Journal of Cancer Therapy
Vol.05 No.11(2014), Article ID:50112,10 pages

Prescription of Cancer Treatment Modalities in Developing Countries: Results from a Multi-Centre Observational Study*

Rolando Camacho1#, Diogo Neves1, Marion Piñeros1, Eduardo Rosenblatt1, Robert Burton2, Yaima Galán3, Feras Hawari4, Saadettin Kilickap5, Cláudia Naylor6, Florian Nicula7, Jesus Reno8, Bhawna Sirohi9, Tatiana Vidaurre10, Kazem Zendehdel11

1International Atomic Energy Agency, Vienna, Austria

2Monash University, Melbourne, Australia

3Ministry of Health, La Habana, Cuba

4King Hussein Cancer Centre, Amman, Jordan

5Hacettepe University Oncology Centre, Ankara, Turkey

6National Cancer Institute José Alencar Gomes da Silva, Rio de Janeiro, Brazil

7Institute of Oncology Prof. Dr. Ion Chiricuţă, Cluj-Napoca, Romania

8National Institute of Oncology and Radiobiology, La Habana, Cuba

9Tata Memorial Hospital, Mumbai, India

10National institute of Neoplastic Diseases, Lima, Peru

11Cancer Research Center, Cancer Institute of Iran, Tehran University of Medical Sciences, Tehran, Islamic Republic of Iran


Copyright © 2014 by authors and Scientific Research Publishing Inc.

This work is licensed under the Creative Commons Attribution International License (CC BY).

Received 4 July 2014; revised 1 August 2014; accepted 1 September 2014


Background: Treatment is an important component of a comprehensive cancer control approach and its outcomes strongly depend on infrastructure, equipment, human and financial resources available. Therefore it is imperative to generate evidence-based tools to assist health policy mak- ers from low resourced countries in planning efficient and equitable treatment services for a de- fined population based on what it is feasible to these settings. Methods: The intended cancer spe-

cific treatment planned and written in the patients’ medical record (treatment prescription) of untreated adult cancer cases (≥18 years of age), excluding non-melanoma skin cancer, was re- corded in a chronological way from 1 January 2012 onwards in a group of eight comprehensive cancer centres located in middle income countries and offering the main modalities of cancer

treatment (surgery, medical oncology and radiotherapy). Results: A total of 17,713 medical re- cords were reviewed, of which 7106 (54.2%) met the eligibility criteria. Prescription of main can- cer treatment modalities were distributed as follows: 57.6% for chemotherapy (n = 4093), 56.8% for surgery (n = 4038), and 46.8% for radiotherapy (n = 3327). There was a predominance of plans consisting of combined treatment modalities over monotherapy (55.2% versus 44.8%). At the time of diagnosis 54.3% of the cancer cases had disease that had spread beyond the primary site, 41.2% were considered as having local disease and in 4.5% of the cases the information on disease extension was unknown. Conclusions: The results obtained should be seen as an approximation of cancer treatment service demand based on what it is currently practiced and therefore feasible in developing countries, particularly in middle income countries.


Cancer Treatment, Developing Countries, Health Services Needs and Demand, Resource Allocation, Observational Study

1. Introduction

Cancer is expected to become an increasingly important proportion of the global burden of disease in the dec- ades to come. According to the International Agency for Research on Cancer (IARC), there were 14.1 million estimated new cancer cases in 2012. These numbers are projected to rise to over 20 million every year by 2030 [1] . Today, about 60% of these new cases are from the developing world, and it is expected that by 2030 they will represent over 70% [2] . The current and foreseen cancer burden is challenging public health policy makers to implement comprehensive approaches in cancer control involving the different levels of care. This is particu- larly important in low resourced countries, where the cancer mortality to incidence ratios are significantly higher than in high income countries [1] .

