Epidemiology Report: Analysis of Cancer Incidence and Mortality Rates

This report provides an analysis of the article "Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2016" by Fitzmaurice. It explores the methodology, focusing on the Global Burden of Disease (GBD) study estimation technique used to assess the burden of cancer. The report details the data analysis, including the use of the Sociodemographic Index (SDI) for stratification and the appropriateness of the research methods. The GBD study's estimation method is highlighted for its effectiveness in addressing data complexities and providing insights applicable to cancer control interventions. The report concludes by emphasizing the value of GBD study estimates in addressing gaps in authentic information regarding cancer and other non-communicable diseases, while also suggesting improvements in data collection to enhance reliability and accuracy. The report uses the GBD 2016 study, which is consistent with the GATHER guidelines and global population standard to compute age-standardized frequencies. The estimation method used reported 95% uncertainty intervals (UIs) for the entire estimates.

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Epidemiology
Introduction
The article entitled “Global, Regional, and National Cancer Incidence, Mortality, Years
of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 29 Cancer
Groups, 1990 to 2016” by Fitzmaurice Christiana investigates prevalence of cancer and other
communicable diseases and its effects on human development (Fitzmauric, 2018, pp. E2). The
article specifically aims to evaluate burden for twenty-nine groups over a specific time to offer a
model for resource allocation, policy deliberation, as well as research focus. The study
underscores the importance of the research given the growing prevalence of cancer and other
communicable diseases (Foreman, Lozano, Lopez & Murray, 2012, pp. 1). Many studies have
shown that only in 2016, there were around 17.2 million cases of cancer disease globally, as well
as 8.9 million mortalities. Therefore, to find the pertinent results that will answer meet the aims
of the stud, there is the need to develop effective research methodology and analysis to answer
the research questions. This analysis will explore the research methodology and data analysis
method that was used by the author.
Methodology
The article used Global Burden of Disease (GBD) study estimation technique as
quantitative assessment tool of the cancer burden of cancer in the group under study. The
method in this study specifically reestimated the time series of each study before the GBD,
where the results in the study superseded previous GBD studies. The estimation method used
defined all cancers based on the International Classification of Diseases (ICD) and categorized

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them into 29 groups (Fitzmauric, 2018, pp. E2). Furthermore, changes from the GBD 2015 study
comprise novel data additions of “other leukemia” being the primary cause, alterations in the
mortality-to-incidence ratio (MIR) assessment and reporting estimates for nonmelanoma skin
cancer disease (NMSC). Therefore, the study estimated nationwide illness burden for 195 nations
plus regions for the GBD 2016 (Begg, Vos, Barker, Stanley & Lopez, 2008). Thus, the estimates
of the GBD 2016 were consistent with the GATHER guidelines and global burden disease on
global population standard was employed in the study for the computation of age-standardized
frequencies. Thus, the method estimated the input of populace aging, population growth, as well
as modification in age-specific frequencies on the modification in incident cases amid 2006 and
2016 (Fitzmauric, 2018, pp. E2). The estimation method used reported 95% uncertainty intervals
(UIs) for the entire estimates.
Analysis
The researchers in the study analyzed the trends and levels over time, and by the
Sociodemographic Index (SDI). The modifications in the occurrence were grouped by the
alterations in levels and trends because of epidemiological vs. SDI. The analysis adequately
stratified the results employing SDI quintiles. The SDI provided a better analysis of the data
collected through the estimates because it is a composite indicator that includes education,
income, as well as fertility that are important measures of GBD that will show a relationship well
with the health outcomes (Fitzmauric, Allen & Barber, 2017, pp. 524).
Appropriateness of Research Methods

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The method that was used in this study based on estimates was appropriate in
investigating the burden of cancer disease in different countries. The GBD study estimation
method was appropriate because it helped to address issues that emerge when data exists in
diverse forms through converting the findings to comparable formats. This was achieved through
employing empirically observed associations between the reference format and non-standard
formats (Anderson & Duggan, 2016, pp. 84). In addition, the methods used in the article can
have applications outside the GBD analysis, for instance, in systematic reviews of public
interventions regarding or other development interventions in which the indicators are diverse in
the case of cancer burden. Accordingly, the method of GBD study method that used estimates
was appropriate for the study because the study entailed estimates of 29 groups in 195 countries
that could be complex when using other qualitative methods (Fitzmauric, 2018, pp. E2).
However, to further improve the reliability and credibility of data collection, there is the need to
develop and expand cancer registries, health surveys, registration systems, and coding systems.
This will improve the data collection and analysis providing results that are more valid and
accurate.
Conclusion
The GBD study estimates offered better method to collect data that was effective in the
development of interventions of cancer control and resource allocation. The estimates were
adequate in providing information that is applicable plus current on the international regional
along with countrywide problem of cancer and other non-communicable diseases (GBD 2016
Causes of Death Collaborators, 2017, 1151). Therefore, the estimates were effective in filling the
gap in which authentic information regarding the disease burden are inaccessible or sparse.

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References
Anderson, B.O. & Duggan, C. (2016). Resource-stratified guidelines for cancer management:
correction and commentary. Journal of Global Oncology. 3(1):84-88.
Begg, S. J., Vos, T., Barker, B., Stanley, L & Lopez, A.D. (2008). Burden of disease and injury
in Australia in the new millennium: measuring health loss from diseases, injuries and risk
factors. Medicine Journal of Australia. 188(1): 36-40.
Fitzmauric, C. (2018). Global, Regional, and National Cancer Incidence, Mortality, Years of Life
Lost, Years Lived With Disability and Disability-Adjusted Life-Years for 29 Cancer Groups,
1990 to 2016: A Systematic Analysis for the Global Burden of Disease Study. JAME Oncology.
3(1): E1-E16.
Fitzmauric, C., Allen, C. & Barber, R.M. (2017). Global Burden of Disease Cancer
Collaboration. Global, regional, and national cancer incidence, mortality, years of life lost,
years lived with disability, and disability-adjusted life-years for 32 cancer groups, 1990 to 2015:
a systematic analysis for the Global Burden of Disease Study. JAMA Oncology. 3(4): 524-548.
Foreman, K.J., Lozano, R., Lopez, A.D. & Murray, C.J. (2012). Modeling causes of death: an
integrated approachusing CODEm. Population Health Metrics. 10(2):1.
GBD 2016 Causes of Death Collaborators. (2017). Global, regional, and national age-sex
specific mortality for 264 causes of death, 1980-2016: A systematic analysis for the Global
Burden of Disease Study 2016. Lancet. 390(10100):1151-1210.