cdx2cea
is an R package that
implements the cost-effectiveness analysis (CEA) of testing average-risk
Stage II colon cancer patients for the absence of CDX2 biomarker
expression followed by adjuvant chemotherapy.
cdx2cea
is part of the
following manuscript:
The release that accompanies the published article has been archived in zenodo: https://zenodo.org/record/5093594#.YPYyDy1h1qs
You can cite this package like this “we based our analysis using the cdx2cea R package (Alarid-Escudero F, Schrag D, and Kuntz KM 2021)”. Here is the full bibliographic reference to include in your reference list for the manuscript and the package (don’t forget to update the ‘last accessed’ date):
Alarid-Escudero F, Schrag D, Kuntz KM. “CDX2 biomarker testing and adjuvant therapy for stage II colon cancer: An exploratory cost-effectiveness analysis”. Value in Health 2022; 25(3):409-418.
Alarid-Escudero F, Schrag D, Kuntz KM (2021). {cdx2cea}: A cost-efectiveness analysis of testing stage II colon cancer patients for the absence of CDX2 biomarker followed by adjuvant chemotherapy (Version v1.0.0). Zenodo. 10.5281/zenodo.5093594. Last accessed 12 July 2021
devtools
to install cdx2cea
as a package and modify it to
generate your own package# Install release version from CRAN
install.packages("devtools")
# Or install development version from GitHub
# devtools::install_github("r-lib/devtools")
We recommend reading the tutorials on cohort state-rtansition models (cSTMs) in R:
Alarid-Escudero F, Krijkamp EM, Enns EA, Yang A, Hunink MGM, Pechlivanoglou P, Jalal H. An Introductory Tutorial on Cohort State-Transition Models in R Using a Cost-Effectiveness Analysis Example. Medical Decision Making, 2023;43(1):3-20. https://doi.org/10.1177/0272989X221103163
Alarid-Escudero F, Krijkamp EM, Enns EA, Yang A, Hunink MGM, Pechlivanoglou P, Jalal H. A Tutorial on Time-Dependent Cohort State-Transition Models in R using a Cost-Effectiveness Analysis Example. Medical Decision Making. 2023;43(1):21-41. https://doi.org/10.1177/0272989X221121747
and understanding the use of multidimensional arrays to represent cSTM dynamics in R described in:
and familiarizing with the DARTH coding framework described in:
To run the CEA, you require dampack
: Decision-Analytic Modeling
Package, an
R package for analyzing and visualizing the health economic outputs of
decision models.
cdx2cea
repository could be used in two different ways:
cdx2cea
cdx2cea
GitHub repository, navigate to the main page of the
repository (https://github.com/feralaes/cdx2cea).cdx2cea.Rproj
.cdx2cea
, please follow these instructions:# Install development version from GitHub
devtools::install_github("feralaes/cdx2cea")
devtools::load_all(".")
cdx2cea
from
GitHub with:devtools::install_github("feralaes/cdx2cea")
library(cdx2cea)
Alarid-Escudero F, Schrag D, Kuntz KM (2021). cdx2cea: A cost-efectiveness analysis of testing stage II colon cancer patients for the absence of CDX2 biomarker followed by adjuvant chemotherapy (Version v1.0.0). Zenodo. http://doi.org/10.5281/zenodo.5093594
This work was supported by a grant from Fulbright and the National Council of Science and Technology of Mexico (CONACYT) and a Doctoral Dissertation Fellowship from the Graduate School of the University of Minnesota as part of Dr. Alarid-Escudero’s doctoral program. Drs. Kuntz and Alarid-Escudero were supported by two grants from the National Cancer Institute at the National Institutes of Health (grant numbers U01-CA-199335 and U01-CA-253913) as part of the Cancer Intervention and Surveillance Modeling Network (CISNET). The funding agencies had no role in the design of the study, interpretation of results, or writing of the manuscript. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report. No other funding noted.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.