TY - JOUR
T1 - The melanoma MAICare framework
T2 - A microsimulation model for the assessment of individualized cancer care
AU - Van Der Meijde, Elisabeth
AU - Van Den Eertwegh, Alfons J M
AU - Linn, Sabine C.
AU - Meijer, Gerrit A.
AU - Fijneman, Remond J A
AU - Coupé, Veerle M H
PY - 2016
Y1 - 2016
N2 - Recently, new but expensive treatments have become available for metastatic melanoma. These improve survival, but in view of the limited funds available, cost‐effectiveness needs to be evaluated. Most cancer cost‐effectiveness models are based on the observed clinical events such as recurrence‐free and overall survival. Times at which events are recorded depend not only on the effectiveness of treatment but also on the timing of examinations and the types of tests performed. Our objective was to construct a microsimulation model framework that describes the melanoma disease process using a description of underlying tumor growth as well as its interaction with diagnostics, treatments, and surveillance. The framework should allow for exploration of the impact of simultaneously altering curative treatment approaches in different phases of the disease as well as altering diagnostics. The developed framework consists of two components, namely, the disease model and the clinical management module. The disease model consists of a tumor level, describing growth and metastasis of the tumor, and a patient level, describing clinically observed states, such as recurrence and death. The clinical management module consists of the care patients receive. This module interacts with the disease process, influencing the rate of transition between tumor growth states at the tumor level and the rate of detecting a recurrence at the patient level. We describe the framework as the required input and the model output. Furthermore, we illustrate model calibration using registry data and data from the literature.
AB - Recently, new but expensive treatments have become available for metastatic melanoma. These improve survival, but in view of the limited funds available, cost‐effectiveness needs to be evaluated. Most cancer cost‐effectiveness models are based on the observed clinical events such as recurrence‐free and overall survival. Times at which events are recorded depend not only on the effectiveness of treatment but also on the timing of examinations and the types of tests performed. Our objective was to construct a microsimulation model framework that describes the melanoma disease process using a description of underlying tumor growth as well as its interaction with diagnostics, treatments, and surveillance. The framework should allow for exploration of the impact of simultaneously altering curative treatment approaches in different phases of the disease as well as altering diagnostics. The developed framework consists of two components, namely, the disease model and the clinical management module. The disease model consists of a tumor level, describing growth and metastasis of the tumor, and a patient level, describing clinically observed states, such as recurrence and death. The clinical management module consists of the care patients receive. This module interacts with the disease process, influencing the rate of transition between tumor growth states at the tumor level and the rate of detecting a recurrence at the patient level. We describe the framework as the required input and the model output. Furthermore, we illustrate model calibration using registry data and data from the literature.
KW - Cancer progression
KW - Melanoma
KW - Microsimulation
KW - Modeling
KW - Tumor growth
UR - http://www.scopus.com/inward/record.url?scp=84975316914&partnerID=8YFLogxK
U2 - 10.4137/CIN.S38122
DO - 10.4137/CIN.S38122
M3 - Article
C2 - 27346945
AN - SCOPUS:84975316914
SN - 1176-9351
VL - 15
SP - 115
EP - 127
JO - Cancer informatics
JF - Cancer informatics
ER -