Mapping Cancer in Africa: A Comprehensive and Comparable Characterization of 34 Cancer Types Using Estimates From GLOBOCAN 2020
ObjectiveCancer incidence and mortality rates in Africa are increasing, yet their geographic distribution and determinants are incompletely characterized. The present study aims to establish the spatial epidemiology of cancer burden in Africa and delineate the association between cancer burden and t...
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Frontiers Media S.A.
2022-04-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2022.839835/full |
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| author | Rajesh Sharma Aashima Mehak Nanda Claudio Fronterre Paul Sewagudde Anna E. Ssentongo Anna E. Ssentongo Kelsey Yenney Nina D. Arhin John Oh Forster Amponsah-Manu Paddy Ssentongo Paddy Ssentongo |
| author_facet | Rajesh Sharma Aashima Mehak Nanda Claudio Fronterre Paul Sewagudde Anna E. Ssentongo Anna E. Ssentongo Kelsey Yenney Nina D. Arhin John Oh Forster Amponsah-Manu Paddy Ssentongo Paddy Ssentongo |
| author_sort | Rajesh Sharma |
| collection | DOAJ |
| description | ObjectiveCancer incidence and mortality rates in Africa are increasing, yet their geographic distribution and determinants are incompletely characterized. The present study aims to establish the spatial epidemiology of cancer burden in Africa and delineate the association between cancer burden and the country-level socioeconomic status. The study also examines the forecasts of the cancer burden for 2040 and evaluates infrastructure availability across all African countries.MethodsThe estimates of age, sex, and country-specific incidence and mortality of 34 neoplasms in 54 African countries, were procured from GLOBOCAN 2020. Mortality-to-incidence ratio (MIR) was employed as a proxy indicator of 5-year survival rates, and the socioeconomic development of each country was measured using its human development index (HDI). We regressed age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and MIR on HDI using linear regression model to determine the relationship between cancer burden and HDI. Maps were generated for each cancer group for each country in Africa. The data about the cancer infrastructure of African countries were extracted from the WHO Cancer Country Profiles.ResultsIn Africa, an estimated 1.1 million new cases [95% uncertainty intervals (UIs) 1.0 – 1.3 million] and 711,429 [611,604 – 827,547] deaths occurred due to neoplasms in 2020. The ASIR was estimated to be 132.1/100,000, varying from 78.4/100,000 (Niger) to 212.5/100,000 (La Réunion) in 2020. The ASMR was 88.8/100,000 in Africa, ranging from 56.6/100,000 in the Republic of the Congo to 139.4/100,000 in Zimbabwe. The MIR of all cancer combined was 0.64 in Africa, varying from 0.49 in Mauritius to 0.78 in The Gambia. HDI had a significant negative correlation with MIR of all cancer groups combined and main cancer groups (prostate, breast, cervical and colorectal). HDI explained 75% of the variation in overall 5-year cancer survival (MIR). By 2040, the burden of all neoplasms combined is forecasted to increase to 2.1 million new cases and 1.4 million deaths in Africa.ConclusionHigh cancer mortality rates in Africa demand a holistic approach toward cancer control and management, including, but not limited to, boosting cancer awareness, adopting primary and secondary prevention, mitigating risk factors, improving cancer infrastructure and timely treatment. |
| first_indexed | 2024-12-10T09:57:57Z |
| format | Article |
| id | doaj.art-9ba220cd6535477fb69989eb6ce67b61 |
| institution | Directory Open Access Journal |
| issn | 2296-2565 |
| language | English |
| last_indexed | 2024-12-10T09:57:57Z |
| publishDate | 2022-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj.art-9ba220cd6535477fb69989eb6ce67b612022-12-22T01:53:26ZengFrontiers Media S.A.Frontiers in Public Health2296-25652022-04-011010.3389/fpubh.2022.839835839835Mapping Cancer in Africa: A Comprehensive and Comparable Characterization of 34 Cancer Types Using Estimates From GLOBOCAN 2020Rajesh Sharma0 Aashima1Mehak Nanda2Claudio Fronterre3Paul Sewagudde4Anna E. Ssentongo5Anna E. Ssentongo6Kelsey Yenney7Nina D. Arhin8John Oh9Forster Amponsah-Manu10Paddy Ssentongo11Paddy Ssentongo12University School of Management and Entrepreneurship, Delhi Technological University, New Delhi, IndiaUniversity School of Management and Entrepreneurship, Delhi Technological University, New Delhi, IndiaUniversity School of Management and Entrepreneurship, Delhi Technological University, New Delhi, IndiaCentre for Health Informatics, Computing, and Statistics, Lancaster University, Lancaster, United KingdomRelife Family Medical Center, Kampala, UgandaDepartment of Public Health Sciences, Penn State