Simulation modelling is increasingly used to inform decision-making on screening, including colorectal cancer screening strategies. The strength of simulation is its ability to handle complexity and to identify the implications of uncertainty in a formal, documented, reproducible and consistent way. Important specific uncertainties concerning colorectal cancer screening are the dwell time of adenomas and the associated sensitivity of the various tests. Concerning these issues, for distal colorectal neoplasia, knowledge has been greatly increased by the recent availability of the once only sigmoidoscopy randomised trial results. Other uncertainties concern the quality of life effects of screening, diagnostic and surveillance colonoscopies, a...
The aim of this review was to critically evaluate published simulation models for breast cancer scre...
A general simulation procedure is described to validate model fitting algorithms for complex likelih...
Objectives: Metamodeling can address computational challenges within decision-analytic modeling stud...
Simulation modelling is increasingly used to inform decision-making on screening, including colorect...
Discrete event simulation was used to model a population-based colorectal cancer screening program. ...
Colorectal cancer is the 3rd most common cause of cancer deaths in the US. Early detection of colore...
Background. Microsimulation models are important decision support tools for screening. However, thei...
Background: Microsimulation models synthesize evidence about disease processes and interventions, pr...
Background: Nowadays, various simulation approaches for evaluation and decision making in cancer scr...
The aim of this thesis is to first describe the steps that are required to standardize the structure...
but some models are useful. ” (1). Simulation models contribute to our knowledge of complex systems ...
Colorectal cancer is a major cause of death for men and women in the Western world. When the cancer ...
This paper reviews the application of statistical models to planning and evaluating cancer screening...
textabstractColorectal cancer is a major public health problem in many countries. In 1997, approxima...
Although randomised controlled trials are the preferred basis for policy decisions on cancer screen...
The aim of this review was to critically evaluate published simulation models for breast cancer scre...
A general simulation procedure is described to validate model fitting algorithms for complex likelih...
Objectives: Metamodeling can address computational challenges within decision-analytic modeling stud...
Simulation modelling is increasingly used to inform decision-making on screening, including colorect...
Discrete event simulation was used to model a population-based colorectal cancer screening program. ...
Colorectal cancer is the 3rd most common cause of cancer deaths in the US. Early detection of colore...
Background. Microsimulation models are important decision support tools for screening. However, thei...
Background: Microsimulation models synthesize evidence about disease processes and interventions, pr...
Background: Nowadays, various simulation approaches for evaluation and decision making in cancer scr...
The aim of this thesis is to first describe the steps that are required to standardize the structure...
but some models are useful. ” (1). Simulation models contribute to our knowledge of complex systems ...
Colorectal cancer is a major cause of death for men and women in the Western world. When the cancer ...
This paper reviews the application of statistical models to planning and evaluating cancer screening...
textabstractColorectal cancer is a major public health problem in many countries. In 1997, approxima...
Although randomised controlled trials are the preferred basis for policy decisions on cancer screen...
The aim of this review was to critically evaluate published simulation models for breast cancer scre...
A general simulation procedure is described to validate model fitting algorithms for complex likelih...
Objectives: Metamodeling can address computational challenges within decision-analytic modeling stud...