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      Long-Term Trend of Liver Cancer Mortality in Serbia, 1991–2015: An Age-Period-Cohort and Joinpoint Regression Analysis

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          Abstract

          Background and Objectives: Trends of liver cancer mortality vary widely around the world. The purpose of this study was to assess the trend of liver cancer mortality in Serbia. Material and Methods: Descriptive epidemiological study design was used in this research. The age-standardized rates (ASRs, per 100,000) were calculated using the direct method, according to the World standard population. Temporal trends were assessed using the average annual percent change (AAPC) with 95% confidence interval (95% CI), according to joinpoint regression. An age-period-cohort analysis was used to evaluate the underlying factors for liver cancer mortality trends. Results: In Serbia from 1991 to 2015, over 11,000 men and nearly 8000 women died from liver cancer. The trend in liver cancer mortality significantly decreased both in men (AAPC = −1.3%; 95% CI = −1.7 to −0.9) and women (AAPC = −1.5%; 95% CI = −1.9 to −1.1). For liver cancer mortality, statistically significant cohort and period effects were observed in both genders. Conclusions: The downward trends in liver cancer mortality in Serbia are recorded during the past decades.

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          Epidemiology of hepatocellular carcinoma: consider the population.

          Hepatocellular carcinoma (HCC) is increasing in incidence and has a very high fatality rate. Cirrhosis due to chronic hepatitis B or hepatitis C is the leading risk factor for HCC. Global epidemiology of HCC is determined by the prevalence of dominant viral hepatitis and the age it is acquired in the underlying population. Upcoming risk factors include obesity, diabetes, and related nonalcoholic fatty liver disease. This review discusses the latest trends of HCC globally and in the United States. It also provides an evidence-based commentary on the risk factors and lists some of the preventive measures to reduce the incidence of HCC.
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            A web tool for age-period-cohort analysis of cancer incidence and mortality rates.

            Age-period-cohort (APC) analysis can inform registry-based studies of cancer incidence and mortality, but concerns about statistical identifiability and interpretability, as well as the learning curves of statistical software packages, have limited its uptake.
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              Counting the dead and what they died from: an assessment of the global status of cause of death data.

              We sought to assess the current status of global data on death registration and to examine several indicators of data completeness and quality. We summarized the availability of death registration data by year and country. Indicators of data quality were assessed for each country and included the timeliness, completeness and coverage of registration and the proportion of deaths assigned to ill-defined causes. At the end of 2003 data on death registration were available from 115 countries, although they were essentially complete for only 64 countries. Coverage of death registration varies from close to 100% in the WHO European Region to less than 10% in the African Region. Only 23 countries have data that are more than 90% complete, where ill-defined causes account for less than 10% of total of causes of death, and where ICD-9 or ICD-10 codes are used. There are 28 countries where less than 70% of the data are complete or where ill-defined codes are assigned to more than 20% of deaths. Twelve high-income countries in western Europe are included among the 55 countries with intermediate-quality data. Few countries have good-quality data on mortality that can be used to adequately support policy development and implementation. There is an urgent need for countries to implement death registration systems, even if only through sample registration, or enhance their existing systems in order to rapidly improve knowledge about the most basic of health statistics: who dies from what?
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                Author and article information

                Journal
                Healthcare (Basel)
                Healthcare (Basel)
                healthcare
                Healthcare
                MDPI
                2227-9032
                21 August 2020
                September 2020
                : 8
                : 3
                : 283
                Affiliations
                [1 ]Faculty of Medicine, University of Belgrade, 11000 Belgrade, Serbia
                [2 ]Institute of Epidemiology, Faculty of Medicine, University of Belgrade, 11000 Belgrade, Serbia; sandra.sipetic-grujicic@ 123456med.bg.ac.rs
                [3 ]Department of Biochemistry, Ave Maria University of Florida, Miami, FL 34142, USA; ssipetic@ 123456yahoo.com
                [4 ]Faculty of Medicine, University Nis, 18000 Nis, Serbia; medicus_epidemiology@ 123456yahoo.com
                [5 ]Department of Anatomy, Faculty of Medical Sciences, University of Kragujevac, 34000 Kragujevac, Serbia; ivanaanatom@ 123456yahoo.com
                [6 ]Department of Social Medicine, Faculty of Medical Sciences, University of Kragujevac, 34000 Kragujevac, Serbia; kocicsanja@ 123456yahoo.com
                [7 ]Department of Epidemiology, Faculty of Medical Sciences, University of Kragujevac, 34000 Kragujevac, Serbia; drmilenailic@ 123456yahoo.com
                Author notes
                [* ]Correspondence: irena.ilic@ 123456med.bg.ac.rs ; Tel.: +381-11-3636300
                Article
                healthcare-08-00283
                10.3390/healthcare8030283
                7551841
                e91808b4-752f-4adb-af97-a2295055cf89
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 30 June 2020
                : 18 August 2020
                Categories
                Article

                liver cancer,mortality,trends,joinpoint regression analysis,age-period-cohort analysis

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