Description Details Author(s) References
The MILC package is designed to predict individual trajectories describing the onset of, progression, and (potentially) death from lung cancer using the MILC continuous time microsimulation model.
The MIcrosimulation Lung Cancer model (MILC), is a new, dynamic, continuous time microsimulation model that, in its current version, comprises a module that describes the natural history of lung cancer in the absence of any screening or treatment component. The model simulates the course of lung cancer from the disease free state to the local, regional, and distant states and eventually to death from either lung cancer or some other cause. When predicting individual trajectories, the model accounts for age, gender, and smoking history, including smoking status, start and quit smoking ages, and average number of cigarettes smoked per day when relevant.
The model comprises four main components:
Onset of the first malignant cell: The local stage of the lung cancer tumor initiates with the onset of the first malignant cell, as described by the Two-Stage Clonal Expansion (TSCE) carcinogenesis model (see HT_mal
for more details).
Tumor growth: The model assumes a spherical tumor growth described by a Gompertz distribution (see t_prog
for more details).
Disease progression: Given a Gompertzian tumor growth, the tumor volume at specific time points is described by log-Normal distributions (see t_prog
for more details).
Survival: The model employs the Cumulative Incidence Function (CIF) non-parametric technique to simulate survival in a competing-risks frame.
Package: | MILC |
Type: | Package |
Version: | 1.0 |
Date: | 2014-02-18 |
License: | GPL-2 |
Stavroula A. Chrysanthopoulou <Stavroula_Chrysanthopoulou@brown.edu>
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Gray, B. (2013) cmprsk: Subdistribution Analysis of Competing Risks, URL: http://CRAN.R-project.org/package=cmprsk. R package version 2.2-6.
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