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Global Outlook for Disability Adjusted Life Years: Brain and Central Nervous System Cancers

Yıl 2025, Cilt: 7 Sayı: 1, 100 - 106, 15.01.2025
https://doi.org/10.37990/medr.1536199

Öz

Aim: In 2019, brain and central nervous system cancers were listed among the top 5 causes of death in men and women by absolute Disability Adjusted Life Years (DALY) burden globally. In this respect, it is important to define the current global status of deaths from neurological disorders and brain and central nervous system cancers. In this study, we aimed to examine the burden of disease metrics of deaths from neurological disorders and brain and central nervous system cancers in 204 different countries/regions by categorizing the countries.
Material and Method: Brain and central nervous system cancer DALYs, motor neuron disease deaths and multiple sclerosis deaths of 204 different countries were obtained from the "GBD Compare" tool of the Institute for Health Metrics and Evaluation. The k-means clustering algorithm, also known as unsupervised machine learning algorithm, was used to categorize the countries. The number of clusters was determined by the Silhouette score (s). The statistical difference between the medians of two independent groups was analyzed by Mann-Whitney U Test.
Results: According to the silhouette score obtained using the K-Means algorithm, the number of clusters was determined as 2 (s=0.684). Cluster I included 135 countries (African and Asian countries) and Cluster II included 65 countries (European and North American countries). The median (min; max) values of Cluster II countries for brain and central nervous system cancer DALYs, Multiple Sclerosis deaths and Motor Neuron Disease deaths variables were 201.77 (147.65;375.16), 0.62 (0.00;2.21), 1.13 (0.00;4.65), while the median (min; max) values of Cluster I countries are 64.50 (6.29;134.99), 0.04 (0.00;0.67), 0.00 (0.00;2.36), respectively (p<0.001).
Conclusion: The group of developed countries in Europe and North America has been found to have more deaths from neurological diseases and more DALYs from brain and central nervous system cancers. When the countries in the groups are evaluated, it is concluded that the geographical proximity and development level of the countries have a significant effect on the variables used in the grouping.