Based on the knowledge and technology available today, it is estimated that approximately 40% of cancer deaths could be avoided by preventive measures, early detection and effective treatment [3] . Access to effective therapies as well as the introduction and dissemination of a multidisciplinary clinical approach in cancer patients’ management have proved to have a predominant effect on survival increase and mortality reduction for some cancers [4] - [6] . However, limited infrastructure, equipment and insufficient number of trained human resources to cover the current patient load impede the capacity of many developing countries to improve treatment out- comes [7] . Therefore, it is imperative to generate evidence-based tools to assist countries in planning efficient and equitable treatment services for a defined population based on an estimation of demand versus resources available.

Currently, information on cancer treatment service demand in low resourced settings is very limited. The main modalities of cancer treatment are surgery, systemic therapies (chemotherapy, hormonal therapy and bio- logical agents) and radiotherapy, which can be delivered alone or in combination and either with curative or pal- liative intent. The development of new and/or strengthening of operational services delivering these therapies is associated with increasingly high costs [8] , therefore making realistic projections is critical to maximize infra- structure, equipment, financial and human resources at a population level. Considering radiotherapy, the infor- mation available has been generated mainly in developed countries; the estimates of service demand are based on expert’s opinion [9] , rate of utilization [10] - [19] , or on what should be prescribed according to clinical guidelines [18] [20] [21] . However, patterns of cancer incidence, stage at diagnosis and access to treatment in developing countries are distinct, thus indications for surgery, systemic therapies and radiotherapy may vary considerably.

The present study aims to provide information on the frequency of prescription of the main treatment modali- ties in new cancer patients from eight comprehensive cancer centres located in different developing countries. Cancer treatment prescription was considered as the intended cancer specific treatment planed and written in the patients’ medical record; recording treatment delivery, completeness and outcome is out of the scope of this study. It is expected that this information will provide an estimate of the cancer treatment prescription rates and therefore have applicability in planning and allocating resources in developing countries.

2. Methods

This observational study was designed and coordinated by the Programme of Action for Cancer Therapy (PACT) of the International Atomic Energy Agency (IAEA), the Coordination Unit, in Vienna and conducted in eight comprehensive cancer centres located in developing countries, classified as middle income countries by the World Bank according to their Gross National Income (GNI) per capita in 2012 [22] from Asia, Europe, Latin America and Middle East regions.

2.1. Criteria for Selection of Centres

The pre-selection of participating centres was done by the Coordination Unit through review of IAEA reports of cancer control assessment missions, known as imPACT reviews [23] [24] , conducted from 2005 to 2012 in de- veloping Member States and information shared by Member States representatives at regional meetings on can- cer control organized by the IAEA, and by performing internet search to identify potential eligible centres.

The following criteria were used to identify potential participating centres: 1) have services for the main modalities of cancer treatment, namely surgery, medical oncology and radiotherapy; 2) be able to obtain data on cancer diagnosis and subsequent treatment modality/modalities prescribed in a chronological way from the hos- pital registry and/or medical records in 2012; 3) register on average 2000 or more new cancer patients every year; and 4) have over 50% of those patients initiating treatment at the centre.

Seventeen cancer centres were identified as potential candidates to be included in the study. To access eligi- bility, a brief questionnaire addressing the abovementioned criteria was sent to those centres; 16 responded and 10 met the criteria. Eligible centres were invited to an introductory technical meeting held in Vienna in April 2013 where cancer centres’ representatives confirmed availability of main cancer treatment services, existence of multidisciplinary teams for commonest cancer sites, and considered infrastructure, workforce, waiting time to commence treatment as adequate to the workload in 2012. Out-of-pocket expenditure was also reported as mi- nimal or non-existent in all centres. At the meeting, the feasibility of conducting the study was assessed and the protocol and timeline were discussed and approved.

The following eight cancer centres complied with the requirements1 and timeline and were included in the study: Brazil National Cancer Institute, Cancer Institute of Iran, Hacettepe University Oncology Hospital (Tur- key), Institute of Oncology “Prof. Dr. Ion Chiricuţă” (Romania), King Hussein Cancer Centre (Jordan), National Institute of Neoplastic Diseases (Peru), National Institute of Oncology and Radiobiology (Cuba), and Tata Me- morial Hospital (India).

