Discussion
Our findings summarise the existing evidence on costs and cost-effectiveness of various paediatric cancer treatments in LMICs. Where available, the cost per DALY averted associated with childhood cancer treatment was less than country per capita GDP, thus meeting criteria for being very cost-effective as per WHO-CHOICE guidelines.
GDP-based cost-effectiveness thresholds are the subject of ongoing debate and suggested cut-offs vary widely among experts. Some scholars have argued that routinely used cost-effectiveness thresholds such as WHO-CHOICE are too high because they do not reflect health opportunity cost—that is, they do not account for health losses that occur because other interventions cannot be provided.56 The upper bounds of opportunity-cost-based cost-effectiveness thresholds have been estimated to be 0.51 and 0.71 times per capita GDP for LMICs, respectively.56 On the other hand, recent investment cases involving WHO health economists regard the total value of a life year across economic and social components to be 1.5 times GDP per capita, while the World Bank estimates the value of a life year at 1.4–4.2 times GDP per capita.57
Among the included studies we ranked as ‘Comprehensive’ or ‘Medium’, using the more conservative opportunity-cost-based thresholds, treatment of all childhood cancers in El Salvador and Ghana, ALL in Mexico, ALL in China, and Burkitt lymphoma in Uganda would remain cost-effective while treatment of ALL in Iran would no longer be cost-effective.
It is also important to note that the cost-effectiveness of an intervention may change over time. As shown in table 2, when comparing the three studies ranked as ‘Comprehensive’, as country GDP per capita increased, costs per DALY averted also increased. This parallel increase can be partly attributed to non-tradable costs such as healthcare personnel salaries and patient accommodations that increase as a country’s income level increases. In addition, as newer treatments or improved supportive care become available, survival rates improve over time, thereby impacting cost-effectiveness.
One systematic review identified and described economic evaluations of paediatric cancer treatment in HICs.20 Of the 40 studies identified in this review, 29 were supportive care studies (eg, growth colony stimulating factor) and 11 assessed tumour-directed therapies. The 11 tumour-directed therapy studies either investigated advanced interventions rarely described in LMICs such as stem cell transplant and radiation therapy or did not report cost-effectiveness as cost per DALY averted which limits comparison with results from our review.
Although global health agendas have generally prioritised treatment of communicable diseases, the prevalence of NCDs such as childhood cancer is rising in LMICs.4 Our study found that the cost per DALY averted for treatment of various paediatric cancers in LMICs ranged from US$22 to US$4475, or US$800 to US$4475 when excluding Burkitt lymphoma and studies ranked ‘Low’ in comprehensiveness of costs. These figures are comparable to the cost per DALY averted of other widely accepted public health strategies for paediatric communicable diseases such as pneumococcus, rubella and polio vaccines (2018 US$1094 to US$3281).58
The costs per DALY averted of treating childhood cancers in LMICs is also comparable to that of screening and treatment of breast cancer in LMICs (2018 US$2010–US$3913) and prevention of cervical cancer via human papilloma virus (HPV) vaccination (2018 US$184–US$5,652).59 There has been significant progress in funding and prioritisation of women’s cancers in LMICs, most notably for breast and cervical cancers. Similar efforts to prioritise childhood cancer in global health have begun with the recent WHO Global Initiative for Childhood Cancer. Through this Initiative, the WHO will support governments in expanding childhood cancer services and integrating childhood cancer into national strategies and health insurance packages.22 Our findings demonstrate that these goals can be achieved cost-effectively.
Developing national childhood cancer strategies may require consideration of variations in incidence of different types of childhood cancer across LMICs. Of the 366 600 new cases of childhood cancer estimated to have occurred in LMICs in 2015, the most common childhood cancer globally was ALL followed by non-Hodgkin’s lymphoma, Wilms tumour, Burkitt lymphoma and retinoblastoma.5 ALL was the most common cancer in most regions of the world except for sub-Saharan Africa.5 However, the overall incidence of childhood cancer was more than five times higher in Africa compared with Europe and North America together due to increased incidence of types of cancer other than ALL.5 In western Africa, there was a significantly higher burden of lymphomas, retinoblastomas and renal tumours, including 60% of the global incidence of Burkitt lymphoma. South-central Asia had the highest incidence of ALL, AML, Hodgkin lymphoma, neuroblastoma and central nervous system (CNS) tumours.5
Moreover, as shown in tables 1 and 2, cost and cost-effectiveness of treatment also vary by type of childhood cancer. One can assume that treatment costs would vary directly with treatment complexity including duration of chemotherapy, need for surgery, and need for supportive care. Treatment complexity is generally lower for malignancies requiring chemotherapy-only regimens of short duration such as Burkitt lymphoma and most lymphomas. Cancers requiring longer chemotherapy duration, such as ALL, or requiring surgery, such as Wilms tumour and retinoblastoma, are more complex, and cancers requiring highly intricate surgery, such as CNS tumours, or very highly intensive and prolonged chemotherapy, such as metastatic neuroblastoma, are most complex.60 It is also important to consider that availability of treatments, such as surgery or radiotherapy, may be a more significant barrier than cost in LMICs.