Kaynakça

  • Palmer JD, Prasad RN, Cioffi G, et al. Exposure to radon and heavy particulate pollution and incidence of brain tumors. Neuro-Oncology. 2022;25:407-17.
  • Wanis HA, Møller H, Ashkan K, Davies EA. The incidence of major subtypes of primary brain tumors in adults in England 1995-2017. Neuro Oncol. 2021;23:1371-82.
  • Monterroso P, Moore KJ, Sample JM, et al. Racial/ethnic and sex differences in young adult malignant brain tumor incidence by histologic type. Cancer Epidemiol. 2022;76:102078.
  • Alvarez EM, Force LM, Xu R, et al. The global burden of adolescent and young adult cancer in 2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Oncol. 2022;23:27-52.
  • Alemu BS, Feisso S, Mohammed EA, Salau AO. Magnetic resonance imaging-based brain tumor image classification performance enhancement. Scientific African. 2023;22:e01963.
  • IHME. GBD Compare. www.healthdata.org/data-tools-practices/interactive-visuals/gbd-compare access date 10.07.2024.
  • Leong YQ, Lee SWH, Ng KY. Cancer risk in Parkinson disease: An updated systematic review and meta‐analysis. Eur J Neurol. 2021;28:4219-37.
  • Nudelman KNH, Risacher SL, West JD, et al. Association of cancer history with Alzheimer's disease onset and structural brain changes. Front Physiol. 2014;5:423.
  • Natale G, Cucchiara F, Bocci G. Historical overview of the “firing” liaison between brain tumors and epilepsy. Neuroscientist. 2021;28:411-9.
  • Sirko A, Dzyak L, Chekha E, et al. Coexistence of multiple sclerosis and brain tumours: case report and review. Interdisciplinary Neurosurgery. 2020;19:100585.
  • Cortés Mancera EA, Sinisterra Solis FA, Romero-Castellanos FR, et al. 18F-FDG PET/CT as a molecular biomarker in the diagnosis of amyotrophic lateral sclerosis associated with prostate cancer and progressive supranuclear palsy: a case report. Front Nucl Med. 2023;3:1137875.
  • Lima AA, Mridha MF, Das SC, et al. A Comprehensive survey on the detection, classification, and challenges of neurological disorders. Biology. 2022;11:469.
  • Abbas SA, Aslam A, Rehman AU, et al. K-Means and K-Medoids: cluster analysis on birth data collected in City Muzaffarabad, Kashmir. IEEE Access. 2020;8:151847-55.
  • Rizvi SA, Umair M, Cheema MA. Clustering of countries for COVID-19 cases based on disease prevalence, health systems and environmental indicators. Chaos Solitons Fractals. 2021;151:111240.
  • Nabors LB, Portnow J, Ahluwalia M, et al. Central Nervous System Cancers, Version 3.2020, NCCN Clinical Practice Guidelines in Oncology. J Natl Compr Canc Netw. 2020;18:1537-70.
  • Lambrou GI, Zaravinos A, Braoudaki M. Co-deregulated miRNA signatures in childhood central nervous system tumors: in search for common tumor miRNA-related mechanics. Cancers. 2021;13:3028.
  • Gaeta M, Campanella F, Capasso L, et al. An overview of different health indicators used in the European Health Systems. J Prev Med Hyg. 2017;58:E114-20.
  • Zarikas V, Poulopoulos SG, Gareiou Z, Zervas E. Clustering analysis of countries using the COVID-19 cases dataset. Data in Brief. 2020;31:105787.
  • Žmuk B. Quality of life indicators in selected European Countries: hierarchical cluster analysis approach. Croatian Review of Economic, Business and Social Statistics. 2015;1:42-54.
  • Akman M, Civek S. Frequency and risk assessment of cardiovascular diseases in the world and Turkey. Jour Turk Fam Phy. 2022;13:21-8.
  • Solberg CT, Sørheim P, Müller KE, et al. The devils in the DALY: prevailing evaluative assumptions. Public Health Ethics. 2020;13:259-74.
  • Ezugwu AES, Agbaje MB, Aljojo N, et al. A comparative performance study of hybrid firefly algorithms for automatic data clustering. IEEE Access. 2020;8:121089-118.
  • Hu H, Liu J, Zhang X, Fang M. An effective and adaptable K-means algorithm for big data cluster analysis. Pattern Recognition. 2023;139:109404.
  • Ezugwu AE, Ikotun AM, Oyelade OO, et al. A comprehensive survey of clustering algorithms: state-of-the-art machine learning applications, taxonomy, challenges, and future research prospects. Engineering Applications of Artificial Intelligence. 2022;110:104743.
  • Ikotun AM, Ezugwu AE, Abualigah L, et al. K-means clustering algorithms: a comprehensive review, variants analysis, and advances in the era of big data. Information Sciences. 2023;622:178-210.
  • Ismkhan H. I-k-means−+: An iterative clustering algorithm based on an enhanced version of the k-means. Pattern Recognition. 2018;79:402-13.
  • Hussein A, Ahmad FK, Kamaruddin SS. Cluster analysis on COVID-19 outbreak sentiments from twitter data using K-means algorithm. Journal of System and Management Sciences. 2021;11:167-89.
  • Uddin MA, Roy S. Examining TOD node typology using k-means, hierarchical, and latent class cluster analysis for a developing country. Innovative Infrastructure Solutions. 2023;8:304.
  • Simsar S, Alborzi M, Ghatari AR, Varjani A. Residential appliance clustering based on their inherent characteristics for optimal use based K-means and hierarchical clustering method. Journal of Optimization in Industrial Engineering. 2023;16:119-27.
  • Bell JS, Koffie RM, Rattani A, et al. Global incidence of brain and spinal tumors by geographic region and income level based on cancer registry data. J Clin Neurosci. 2019;66:121-7.
  • Girardi F, Di Carlo V, Stiller C, et al. Global survival trends for brain tumors, by histology: analysis of individual records for 67,776 children diagnosed in 61 countries during 2000–2014 (CONCORD-3). Neuro-Oncology. 2023;25:593-606.
  • Lewis A, Bakkar A, Kreiger-Benson E, et al. Determination of death by neurologic criteria around the world. Neurology. 2020;95:e299-309. Erratum in: Neurology. 2020;95:802.
  • De Robles P, Fiest KM, Frolkis AD, et al. The worldwide incidence and prevalence of primary brain tumors: a systematic review and meta-analysis. Neuro-Oncology. 2015;17:776-83.
  • Haakenstad A, Irvine CMS, Knight M, et al. Measuring the availability of human resources for health and its relationship to universal health coverage for 204 countries and territories from 1990 to 2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet. 2022;399:2129-54.
  • Miranda-Filho A, Piñeros M, Soerjomataram I, et al. Cancers of the brain and CNS: global patterns and trends in incidence. Neuro Oncol. 2017;19:270-80.
  • Farmanfarma KK, Mohammadian M, Shahabinia Z, et al. Brain cancer in the world: an epidemiological review. World Cancer Res J. 2019;6:1-5.
  • Wanner M, Rohrmann S, Korol D, et al. Geographical variation in malignant and benign/borderline brain and CNS tumor incidence: a comparison between a high-income and a middle-income country. J Neurooncol. 2020;149:273-82.
  • Ostrom QT, Price M, Ryan K, et al. CBTRUS statistical report: pediatric brain tumor foundation childhood and adolescent primary brain and other central nervous system tumors diagnosed in the United States in 2014–2018. Neuro-Oncology. 2022;24:iii1-38.
  • Ostrom QT, Francis SS, Barnholtz-Sloan JS. Epidemiology of brain and other CNS tumors. Curr Neurol Neurosci Rep. 2021;21:68.
Yıl 2025, Cilt: 7 Sayı: 1, 100 - 106, 15.01.2025
https://doi.org/10.37990/medr.1536199