2.2. Criteria for Selection of Cases

All patients that were registered in each participating cancer centre and were assigned with a medical record number in 2012 were recorded in a chronological way from 1 January 2012 onwards. From this pool of cases, the population to be analysed consisted of untreated adult cancer cases (≥18 years of age), excluding non-melanoma skin cancer, with an established treatment plan to be initiated in the cancer centre, or elsewhere.

Although all cancer centres in this study treat paediatric patients, those cases were excluded since the majority are referred to specialized haematological hospitals before establishing a treatment plan and the age limit of pa- tients admitted in the different paediatric oncology departments varied from 14 to 18 years of age.

2.3. Data Collection and Analysis

A database was created using Microsoft Excel 2007 and distributed to each participating cancer centre, in which seven variables were recorded for every eligible case. These variables were: age [1] ; gender [2] ; cancer site [3] ;

most valid method of diagnosis [4] ; extension of the disease [5] ; treatment prescribed [6] ; and, type of radiation therapy prescribed [7] . Cancer sites were coded according to the 10th edition of the International Classification of Diseases (ICD-10) [25] . Treatment modalities to be recorded were surgery, chemotherapy, radiotherapy, hor-

monal therapy, radio-iodine therapy and immunotherapy, alone or in combination.

The Coordination Unit received anonymous data submitted by the cancer centres between 1 June and 30 No- vember 2013 (“reporting period”), and performed periodic data quality control. Inconsistencies and incomplete- ness of data were discussed in a group meeting held in Vienna in December 2013. Final data from centres’ da- tabases were merged into one database and descriptive analyses were done using CDC Epi Info 7TM. The esti- mated new cancer cases of each one of the countries were grouped and considered as an independent population in Globocan 2012. The 10 most common cancer sites from the two populations, study and Globocan 2012, were compared through different non parametric statistical tests, namely the Wilcoxon signed-rank test and the Mann- Whitney U test, using IBM SPSS 15.0 software.

3. Results

During the reporting period, the group of eight comprehensive cancer centres reviewed a total of 17,713 medical records chronologically registered in 2012. Figure 1 shows how eligibility of cancer cases was assessed. Ga- thered information included 13104 confirmed cancer cases, of which 7106 (54.2%) were eligible and therefore considered as the sample to be analysed.

3.1. Characteristics of the Cancer Centres

In terms of accessibility and availability of services, all centres are integrated in their respective public health care systems and had the main modalities of treatment available in 2012. These services included surgical oncology department with specialized surgeons treating the main solid tumours, adequate number of opera- ting theatres and intensive care unit; operational and well-staffed medical oncology and radiotherapy de- partments.

All centres had clinical guidelines and/or protocols implemented and tumour boards established for the most common cancer sites. The mean and median estimated waiting time to commence radiotherapy treatment in the group of cancer centres in 2012 was 35 and 33 (range: 7 - 84 days) respectively.

The only private centre participating in the study was a not-for-profit cancer centre where cancer treatment is fully subsidized by the government and that currently treats about 60% of the cancer patients in the country. In all the selected cancer centres, cancer diagnosis and treatment was subsidized by the governments and out-of- pocket expenditure was considered minimal or non-inexistent.

3.2. Characteristics of the Study Population

From the 7106 eligible cases, 4337were female (61.0%) and 2769 were male (39.0%). The mean age of the pop- ulation analysed was 57 years of age (range: 18 - 99 years of age).

The five commonest cancers sites were breast, cervical, oral cavity, colorectal, and lung, which all combined accounted for more than half of the cases. Among women, breast and gynaecological cancers accounted for over 60% of the cancers, whereas among men the top cancer sites were head and neck, prostate, lung, and colorectal. Table 1 shows the most common cancer sites found in the study in both sexes and their respective frequency and distribution in the countries where the cancer centres are located based on Globocan 2012 estimates. The comparison of the distribution of cancer sites between these two populations showed no significant differences. Histopathology was the most valid method of diagnosis in 91.0% of the cases.