College of Medicine, Hershey, PA, United StatesDivision of Trauma Surgery, Department of Surgery, Penn State College of Medicine and Milton S. Hershey Medical Center, Hershey, PA, United StatesWashington State University Elson S. Floyd College of Medicine, Seattle, WA, United StatesDivision of Hematology/Oncology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United StatesDivision of Trauma Surgery, Department of Surgery, Penn State College of Medicine and Milton S. Hershey Medical Center, Hershey, PA, United StatesDepartment of Surgery, Eastern Regional Hospital, Koforidua, GhanaDepartment of Public Health Sciences, Penn State College of Medicine, Hershey, PA, United StatesCenter for Neural Engineering, The Pennsylvania State University, State College, PA, United StatesObjectiveCancer incidence and mortality rates in Africa are increasing, yet their geographic distribution and determinants are incompletely characterized. The present study aims to establish the spatial epidemiology of cancer burden in Africa and delineate the association between cancer burden and the country-level socioeconomic status. The study also examines the forecasts of the cancer burden for 2040 and evaluates infrastructure availability across all African countries.MethodsThe estimates of age, sex, and country-specific incidence and mortality of 34 neoplasms in 54 African countries, were procured from GLOBOCAN 2020. Mortality-to-incidence ratio (MIR) was employed as a proxy indicator of 5-year survival rates, and the socioeconomic development of each country was measured using its human development index (HDI). We regressed age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and MIR on HDI using linear regression model to determine the relationship between cancer burden and HDI. Maps were generated for each cancer group for each country in Africa. The data about the cancer infrastructure of African countries were extracted from the WHO Cancer Country Profiles.ResultsIn Africa, an estimated 1.1 million new cases [95% uncertainty intervals (UIs) 1.0 – 1.3 million] and 711,429 [611,604 – 827,547] deaths occurred due to neoplasms in 2020. The ASIR was estimated to be 132.1/100,000, varying from 78.4/100,000 (Niger) to 212.5/100,000 (La Réunion) in 2020. The ASMR was 88.8/100,000 in Africa, ranging from 56.6/100,000 in the Republic of the Congo to 139.4/100,000 in Zimbabwe. The MIR of all cancer combined was 0.64 in Africa, varying from 0.49 in Mauritius to 0.78 in The Gambia. HDI had a significant negative correlation with MIR of all cancer groups combined and main cancer groups (prostate, breast, cervical and colorectal). HDI explained 75% of the variation in overall 5-year cancer survival (MIR). By 2040, the burden of all neoplasms combined is forecasted to increase to 2.1 million new cases and 1.4 million deaths in Africa.ConclusionHigh cancer mortality rates in Africa demand a holistic approach toward cancer control and management, including, but not limited to, boosting cancer awareness, adopting primary and secondary prevention, mitigating risk factors, improving cancer infrastructure and timely treatment.https://www.frontiersin.org/articles/10.3389/fpubh.2022.839835/fullcancer burdenmappingspatial epidemiologyincidencemortalityAfrica |
| spellingShingle | Rajesh Sharma Aashima Mehak Nanda Claudio Fronterre Paul Sewagudde Anna E. Ssentongo Anna E. Ssentongo Kelsey Yenney Nina D. Arhin John Oh Forster Amponsah-Manu Paddy Ssentongo Paddy Ssentongo Mapping Cancer in Africa: A Comprehensive and Comparable Characterization of 34 Cancer Types Using Estimates From GLOBOCAN 2020 Frontiers in Public Health cancer burden mapping spatial epidemiology incidence mortality Africa |
| title | Mapping Cancer in Africa: A Comprehensive and Comparable Characterization of 34 Cancer Types Using Estimates From GLOBOCAN 2020 |
| title_full | Mapping Cancer in Africa: A Comprehensive and Comparable Characterization of 34 Cancer Types Using Estimates From GLOBOCAN 2020 |
| title_fullStr | Mapping Cancer in Africa: A Comprehensive and Comparable Characterization of 34 Cancer Types Using Estimates From GLOBOCAN 2020 |
| title_full_unstemmed | Mapping Cancer in Africa: A Comprehensive and Comparable Characterization of 34 Cancer Types Using Estimates From GLOBOCAN 2020 |
| title_short | Mapping Cancer in Africa: A Comprehensive and Comparable Characterization of 34 Cancer Types Using Estimates From GLOBOCAN 2020 |
| title_sort | mapping cancer in africa a comprehensive and comparable characterization of 34 cancer types using estimates from globocan 2020 |
| topic | cancer burden mapping spatial epidemiology incidence mortality Africa |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2022.839835/full |
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