Öz

Kaynakça

  • Palmer JD, Prasad RN, Cioffi G, et al. Exposure to radon and heavy particulate pollution and incidence of brain tumors. Neuro-Oncology. 2022;25:407-17.
  • Wanis HA, Møller H, Ashkan K, Davies EA. The incidence of major subtypes of primary brain tumors in adults in England 1995-2017. Neuro Oncol. 2021;23:1371-82.
  • Monterroso P, Moore KJ, Sample JM, et al. Racial/ethnic and sex differences in young adult malignant brain tumor incidence by histologic type. Cancer Epidemiol. 2022;76:102078.
  • Alvarez EM, Force LM, Xu R, et al. The global burden of adolescent and young adult cancer in 2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Oncol. 2022;23:27-52.
  • Alemu BS, Feisso S, Mohammed EA, Salau AO. Magnetic resonance imaging-based brain tumor image classification performance enhancement. Scientific African. 2023;22:e01963.
  • IHME. GBD Compare. www.healthdata.org/data-tools-practices/interactive-visuals/gbd-compare access date 10.07.2024.
  • Leong YQ, Lee SWH, Ng KY. Cancer risk in Parkinson disease: An updated systematic review and meta‐analysis. Eur J Neurol. 2021;28:4219-37.
  • Nudelman KNH, Risacher SL, West JD, et al. Association of cancer history with Alzheimer's disease onset and structural brain changes. Front Physiol. 2014;5:423.
  • Natale G, Cucchiara F, Bocci G. Historical overview of the “firing” liaison between brain tumors and epilepsy. Neuroscientist. 2021;28:411-9.
  • Sirko A, Dzyak L, Chekha E, et al. Coexistence of multiple sclerosis and brain tumours: case report and review. Interdisciplinary Neurosurgery. 2020;19:100585.
  • Cortés Mancera EA, Sinisterra Solis FA, Romero-Castellanos FR, et al. 18F-FDG PET/CT as a molecular biomarker in the diagnosis of amyotrophic lateral sclerosis associated with prostate cancer and progressive supranuclear palsy: a case report. Front Nucl Med. 2023;3:1137875.
  • Lima AA, Mridha MF, Das SC, et al. A Comprehensive survey on the detection, classification, and challenges of neurological disorders. Biology. 2022;11:469.
  • Abbas SA, Aslam A, Rehman AU, et al. K-Means and K-Medoids: cluster analysis on birth data collected in City Muzaffarabad, Kashmir. IEEE Access. 2020;8:151847-55.
  • Rizvi SA, Umair M, Cheema MA. Clustering of countries for COVID-19 cases based on disease prevalence, health systems and environmental indicators. Chaos Solitons Fractals. 2021;151:111240.
  • Nabors LB, Portnow J, Ahluwalia M, et al. Central Nervous System Cancers, Version 3.2020, NCCN Clinical Practice Guidelines in Oncology. J Natl Compr Canc Netw. 2020;18:1537-70.
  • Lambrou GI, Zaravinos A, Braoudaki M. Co-deregulated miRNA signatures in childhood central nervous system tumors: in search for common tumor miRNA-related mechanics. Cancers. 2021;13:3028.
  • Gaeta M, Campanella F, Capasso L, et al. An overview of different health indicators used in the European Health Systems. J Prev Med Hyg. 2017;58:E114-20.
  • Zarikas V, Poulopoulos SG, Gareiou Z, Zervas E. Clustering analysis of countries using the COVID-19 cases dataset. Data in Brief. 2020;31:105787.
  • Žmuk B. Quality of life indicators in selected European Countries: hierarchical cluster analysis approach. Croatian Review of Economic, Business and Social Statistics. 2015;1:42-54.
  • Akman M, Civek S. Frequency and risk assessment of cardiovascular diseases in the world and Turkey. Jour Turk Fam Phy. 2022;13:21-8.
  • Solberg CT, Sørheim P, Müller KE, et al. The devils in the DALY: prevailing evaluative assumptions. Public Health Ethics. 2020;13:259-74.
  • Ezugwu AES, Agbaje MB, Aljojo N, et al. A comparative performance study of hybrid firefly algorithms for automatic data clustering. IEEE Access. 2020;8:121089-118.
  • Hu H, Liu J, Zhang X, Fang M. An effective and adaptable K-means algorithm for big data cluster analysis. Pattern Recognition. 2023;139:109404.
  • Ezugwu AE, Ikotun AM, Oyelade OO, et al. A comprehensive survey of clustering algorithms: state-of-the-art machine learning applications, taxonomy, challenges, and future research prospects. Engineering Applications of Artificial Intelligence. 2022;110:104743.
