Meet Inspiring Speakers and Experts at our 3000+ Global Conference Series LLC LTD Events with over 1000+ Conferences, 1000+ Symposiums
and 1000+ Workshops on Medical, Pharma, Engineering, Science, Technology and Business.

Explore and learn more about Conference Series LLC LTD : World’s leading Event Organizer


7th Global Summit on Cancer Therapy

Dubai, UAE

Shahram Bahmanyar

Shahram Bahmanyar

Karolinska Institutet, Stockholm Sweden

Title: Multi data based studies using national health registers to investigate cancer risk and patient health outcomes


Biography: Shahram Bahmanyar


Because of the lengthy latent period for cancer, a long follow-up period and large sample size are required to study possible association between a specific risk factor and cancer. A prospective cohort is usually not feasible due to factors such as high cost, complex logistic and high rate of loss to follow-up which can be differential and create bias. The retrospective cohort study design is a more feasible approach to evaluate the possible association between different exposures and cancer risks. A beneficial source of data for this purpose is administrative and other electronic medical records. Multi-source studies are a way to improve statistical power of studies and assess generalizability concerning rare exposures such as infrequently prescribed drugs and rare outcomes such as cancer. I will present data structure, methodology and results of two studies we performed: 1) a study using data from the Swedish National Registers including the Cancer Register to investigate associations between offspring size at birth in the most recent pregnancy before premenopausal breast cancer diagnosis and the risks of maternal breast cancer mortality, and 2) a multi-database retrospective cohort study in four European countries (Sweden, Finland, the United Kingdom and the Netherlands) using linkage of databases such as drug prescribing, cancer, patient and migration registers to investigate the association between Pioglitazone and bladder cancer. The approach developed for pooling and integration of heterogeneous data for research in this study will be discussed.