As a part of EUROCADET, 5 workshops were organised by Eurocadet partners, in order to facilitate the use of PREVENT by professionals working in the cancer area.

The aims of the workshops were: 

• To make participants familiar with the Eurocadet project

• To make participants familiar with the concepts, possibilities and limitations of the Prevent-model
• To provide opportunities for computer-based practical analysis of cancer data with PREVENT so they can make their own scenario’s and predictions.

  The workshops were open to a maximum number of 15-20 participants each, encompassed 1.5 days and were hosted and organised by: 

Great Britain, Ireland, Belgium, The Netherlands
Organiser: Henrik Moller, Thames Cancer Registry, London
Date: June 9-10, 2008 - link

Central and Eastern Europe
Organiser: Witold Zatonski, Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Warsaw, Poland
Date: February 16-17, 2009 - link

Northern Europe (e.g. Finland, Norway, Sweden, Denmark, Iceland, Baltic countries)
Organiser: Hans Storm, Danish Cancer Society, Copenhagen, Denmark
Date: October 23-24, 2008 - link

Central/Western Europe (e.g. Germany, Switzerland, Austria, Czech Republic, Slovakia, Slovenia)
Organiser: Hermann Brenner, Deutsches Krebsforschungszentrum, Heidelberg, Germany Date: November 6-7, 2008 - link

Southern Europe (e.g. Spain, Italy, Portugal, France, Greece)
Organiser: Josep Borràs, Institut Catala d'Oncologia, Barcelona, Spain
Date: March 12-13, 2009 - link 

 

 

 

 

 

 

1. About PREVENT

The simulation model PREVENT estimates the effect of changes in risk factor prevalence, ‘autonomous’ trends in incidence, and interventions on disease occurrence and/or mortality ^1-5. It was developed as a tool to translate the results of epidemiological studies into estimates of potential health benefits of preventive interventions in a specific population.
The model takes into account:

• associations between risk factors and diseases
• associations between risk factors
• time dimensions (including lag times e.g. for smoking)
• projected changes in demography
• trends in incidence of disease independent of the risk factors under study in the model (autonomous trends)
  

Eurocadet will use the Prevent model in order to fulfill its aims: identifying effective preventive strategies and estimating the effects of implementation of these strategies. The potential impact on cancer incidence of the prevalence of multiple risk factors, different preventive strategies and barriers to a successful implementation will be taken into account. Estimating the quantitative expected impact of interventions on future cancer incidence will help optimise policies and underpin priorities.

For Eurocadet, we will use the PREVENT version 3.01 (beta), which is different from previous versions^1-5 in that:

• it can deal with incidence data, using causal webs and projected demography produced by statistical agencies rather than calculating future population sizes based on mortality and fertility rates
• it models the effects of interventions on the prevalence of risk factors by cohort
• it deals with both categorical and continuous exposure variables, giving better estimations because risk factor exposures and the effects of interventions are often measured on a continuous scale

A manual for PREVENT 3.01 beta is under development within the framework of Eurocadet, the most recent (but not final) version can be downloaded here.

Information on Prevent can also be found on this website , made by the developer of Prevent, Jan Barendregt.

References:

1. Mooy JM, Gunning-Schepers LJ. Computer-assisted health impact assessment for intersectoral health policy. Health Policy. 2001 Sep;57(3):169-77.
2. Gunning-Schepers L. The health benefits of prevention: a simulation approach. Health Policy. 1989 Jul;12(1-2):1-255.
3. Bronnum-Hansen H. How good is the Prevent model for estimating the health benefits of prevention? J Epidemiol Community Health. 1999 May;53(5):300-5.
4. Bronnum-Hansen H, Juel K. Estimating mortality due to cigarette smoking: two methods, same result. Epidemiology. 2000 Jul;11(4):422-6.
5. Naidoo B, Thorogood M, McPherson K, Gunning-Schepers LJ. Modelling the effects of increased physical activity on coronary heart disease in England and Wales. J Epidemiol Community Health. 1997 Apr;51(2):144-50.