on one plot. If the nomogram requires more than one "page", the "Points" axis will be repeated at the top of each page when necessary.
points.label	a character string giving the axis label for the points scale
total.points.label	a character string giving the axis label for the total points scale
total.sep.page	set to TRUE to force the total points and later axes to be placed on a separate page
total.fun	a user-provided function that will be executed before the total points axis is drawn. Default is not to execute a function. This is useful e.g. when total.sep.page=TRUE and you wish to use locator to find the coordinates for positioning an abbreviation legend before it's too late and a new page is started (i.e., total.fun=function()print(locator(1))).
verbose	set to TRUE to get printed output detailing how tick marks are chosen and labeled for function axes. This is useful in seeing how certain linear predictor values cannot be solved for using inverse linear interpolation on the (requested linear predictor values, function values at these lp values). When this happens you will see NAs in the verbose output, and the corresponding tick marks will not appear in the nomogram.
total.min	Setting the minimal value in the total point axis on the nomogram.
total.max	Setting the maximal value in the total point axis.
mikeomit	The predictor variables specified by their names here will not be shown in the nomogram. The predicted outcome based on this reduced nomogram would be the same as if users were using the full version of the nomogram by entering the some values for the predictors remaining in the reduced nomogram but adjusted values for the hiden predictors so that 0 points will be achieved from these hiden predictor variables in the full nomogram.

Details

The nomogram does not have lines representing sums, but it has a reference line for reading scoring points (default range 0–100). Once the reader manually totals the points, the predicted values can be read at the bottom. Non-monotonic transformations of continuous variables are handled (scales wrap around), as are transformations which have flat sections (tick marks are labeled with ranges).

Value

a list of class "nomogram" that contains information used in plotting the axes. Please see nomogram for details.

Note

internal use only

Author(s)

Frank Harrell
Department of Biostatistics
Vanderbilt University
[e-mail]

Draw a Competing Risks Nomogram

Draws a partial nomogram adjusting for competing risks for a cox ph survival model.

Changhong Yu, Michael Kattan, Ph.D
Department of Quantitative Health Sciences
Cleveland Clinic

References

Banks J: Nomograms. Encylopedia of Statistical Sciences, Vol 6. Editors: S Kotz and NL Johnson. New York: Wiley; 1985.

Lubsen J, Pool J, van der Does, E: A practical device for the application of a diagnostic or prognostic function. Meth. Inform. Med. 17:127–129; 1978.

Wikipedia: Nomogram, http://en.wikipedia.org/wiki/Nomogram.

Michael W. Kattan, Glenn Heller and Murray F. Brennan (2003). A competing-risks nomogram
for sarcoma-specific death following local recurrence. Statistics in Medicine. Stat Med. 2003;22:3515-3525.

See Also

nomogram, crr.fit, pred2.crr, nomo2.crr

Examples

data(prostate.dat)
dd <- datadist(prostate.dat)
options(datadist = "dd")
prostate.f <- cph(Surv(TIME_EVENT,EVENT_DOD == 1) ~ TX  + rcs(PSA,3) +
           BX_GLSN_CAT +  CLIN_STG + rcs(AGE,3) +
           RACE_AA, data = prostate.dat,
           x = TRUE, y= TRUE, surv=TRUE,time.inc = 144)
prostate.crr <- crr.fit(prostate.f,cencode = 0,failcode = 1)
## make a CRR nomogram
nomogram.crr(prostate.crr,failtime = 120,lp=FALSE,
funlabel = "Predicted 10-year cumulative incidence")

jixccf/QHScrnomo documentation built on Dec. 21, 2021, 12:08 a.m.