At the time of diagnosis over 54.3% of the cancer cases had disease that had spread beyond the primary site, 41.2% were considered as having local disease and in 4.5% of the cases the information on disease extension was unknown. The proportion of females diagnosed with local disease was about 10% higher than in males.

3.3. Treatment Modalities Prescribed

Figure 2 shows the distribution of modalities that were included in the treatment, where each bar corresponds to the combination of single and/or multi-therapy schemes where that particular treatment modality was indicated. Prescription of main cancer treatment modalities were distributed as follows: 57.6% for chemotherapy (n = 4093), 56.8% for surgery (n = 4038), and 46.8% for radiotherapy (n = 3327). Other therapies were prescribed in a small proportion of patients and in the majority of these cases in combination with main modalities; hormonal therapy (12.0%), radio-iodine therapy (2.0%) and immunotherapy (0.9%).

Figure 1. Flowchart for assessing eligibility of a cancer case.

Table 1. Most common cancers in study population and respective Globocan 2012 estimates for participant countries.

There was a predominance of treatment plans consisting of combination of treatment modalities over mono- therapy (55.2% versus 44.8%). Overall, the most common combination of treatment modalities involved che- motherapy and radiotherapy (16.6%) followed by surgery, chemotherapy and radiotherapy (10.8%), surgery and chemotherapy (9.2%), and surgery and radiotherapy (4.6%). Among treatment modalities prescribed alone, sur- gery, chemotherapy and radiotherapy accounted for 23.0%, 13.0% and 6.8% of all prescriptions, respectively. For those patients that had a prescription of radiotherapy, the large majority were planned to receive telethe- rapy only (74.0%) whilst 8.4% were prescribed to undergo both teletherapy and brachytherapy. Brachytherapy

Figure 2. Distribution of treatment modalities prescribed.

alone was prescribed in 9.3% of the radiotherapy patients. Information on the type of radiation therapy pre- scribed was not available in 8.2% of the cases, since in some cases the initial treatment plan did not specify type of radiation therapy. There was no mention of treatment with any other radio-isotope than iodine (I131).

When grouping patients into sub-populations according to extension of the disease, the findings show varia- tions in prescription among different treatment modalities. As illustrated in Figure 3, the proportion of patients with indications for surgery decreased gradually as disease advances from local to metastatic disease (from 72.8% to 25.7%), in contrast with the prescription of chemotherapy that increased (from 37.2% to 76.1%). The inclu- sion of radiotherapy in the first treatment plan varied from 41.1%, 61.9% and 31.5% in local, regional and dis- tant tumours, respectively. No major differences were noted in hormonal therapy, radio-iodine therapy and im- munotherapy.

4. Discussion

The sample in this study consisted of 7106 new adult untreated cancer patients, excluding non-melanoma skin cancer, consecutively registered in 2012. The results suggest a demand of surgery, chemotherapy and radiothe- rapy services of 57.6%, 56.8%, and 46.8%, respectively. In addition, hormonal therapy, radio-iodine therapy and immunotherapy were prescribed to 12.0%, 2.0% and 0.9% of the total cancer patients, respectively (Figure 2).

In planning oncology services, the impact on initial investment is more pronounced in radiotherapy than in the other cancer treatment modalities such as medical oncology and surgery, where infrastructure demand is generally determined at the hospital level. In these modalities, costs related to oncology medicines, surgical procedures, hos- pitalizations and workforce account for a much larger fraction than setting up treatment services. For these reasons, studies aiming at planning oncology services at a national level tend to focus on radiotherapy due to the expected higher capital costs of establishing a new radiotherapy facility. This initial investment could reach 5 - 6 million US $ in developing countries [26] . Studies in developed countries show that equipment and building costs for radio- therapy represent about 30% of the total costs, while wage costs account for about half [15] [27] . In developing countries, however, staffing costs are significantly lower and therefore the proportion of radiotherapy cost re- lated to the establishment of a new facility may be much higher.