Although an intervention may be cost-effective, it is not necessarily affordable to families. In one study assessing the financial burden of Burkitt lymphoma treatment in Nigeria, one quarter of families could not afford the cost of diagnostic tests.48 About one-fifth of the children did not receive chemotherapy because their families were unable to pay and one-third of children withdrew from treatment due to financial constraints.48 Another study evaluating the costs to families of ALL treatment in India found that families spend up to seven times their monthly income during the first month of therapy.33 For children with leukaemia in LMICs, treatment abandonment rates as high as 74.5% have been described.61 Movements toward financial coverage of paediatric cancer treatment have begun in some LMICs including Tanzania, Mexico and China and are crucial to advancing affordability to families.62
Furthermore, the cost-effectiveness of an intervention does not necessarily imply that governments will prioritise a given issue including childhood cancer. In settings with limited resources, multiple factors such as justice, efficiency, political climate, economic growth and cultural values compete and contribute variably to shaping health system priorities.63 At times, social, cultural and political sentiments may prevail over cost-effectiveness or other purely economic factors in determining prioritisation of healthcare investments. Our findings can aid policymakers in considering childhood cancer treatment as a priority relative to other health interventions but cannot ultimately ensure allocation of policy attention and funding toward childhood cancer services in a given country’s specific context.
The main limitation of this systematic review relates to the quality of the existing literature in this area. Few economic evaluations in our study were of high methodological rigour, as demonstrated by their CHEERS checklist scores. Several studies did not outline assumptions made in study design, describe the analytical perspective of the study, or report a discount rate, and only five studies included a sensitivity analysis, all of which contributed to lower CHEERS checklist scores. Clearly outlining assumptions and conducting sensitivity analyses help mitigate the uncertainties inherent in most economic evaluations. Future economic evaluations in this area should adhere to the CHEERS checklist, which consolidates previous economic evaluation guidelines and provides recommendations to optimise the design and reporting of economic evaluations in healthcare. Doing so will not only produce more accurate data to help guide policymakers, but will allow comparisons between studies and settings.
Another important limitation relates to costing methodology. Among the ‘Comprehensive’ studies, the most significant cost inputs were healthcare personnel, chemotherapy, surgery, patient accommodations and administration. Although each of the 30 included studies considered costs of chemotherapy and/or surgery, only 11 included healthcare personnel salaries, only 15 included patient accommodations, and only three included administration costs. Omission of key cost inputs, particularly hospital administration, which accounts for utilities, space, human resource managers, and patient record and cancer registry staff, significantly underestimates total cost.64 For studies investigating ALL, costs per treated child ranged from US$801 to US$44 667. Although part of this discrepancy may be reflected in varying treatment protocols for different countries, this broad range likely also reflects the heterogeneity and uncertainty of inputs included in the cost analyses.
Poor reporting of cost inputs could be related to sources of study funding. Most studies ranked as ‘Comprehensive’ had funding sources from international organisations or HIC institutions. However, many ‘Low’-ranked studies also had funding from HIC institutions and two ‘Comprehensive’ studies did not specify any funding source, which suggests that study funding does not necessarily preclude conducting a rigorous economic evaluation.
Finally, only three studies included an analysis that adjusted their results for long-term morbidity and reduced life expectancy due to cancer-related or treatment-related late effects.16 18 30 Accounting for late effects resulted in decreased cost-effectiveness of the interventions likely due to a reduced number of DALYs averted and higher treatment costs when including costs of managing late effect complications. The impact of late effects of childhood cancer therapy is highly variable and contingent on the type and intensity of treatments applied, with corresponding variability in their impact on cost-effectiveness estimates. Their routine incorporation in future economic analyses of childhood cancer care will be essential to accurate estimation of the societal value of childhood cancer treatment over the life-course.
Despite these limitations, even when restricting our analyses to the most rigorous studies that accounted for key cost inputs and adjusted for late effects, cost-effectiveness remained well below internationally accepted GDP-based thresholds. This suggests that even if all omitted expenses were to be included in the less comprehensive studies and late effects were accounted for, LMIC childhood cancer treatment would likely remain consistently very cost-effective.
Given that methodologies including analytic perspective of studies and reported cost inputs varied considerably across studies investigating treatments of the same paediatric cancer, we elected not to conduct a meta-analysis. Improved methodological rigour in future studies will allow opportunity for meta-analysis.
