Eduardo Rosenblatt1, Elena Fidarova2, Eduardo H Zubizarreta2, Michael B Barton3, Glenn W Jones4, William J Mackillop5, Lisbeth Cordero6, Joel Yarney7, Gerard Lim8, John V Gan9, Valentin Cernea10, Suzana Stojanovic-Rundic11, Primoz Strojan12, Lotfi Kochbati13, Aldo Quarneti14. 1. International Atomic Energy Agency, Vienna, Austria. Electronic address: rosenblatt21@gmail.com. 2. International Atomic Energy Agency, Vienna, Austria. 3. Ingham Institute for Applied Medical Research, UNSW, Sydney, Australia. 4. The Cancer Centre Eastern Caribbean, St. John's, Antigua and Barbuda. 5. Division of Cancer Care and Epidemiology, Kingston, Canada. 6. Hospital Mexico, San Jose, Costa Rica. 7. Centre for Radiotherapy and Nuclear Medicine, Korle Bu Teaching Hospital, Accra, Ghana. 8. National Cancer Institute, Putrajaya, Malaysia. 9. Jose R. Reyes Memorial Medical Centre, Quezon City, Philippines. 10. Oncology Institute, Cluj-Napoca, Romania. 11. Institute of Oncology and Radiology of Serbia, Belgrade, Serbia. 12. Institute of Oncology, Ljubljana, Slovenia. 13. Institut National de Cancer Salah Azaïz, Tunisia. 14. Hospital Pereira Rossell, Montevideo, Uruguay.
Abstract
BACKGROUND: The planning of national radiotherapy (RT) services requires a thorough knowledge of the country's cancer epidemiology profile, the radiotherapy utilization (RTU) rates and a future projection of these data. Previous studies have established RTU rates in high-income countries. METHODS: Optimal RTU (oRTU) rates were determined for nine middle-income countries, following the epidemiological evidence-based method. The actual RTU (aRTU) rates were calculated dividing the total number of new notifiable cancer patients treated with radiotherapy in 2012 by the total number of cancer patients diagnosed in the same year in each country. An analysis of the characteristics of patients and treatments in a series of 300 consecutive radiotherapy patients shed light on the particular patient and treatments profile in the participating countries. RESULTS: The median oRTU rate for the group of nine countries was 52% (47-56%). The median aRTU rate for the nine countries was 28% (9-46%). These results show that the real proportion of cancer patients receiving RT is lower than the optimal RTU with a rate difference between 10-42.7%. The median percent-unmet need was 47% (18-82.3%). CONCLUSIONS: The optimal RTU rate in middle-income countries did not differ significantly from that previously found in high-income countries. The actual RTU rates were consistently lower than the optimal, in particular in countries with limited resources and a large population. Crown
BACKGROUND: The planning of national radiotherapy (RT) services requires a thorough knowledge of the country's cancer epidemiology profile, the radiotherapy utilization (RTU) rates and a future projection of these data. Previous studies have established RTU rates in high-income countries. METHODS: Optimal RTU (oRTU) rates were determined for nine middle-income countries, following the epidemiological evidence-based method. The actual RTU (aRTU) rates were calculated dividing the total number of new notifiable cancerpatients treated with radiotherapy in 2012 by the total number of cancerpatients diagnosed in the same year in each country. An analysis of the characteristics of patients and treatments in a series of 300 consecutive radiotherapy patients shed light on the particular patient and treatments profile in the participating countries. RESULTS: The median oRTU rate for the group of nine countries was 52% (47-56%). The median aRTU rate for the nine countries was 28% (9-46%). These results show that the real proportion of cancerpatients receiving RT is lower than the optimal RTU with a rate difference between 10-42.7%. The median percent-unmet need was 47% (18-82.3%). CONCLUSIONS: The optimal RTU rate in middle-income countries did not differ significantly from that previously found in high-income countries. The actual RTU rates were consistently lower than the optimal, in particular in countries with limited resources and a large population. Crown
Authors: Wee Loon Ong; Norah Finn; Luc Te Marvelde; Colin Hornby; Roger L Milne; Gerard G Hanna; Graham Pitson; Hany Elsaleh; Jeremy L Millar; Farshad Foroudi Journal: J Med Imaging Radiat Oncol Date: 2022-03-31 Impact factor: 1.667
Authors: Francis A Asamoah; Joel Yarney; Shivanshu Awasthi; Verna Vanderpuye; Mary A Dadzie; Angelina Fink; Arash O Naghavi; Afua Abrahams; James E Mensah; Evans Sasu; Samuel N Tagoe; Jasreman Dhillon; Peter A S Johnstone; Kosj Yamoah Journal: Am J Clin Oncol Date: 2019-12 Impact factor: 2.339