The proportion of patients prescribed with radiotherapy in this study is in line with the common benchmark reported in recent years of at least 50% of new cancer patients requiring radiotherapy [20] . Reviewing the available literature, different approaches can be found in Table 2 concerning the estimation of radiotherapy de- mand in different countries.

In the majority of the studies, the number of patients that received treatment in the radiotherapy departments in a defined period of time was compared to the respective national cancer registry to understand how radiothe- rapy was being utilized in the care of cancer patients. The results in these assessments varied from 26% in Japan (2007) [19] to 48% in the Netherlands (1997) [14] . The results from the Dutch survey were consistent with the assessment made by the Swedish Council on Technology Assessment in Health Care (SBU) which in 2001 es- tablished a radiotherapy utilization rate of 47% in Sweden, 15% higher than in 1992 [11] [15] . Identical ap- proaches with somewhat similar results on radiotherapy utilization rate have been followed in Austria (42%) [16] , Italy (41%) [17] , and Spain (38%) [13] .

Figure 3. Distribution of treatment modalities prescribed according to the extension of the disease (local; regional; distant; unknown).

Table 2. Reported ratios of radiotherapy utilization in different countries/regions.

*: Not applicable; External beam radiation sessions; α: Prospective survey in radiotherapy departments; β: Retrospective survey in radiotherapy de- partments; δ: Governmental report on the use of special medical techniques, including radiotherapy; φ: Decision trees based on evidence-based guide- lines and population-based data; γ: Decision trees based on evidence-based guidelines (CCORE model) and estimated population-based data (Globocan 2002); σ: Expert’s opinion.

In the case of the Spanish and Italian surveys, the needs in radiotherapy accessibility were assessed by com- paring the findings with an expected radiotherapy utilization rate. In the case of the Spanish survey, Esco et al. proposed a benchmark of 60% of new and prevalent cancer cases needing radiotherapy as part of their treatment plan and calculated the needed resources to fulfill the estimated national demand by comparing with the esti- mated percentage of cancer cases that received radiotherapy in 1998 (38%). On the other hand, Pagano et al. calculated the gap in radiotherapy in Piedmont region (Italy) by applying the model developed by the Collabora- tion for Cancer Outcome Research and Evaluation (CCORE), which estimates the optimal radiotherapy utiliza- tion rate by combining epidemiological data with decision-trees based on clinical guidelines in Australia [20] ; the comparison suggested that the utilization of radiotherapy was about 15% lower than expected if those clini- cal guidelines would be fully implemented.

The model developed by CCORE and the estimate that 52% of cancer patients in Australia has been used as a gold standard level of radiotherapy utilization in both developed and developing countries. Similar to the Italian survey, this model was applied in the African population and suggested that 55% of the new cancer cases in that continent have an indication of radiotherapy [28] . This utilization rate relied on estimates taken from Globocan 2002, so no information on the staging of the disease was available. The authors further projected that due to the advanced nature of cancer cases at diagnosis, the radiotherapy utilization rate might be even higher in low and middle income countries as advanced tumours are unlikely to be as amenable to surgery and more often treated with palliative radiotherapy.

However, a study conducted in the São Paulo state in Brazil determined that radiation therapy was delivered in just over 40% of new cancer cases and that surgery and chemotherapy were provided to nearly 50% of these cancer patients [29] . In fact, even among high income countries with similar patterns of care and populations, such as Australian and British populations, indications for radiotherapy based on clinical guidelines can vary by about 10% [20] [21] . These disparities suggest that indications for treatment in developing countries derived from guidelines and standards of treatment followed by countries with higher availability of resources should be analysed with caution. In many countries, treatment plans are not supported by evidence although they are con- sidered common clinical practice in some hospitals and the optimal utilization of treatment modalities is often not feasible [30] , particularly in resource constrained settings.

