nomogram.crr {QHScrnomo}

Construct a Nomogram for a Competing Risks Regression Model

Description

Draws a partial nomogram from a crr.fit object that can be used to manually obtain predicted values from from a competing risks regression model.

Usage

nomogram.crr(
  fit,
  failtime,
  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 model fit by crr.fit

failtime

A vector of time points to display failure probability axes for.

ci

Should the failure probability be displayed? Defaults to TRUE. If FALSE, the event-free probability is displayed.

...

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 the 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 datadist was not defined for all predictors, it is required 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. Defaults to TRUE.

lp.at

If lp=TRUE, specifies 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.

Value

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

Author(s)

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

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

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, https://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 nomogram.mk6 crr.fit

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")