ISSN: 2161-1165

Epidemiology: Open Access
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  • Research Article   
  • Epidemiology (Sunnyvale) 2015, Vol 5(3): 193
  • DOI: 10.4172/2161-1165.1000193

Predictive Models for Incidence and Economic Burden of Liver Cancer in Saudi Arabia

Shoukri MM1,4*, Elsiesy HA2, Khafaga Y3, Bazarbashi S3,4, Al-Sebayel M2, Collison K1 and Al-Mohanna F1,4
1Department of Cell Biology, King Faisal Specialist Hospital and Research Center, , Saudi Arabia
2Organ Transplant Center, King Faisal Specialist Hospital and Research Center, , Saudi Arabia
3Oncology Center, King Faisal Specialist Hospital and Research Center, , Saudi Arabia
4College of Medicine, Al Faisal University, Saudi Arabia
*Corresponding Author : Shoukri MM Principal Scientist/Professor, King Faisal Specialist Hospital and Research Center, Cell Biology, Saudi Arabia, Tel: +966509491454, Email: shoukri@kfshrc.edu.sa

Received Date: Jun 23, 2015 / Accepted Date: Jul 28, 2015 / Published Date: Jul 31, 2015

Abstract

Hepatocellular carcinoma (HCC) is a major cause of cancer-related death worldwide, and the burden of this devastating disease is expected to increase. The variability in the incidence and prevalence of this disease is documented in many epidemiological studies. This variation may be attributed to the variation in the prevalence of major risk factors such as, smoking, drinking, gender, hepatitis B and C viral infection and the Nonalcoholic Fatty Liver Disease (NAFLD). In order to understand the role of such risk factors in the disease etiology a surveillance system with rich data should be available. We intend to use the Saudi Cancer Registry (SCR) data to establish the relationship between age, gender, and the HCC incidence, and the future burden in terms of the forecasted number of liver cancer cases. Moreover we shall link the information available from the Saudi Transplant Registry (STR) with a model that utilizes the number of forecasted HCC cases to predict the future number of needed liver transplants, and hence the economic burden for the next 10 years. This is done by using the Poisson regression model for count data. The projected information will be reported (within limits of uncertainty) and is expected to play a critical role in guiding health officials on future disease patient management.

Keywords: Hepatocellular carcinoma; Risk factors; Saudi cancer registry; Count regression models; Incidence prediction; Goodness of fit

Citation: Shoukri MM, Elsiesy HA, Khafaga Y, Bazarbashi S, Al-Sebayel M, et al. (2015) Predictive Models for Incidence and Economic Burden of Liver Cancer in Saudi Arabia. Epidemiology (sunnyvale) 5:193. Doi: 10.4172/2161-1165.1000193

Copyright: © 2015 Shoukri M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

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