Many developing countries are undergoing the process of setting up new radiotherapy services and different approaches have been taken to estimate the needed infrastructure and improve access to treatment. In India, te- letherapy needs were calculated based on the benchmark of one cobalt unit per one million population and based on this a shortfall of over 700 teletherapy units was reported in 2006 [31] . In contrast, in Romania a proposal on the expansion of radiotherapy services within the country was planned on the basis that 70% of the new cancer cases require radiation [32] . Although generalizing contexts must be done carefully, in the case of developing countries and having in mind that the IAEA reported that nearly 30 African and Asian countries have no radio- therapy services at all [26] , and only 23 African countries are known to have teletherapy [33] , it is important to generate information in constrained resources settings to support feasible solutions and to better assist national health planners in the decision making process.

This study which provides estimates of the main cancer treatment modalities prescribed to new cancer cases in developing countries aimed to generate evidence on what is currently realistic and feasible to meet demands on their health systems. More detailed analytical information gathered in constrained resources settings will shed light on the patterns of care and the different elements of access that affect the prescription and utilization of cancer therapies in developing countries.

An important limitation in cancer infrastructure planning in developing countries is the absence or underde- velopment of population-based cancer registries that can provide unbiased estimates of cancer incidence in a well-defined population [34] [35] . As a result, for many of these countries the best and sometimes the only avai- lable source of epidemiological information for planning cancer-related services is the Globocan database. This study took this into consideration and the eligibility criteria were therefore established to allow cross-checking with Globocan and therefore provide data that can be useful for health planners in low resourced settings. For this reason, the study captured only new cancer cases and excluded non-melanoma skin cancer. In order to overcome a possible treatment modality selection bias effect, only new untreated cancer patients were consi- dered in this study as many cancer patients in developing countries (about 25% of the total cancer cases reg- istered in the study) receive, for example, surgical treatment in a non-comprehensive cancer care centre and are subsequently referred to a specialized hospital to complete the treatment plan with chemotherapy and/or radiotherapy.

Even though there are variations in the GNI per capita (range: 1530 - 11630 USD) [22] and human develop- ment index (HDI) (range: 0.554 - 0.786) [36] among the group of countries in this study, the selected centres have similar characteristics in terms of their availability of treatment services including human resources and affordability for patients which are among the main elements of access to cancer treatment. Moreover, the aver- age estimated waiting time to commence treatment in the group of cancer centres is shorter than what has been suggested as the maximum corresponding waiting time tolerated by Australian cancer patients before deciding to travel to a more distant centre (one week less) or to stay away from home for the duration of treatment (two weeks less) [37] .

Considering the similarities among centres, the results obtained should be seen as an approximation of cancer treatment service demand based on what is currently practiced and therefore feasible in developing countries, particularly in middle income countries. Hence, the results are relevant for developing countries that are in the process of creating new or strengthening existent cancer treatment services in the context of a comprehensive national cancer control plan.


The authors wish to thank Dr. Milward Ubillus (National institute of Neoplastic Diseases, Peru) and Dr. Made- laine Sarria (National Institute of Oncology and Radiobiology, Cuba) for their support in completing informa- tion for their respective cancer centres; Dr. Fred Okuku (Uganda Cancer Institute, Uganda), Dr. Nguyen Nga and Dr. Pham Huy (K Hospital, Vietnam) for their contribution to the study design through participation in the introductory meeting held in Vienna in April 2013; Ms. Aisha Shtaiwi (King Hussein Cancer Centre, Jordan) and Dr. Chaitali Nashikkar (Tata Memorial Hospital, India) for their assistance in data collection; and Dr. Juan Lence (The Cuban Hospital, Qatar) for his helpful comments on the design of methodology of the study.


