MedicalResearch.com Interview with:
Victor Moreno, PhD.
Director of Cancer Prevention and Control Program, Catalan Institute of Oncology-IDIBELL, L’Hospitalet de Llobregat, Spain
Department of Clinical Sciences, Faculty of Medicine
University of Barcelona
Gemma Ibáñez-Sanz, MD
*Cancer Prevention and Control Unit, Catalan Institute of Oncology. L’Hospitalet deLlobregat, Barcelona, SPAIN
*Gastroenterology Department, Bellvitge University Hospital-IDIBELL,
L’Hospitalet de Llobregat, Spain
MedicalResearch.com: What is the background for this study?
Response: Colorectal cancer (CRC) screening by faecal occult blood testing has been demonstrated to reduce CRC incidence and mortality, as well as being a cost-effective strategy compared to no screening. Currently, the target population is defined basically by age (≥50 years old), which has been called a ‘one-size-fits-all’ strategy. This strategy implies performing unnecessary screening tests in low-risk people leading to avoidable risks for patients and extra costs for the healthcare system. On the other hand, high-risk patients may receive non-invasive testing, which is a suboptimal screening technique in their case. Several risk prediction models, either for colorectal cancer or advanced neoplasia, have been previously developed, all with limited discriminating ability.
We have developed a risk stratification model that combines environmental factors with family history and genetic susceptibility. Furthermore, we have assessed the relative contribution of these factors and the utility of the model for risk stratification and public health intervention.
MedicalResearch.com: What are the main findings?
Response: Data from common genetic susceptibility loci could be useful to stratify colorectal cancer screening in average-risk population. Individuals in the top quintile of risk alleles have an 82% increased risk compared to those in the lower quintile. We have estimated the impact of determining an individual environmental and genetic risk score in a Spanish CRC screening population. In our model, although the genetic factors are significant contributors, the modifiable risk factors contribute more strongly. Risk assessment may increase screening participation and adoption of healthier lifestyles.
MedicalResearch.com: What should readers take away from your report?
Response: On average, each environmental risk factor increases CRC risk by 35%, while each risk allele only increases it by 7%. This implies that the change of one modifiable risk factor towards healthier lifestyle might offset the effect of 4 risk alleles. Given the fact that environmental factors explain part of the CRC risk, we believe it to be important to give thought to incorporating clinical data to encourage individuals to achieve a healthier lifestyle. As the European Code Against Cancer recommends, and our findings confirm, one should have a healthy diet, a healthy body weight, be physically active and should not smoke or a high consumption of alcohol.
MedicalResearch.com: What recommendations do you have for future research as a result of this study?
Response: Future prospective studies should aim to analyse if stratifying by genetic and lifestyle risk scores is useful and cost-effective to improve screening. Subjects with higher predicted risk should probably start screening earlier and decrease the intervals between tests, while low risk individuals could start later or space more the between test intervals.
MedicalResearch.com: Is there anything else you would like to add?
Response: Population acceptability of genetic tests is not well known. We are currently recruiting subjects from colorectal cancer screening and gastroenterology clinics in a study called COLSCREEN to assess risk perception and attitudes regarding genetic testing to prevent cancer.
Sci Rep. 2017 Feb 24;7:43263. doi: 10.1038/srep43263.
Risk Model for Colorectal Cancer in Spanish Population Using Environmental and Genetic Factors: Results from the MCC-Spain study.
Ibáñez-Sanz G1, Díez-Villanueva A1, Alonso MH1,2, Rodríguez-Moranta F2,3, Pérez-Gómez B2,4,5, Bustamante M2,6, Martin V2,7, Llorca J2,8, Amiano P2,9, Ardanaz E2,10, Tardón A2,11, Jiménez-Moleón JJ2,12, Peiró R2,13, Alguacil J2,14, Navarro C2,15, Guinó E1,2, Binefa G1,2, Navarro PF2,4,5, Espinosa A2,6, Dávila-Batista V7, Molina AJ2,7, Palazuelos C8, Castaño-Vinyals G2,6,16,17, Aragonés N2,4,5, Kogevinas M2,6,16,17,18, Pollán M2,4,5, Moreno V1,2,19.
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