Evaluate Treatment Selection Biomarkers

A suite of descriptive and inferential methods designed to evaluate one or more biomarkers for their ability to guide patient treatment recommendations. Package includes functions to assess the calibration of risk models; and plot, evaluate, and compare markers. Please see the reference Janes H, Brown MD, Huang Y, et al. (2014) for further details.

This R package includes a suite of descriptive and inferential methods designed to evaluate one or more biomarkers for their ability to guide patient treatment recommendations. relevant functions are:

  • trtsel_measures for evaluating the performance of a user-specified marker-based treatment rule
  • trtsel for creating trtsel objects
  • plot.trtsel for plotting risk curves and more
  • evaluate.trtsel for evaluating marker performance
  • calibrate.trtsel for assessing model calibration
  • compare.trtsel to compare two trtsel objects.

To dowload the package from CRAN, type:


To download and install the most recent version of the package directly from github, type:

if (!require("devtools")) install.packages("devtools")
devtools::install_github("TreatmentSelection", "mdbrown")

A manuscript describing the methods employed in the package can be found here and a brief tutorial is available here.


TreatmentSelection 1.1.3

  • tweaked estimation of Var(Delta) for subcohort designs.

TreatmentSelection 1.1.2

  • added plot.type 'selection impact'. see ?plot.trtsel for more information.

  • fixed a small bug that caused warnings when plotting a trtsel object created from providing fixed risk estimates.

TreatmentSelection 1.1.1

  • eval.trtsel: modeled estimates of event rates calculated for subcohort designs had a bug. Calculations now are correct.

  • eval.trtsel: also fixed bug where event rates werent calculated when bootstraps = 0.

  • eval.trtsel: fixed event rate labeling bug that swapped trt all for trt none.

  • plot.trtsel: added new plot.type that plots event rate under different marker based treatment assignment rules vs. F_delta(v).

  • plot.trtsel: the mean trt effect line for subcohort designs was not weighted correctly. this has been fixed for continuous and discrete markers.

  • plot.trtsel: fixed a bug building plots for subcohort designs with discrete markers

  • fixed various small things so that the package now has no warnings from R CMD Check

  • added manual files for tsdata_scc and tsdata_cc

  • calibrate.trtsel: fixed bug when calibrating models fit using stratified case-control data.

TreatmentSelection 2.0.3

Note: This is a large update with many changes. Although, the estimation methods remain the same, many of the functions inputs have changed. This is to accomodate multivariate models and survival outcomes.

  • Addition of 'trtsel_measures': a simple function for evaluating the performance of a user-specified marker-based treatment rule.
  • Input formulas into trtsel objects instead of univariate marker information. This allows for the evaluation of multivariate models.
  • The package now allows for survival outcomes.
  • Bias-correction to adjust for over-optimism that comes from evaluating models on the same data that were used to fit model parameters. eval.trtsel and compare.trtsel now implements a bootstrap bias-correction method.

TreatmentSelection 2.0.4

  • adjusted estimate of event rate under marker-based trt.

TreatmentSelection 2.1.0

Two key additions:

  • allow continuous and time-to-event outcomes
  • allow a user to evaluate models with more than one marker

One minor additions:

  • updated the estimator of event rate under marker based treatment.

TreatmentSelection 2.1.1

  • Update trtsel man files specifying that larger values of a continuous outcome should be associated with worse outcomes.

Reference manual

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2.1.1 by Marshall Brown, 4 years ago


Browse source code at https://github.com/cran/TreatmentSelection

Authors: Marshall Brown and Holly Janes

Documentation:   PDF Manual  

GPL-3 license

Imports ggplot2, survival, binom, grid

See at CRAN