  1. Ferlay, J., Soerjomataram, I., Ervik, M., et al. (2013) Globocan 2012: Estimated Cancer Incidence, Mortality and Pre- valence Worldwide in 2012.
  2. World Health Organization (2005) Preventing Chronic Diseases: A Vital Investment. World Health Organization, Geneva.
  3. World Health Organization (2007) Fight against Cancer: Strategies That Prevent, Cure and Care. World Health Or- ganization, Geneva.
  4. Beral, V., Hermon, C., Reeves, G. and Peto, R. (1995) Sudden Fall in Breast Cancer Death Rates in England and Wales. Lancet, 345, 1642-1643.
  5. Kalager, M., Zelen, M., Langmark, F. and Adami, H.O. (2010) Effect of Screening Mammography on Breast Cancer Mortality in Norway. The New England Journal of Medicine, 363, 1203-1210.
  6. Autier, P., Boniol, M., La Vecchia, C., et al. (2010) Disparities in Breast Cancer Mortality Trends between 30 Euro- pean Countries: Retrospective Trend Analysis of WHO Mortality Database. BMJ, 341, c3620.
  7. Anderson, B.O., Yip, C.H., Smith, R.A., et al. (2008) Guideline Implementation for Breast Healthcare in Low Income and Middle Income Countries: Overview of the Breast Health Global Initiative Global Summit 2007. Cancer, 113, 2221-2243.
  8. Sullivan, R., Peppercorn, J., Sikora, K., et al. (2011) Delivering Affordable Cancer Care in High-Income Countries. The Lancet Oncology, 12, 933-980.
  9. Inter-Society Council for Radiation Oncology (ISCRO) (1991) Radiation Oncology in Integrated Cancer Management: Report of the Inter-Society Council for Radiation Oncology (Blue Book). American College of Radiology, Reston.
  10. Van Daal, W.A.J. and Bos, M.A. (1997) Infrastructure for Radiotherapy in the Netherlands: Development from 1970 to 2010. International Journal of Radiation Oncology * Biology * Physics, 37, 411-415.
  11. SBU: The Swedish Council on Technology Assessment in Health Care (1996) Radiotherapy for Cancer Vol. 1: Cost of Radiotherapy in Sweden. Acta Oncologica, 35, 57-71.
  12. Barton, M. (2000) Radiotherapy Utilization in New South Wales from 1996 to 1998. Australasian Radiology, 44, 308- 314.
  13. Esco, R., Palacios, A., Pardo, J., Biete, A., Carceller, J.A., Veiras, C., et al. (2003) Infrastructure of Radiotherapy in Spain: A Minimal Standard of Radiotherapy Resources. International Journal of Radiation Oncology & Biology & Physics, 56, 319-327.
  14. Slotman, B.J. and Leer, J.W.H. (2003) Infrastructure of Radiotherapy in the Netherlands: Evaluation of Prognoses and Introduction of a New Model for Determining the Needs. Radiotherapy and Oncology, 66, 345-349.
  15. SBU: The Swedish Council on Technology Assessment in Health Care (2003) Costs of Radiotherapy. Acta Oncologica, 42, 411-415.
  16. Ramona, M., Ulrike, M., Robert, J., Richard, P., Christian, V., Helmut, E., et al. (2004) Epidemiological Aspects of Hadron Therapy: A Prospective Nationwide Study of the Austrian Project MedAustron and the Austrian Society of Ra- diooncology (OEGRO). Radiotherapy and Oncology, 73, S24-S28.
  17. Pagano, E., Di Cuonzo, D., Bona, C., Baldi, I., Gabriele, P., Ricardi, U., et al. (2007) Accessibility as a Major Deter- minant of Radiotherapy Underutilization: A Population Based Study. Health Policy, 80, 483-491.
  18. Erridge, S.C., Featherstone, C., Chalmers, R., Campbell, J., Stockton, D. and Black, R. (2007) What Will Be the Radiotherapy Machine Capacity Required for Optimal Delivery of Radiotherapy in Scotland in 2015. European Journal of Cancer, 43, 1802-1809.
  19. Teshima, T., Numasaki, H., Shibuya, H., Nishio, M., Ikeda, H., Sekiguchi, K., et al. (2010) Japanese Structure Survey of Radiation Oncology in 2007 Based on Institutional Stratification of Patterns of Care Study. International Journal of Radiation Oncology & Biology & Physics, 78, 1483-1493.