  • Ikotun AM, Ezugwu AE, Abualigah L, et al. K-means clustering algorithms: a comprehensive review, variants analysis, and advances in the era of big data. Information Sciences. 2023;622:178-210.
  • Ismkhan H. I-k-means−+: An iterative clustering algorithm based on an enhanced version of the k-means. Pattern Recognition. 2018;79:402-13.
  • Hussein A, Ahmad FK, Kamaruddin SS. Cluster analysis on COVID-19 outbreak sentiments from twitter data using K-means algorithm. Journal of System and Management Sciences. 2021;11:167-89.
  • Uddin MA, Roy S. Examining TOD node typology using k-means, hierarchical, and latent class cluster analysis for a developing country. Innovative Infrastructure Solutions. 2023;8:304.
  • Simsar S, Alborzi M, Ghatari AR, Varjani A. Residential appliance clustering based on their inherent characteristics for optimal use based K-means and hierarchical clustering method. Journal of Optimization in Industrial Engineering. 2023;16:119-27.
  • Bell JS, Koffie RM, Rattani A, et al. Global incidence of brain and spinal tumors by geographic region and income level based on cancer registry data. J Clin Neurosci. 2019;66:121-7.
  • Girardi F, Di Carlo V, Stiller C, et al. Global survival trends for brain tumors, by histology: analysis of individual records for 67,776 children diagnosed in 61 countries during 2000–2014 (CONCORD-3). Neuro-Oncology. 2023;25:593-606.
  • Lewis A, Bakkar A, Kreiger-Benson E, et al. Determination of death by neurologic criteria around the world. Neurology. 2020;95:e299-309. Erratum in: Neurology. 2020;95:802.
  • De Robles P, Fiest KM, Frolkis AD, et al. The worldwide incidence and prevalence of primary brain tumors: a systematic review and meta-analysis. Neuro-Oncology. 2015;17:776-83.
  • Haakenstad A, Irvine CMS, Knight M, et al. Measuring the availability of human resources for health and its relationship to universal health coverage for 204 countries and territories from 1990 to 2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet. 2022;399:2129-54.
  • Miranda-Filho A, Piñeros M, Soerjomataram I, et al. Cancers of the brain and CNS: global patterns and trends in incidence. Neuro Oncol. 2017;19:270-80.
  • Farmanfarma KK, Mohammadian M, Shahabinia Z, et al. Brain cancer in the world: an epidemiological review. World Cancer Res J. 2019;6:1-5.
  • Wanner M, Rohrmann S, Korol D, et al. Geographical variation in malignant and benign/borderline brain and CNS tumor incidence: a comparison between a high-income and a middle-income country. J Neurooncol. 2020;149:273-82.
  • Ostrom QT, Price M, Ryan K, et al. CBTRUS statistical report: pediatric brain tumor foundation childhood and adolescent primary brain and other central nervous system tumors diagnosed in the United States in 2014–2018. Neuro-Oncology. 2022;24:iii1-38.
  • Ostrom QT, Francis SS, Barnholtz-Sloan JS. Epidemiology of brain and other CNS tumors. Curr Neurol Neurosci Rep. 2021;21:68.
Toplam 39 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Beyin ve Sinir Cerrahisi (Nöroşirurji)
Bölüm Özgün Makaleler
Yazarlar

Yunus Emre Karataş 0000-0001-6488-1685

Songül Çınaroğlu 0000-0001-5699-8402

Yayımlanma Tarihi 15 Ocak 2025
Gönderilme Tarihi 20 Ağustos 2024
Kabul Tarihi 22 Kasım 2024
Yayımlandığı Sayı Yıl 2025 Cilt: 7 Sayı: 1

Kaynak Göster

AMA Karataş YE, Çınaroğlu S. Global Outlook for Disability Adjusted Life Years: Brain and Central Nervous System Cancers. Med Records. Ocak 2025;7(1):100-106. doi:10.37990/medr.1536199

 Chief Editors

Assoc. Prof. Zülal Öner
Address: İzmir Bakırçay University, Department of Anatomy, İzmir, Turkey

Assoc. Prof. Deniz Şenol
Address: Düzce University, Department of Anatomy, Düzce, Turkey

Editors
Assoc. Prof. Serkan Öner
İzmir Bakırçay University, Department of Radiology, İzmir, Türkiye

E-mail: medrecsjournal@gmail.com

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