  20. Delaney, G., Jacob, S., Featherstone, C. and Barton, M. (2005) The Role of Radiotherapy in Cancer Treatment: Esti- mating Optimal Utilization from a Review of Evidence-Based Clinical Guidelines. Cancer, 104, 1129-1137.
  21. Round, C.E., Williams, M.V., Mee, T., Kirkby, N.F., Cooper, T., Hoskin, P., et al. (2013) Radiotherapy Demand and Activity in England 2006-2020. Clinical Oncology, 25, 522-530.
  22. World Bank (2013) World Data Bank.
  23. International Atomic Energy Agency (2013) Programme of Action for Cancer Therapy.
  24. Camacho, R., Dangou, J.M., Neves, D., Morgan, S., Piñeros, M. and Cayol, J.P. (2014) Collaborative Activities of United Nations Agencies and Partners in Support of Cancer Control in Africa. African Journal of Cancer, 6, 3-10.
  25. World Health Organization (2010) International Statistical Classification of Diseases and Related Health Problems, 10th Revision. World Health Organization, Geneva.
  26. International Atomic Energy Agency (2010) Planning National Radiotherapy Services: A Practical Tool. International Atomic Energy Agency, Vienna.
  27. Van de Werf, E., Verstraete, J. and Lievens, Y. (2012) The Cost of Radiotherapy in a Decade of Technology Evolution. Radiotherapy and Oncology, 102, 148-153.
  28. Barton, M., Frommer, M. and Shaqif, J. (2006) Role of Radiotherapy in Cancer Control in Low-Income and Middle- Income Countries. The Lancet Oncology, 7, 584-595.
  29. Gomes Jr., S.C. and Almeida, R.T. (2009) Simulation Model for Estimating the Cancer Care Infrastructure Required by the Public Health System. Revista Panamericana de Salud Pública, 25, 113-119.
  30. Eniu, A., Carlson, R.W., El Saghir, N.S., Bines, J., Bese, N.S., Vorobiof, D., et al. (2008) Guideline Implementation for Breast Healthcare in Low and Middle Income Countries: Treatment Resource Allocation. Cancer, 113, 2269-2281.
  31. Murthy, N.S., Chaudhry, K. and Rath, G.K. (2008) Burden of Cancer and Projections for 2016, Indian Scenario: Gaps in the Availability of Radiotherapy Treatment Facilities. Asian Pacific Journal of Cancer Prevention, 9, 671-677.
  32. Cernea, V., Nagy, V., Irimie, A., Savu, M., Chis, A. and Chereji, I. (2008) Report Regarding the Present State of Radiotherapy Laboratories in Romania, National Program for Radiotherapy 2008-2010. Journal of Radiotherapy and Me- dical Oncology, 15, 7-24.
  33. Abdel-Wahab, M., Bourque, J.M., Pynda, Y., Iżewska, J., Van der Merwe, D., Zubizarreta, E., et al. (2013) Status of Radiotherapy Resources in Africa: An International Atomic Energy Agency Analysis. The Lancet Oncology, 14, e168- e175.
  34. Valsecchi, M.G. and Steliarova-Foucher, E. (2008) Cancer Registration in Developing Countries: Luxury or Necessity. The Lancet Oncology, 9, 159-167.
  35. Hanna, T.P. and Kangolle, A.C.T. (2010) Cancer Control in Developing Countries: Using Health Data and Health Ser- vices Research to Measure and Improve Access, Quality and Efficiency. BMC International Health and Human Rights, 10, 24.
  36. United Nations Development Programme (2013) UNDP: Human Development Reports.
  37. Lehman, M., Jacob, S., Delaney, G., Papadatos, G., Jalaludin, B., Cail, S., et al. (2004) Waiting Times for Radiother- apy: A Survey of Patients’ Attitudes. Radiotherapy and Oncology, 70, 283-289.


*Affiliations are as of 1 March 2014.

#Corresponding author.

1Requirements to participate in the study included confirmation of acceptance and nomination of an investigator by the Directors of participating cancer centres and submission and approval of the study protocol by respective institutional review boards.