Original Research

Cost evaluation of cancer care and treatment outside Lesotho: Provider perspective

Maseabata M. Ramathebane, Mopa A. Sooro, Lineo J. Maja, Kabelo Mputsoe, Mulungoa Sello, Motselisi C. Mokhethi

Received: 18 July 2024; Accepted: 20 Jan. 2025; Published: 30 Apr. 2025

Copyright: © 2025. The Author(s). Licensee: AOSIS.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background: Cancer is a global health burden with an increasing incidence, particularly in low- and middle-income countries. Cancer treatment is associated with a financial burden worsened by insurance status, treatment type and geographic location.

Aim: This study evaluates the cost of cancer treatment for patients treated outside Lesotho from the perspective of the healthcare service provider.

Setting: The study was carried out at the Ministry of Health (MOH) headquarters using payment bills and at the Senkatana Oncology Clinic using the patients’ clinical files.

Methods: A quantitative cross-sectional retrospective study analysed medical bills incurred between 2019 and 2022 and patients’ clinical files from the same period. The average costs of various treatment modalities were compared based on age, gender and cancer type.

Results: Of the 200 patients enrolled, 76% (n = 152) were females, and the majority were aged above 30 years (n = 183, 91.5%). Younger patients (below 30) faced the highest chemotherapy average costs, and radiotherapy average costs were highest for the 31–60 age group. The average cost of accommodation coefficient (1.216) showed a positive association, but it was not statistically significant (p = 0.625). A statistically significant difference was observed in the combination of radiotherapy and chemotherapy with accommodation (p = 0.001).

Conclusion: Cancer patients who seek cancer treatment outside the country undergo chemotherapy, radiotherapy and surgery, with the majority being on both chemotherapy and radiotherapy. A statistically significant difference was observed in the combination of radiotherapy and chemotherapy and accommodation.

Contribution: This study provides an understanding of cancer treatment costs outside Lesotho by enhancing budget insights and recommending a strategic approach.

Keywords: budget; cost; cancer clinic; chemotherapy; Lesotho.

Introduction

In sub-Saharan Africa (SSA), the cost of cancer treatment presents a significant challenge, further exacerbated by limited resources and infrastructure.^1,2 Access to comprehensive cancer care is often hindered by factors such as poverty, inadequate healthcare facilities and a shortage of trained medical personnel. According to Ngwa et al. in SSA, a patient’s financial capacity is always linked to an early diagnosis and successful treatment.³ The expenses associated with cancer treatment in this region can quickly escalate, encompassing diagnostics, surgery, chemotherapy, radiation therapy and supportive care.⁴ For instance, healthcare expenses are often paid for out-of-pocket by patients, which leads to many instances of catastrophic spending.³ Moreover, the scarcity of specialised oncology centres and essential medications often forces patients to travel long distances or seek care abroad, adding further financial strain.⁵ As a result, a considerable number of individuals in SSA are unable to access timely and adequate cancer treatment, leading to poorer health outcomes and increased mortality rates.⁶

Lesotho is a small landlocked country in Southern Africa, also experiencing the double burden of communicable and non-communicable diseases.⁷ In Lesotho, cervical cancer ranks as the most prevalent form of cancer, with breast cancer and prostate cancer following closely behind, collectively constituting over 60% of all cancer cases in 2020.⁸ Historically, Maseru Private Hospital provided cancer care in Lesotho with the assistance of an agreement between the Lesotho Government and a hospital in South Africa, which created a system of availing oncology services from the Free State capital of Bloemfontein.⁹ This agreement enabled an oncologist to travel from South Africa to Maseru Private Hospital to diagnose, treat and assess patients with suspected or confirmed cancer. The oncologists’ visits were financed by a government contract and this contract also enabled the hospital to provide the associated cancer services. Brown adds that this arrangement was beneficial to both healthcare professionals and patients with cancer. Healthcare professionals were trained in the management of cancer in areas such as drug administration, management of side effects, discharges and subsequent clinic appointments.⁹ Patients, on the other hand, benefited in that they were treated in our country, thus, they had support from their families, and they were able to avoid the expensive and bureaucratic travel process to South Africa. However, the agreement between the government of Lesotho and a hospital in South Africa was terminated in 2008 resulting in patients in dire need of treatment being referred to Bloemfontein or remaining in Lesotho, with treatment for symptoms rather than the underlying disease.

On a positive note, NGOs such as the Lesotho Breast Cancer Network and the Lesotho branch of the International Planned Parenthood Association raised awareness of cancer through public education programmes.⁹ In June 2020, Bristol Myers Squibb Foundation – Global Cancer Disparities (Africa) (BMSF – GCD) funded the establishment of the Senkatana Oncology Clinic to provide chemotherapy.¹⁰ In July 2022, Lesotho initiated the treatment of solid tumour patients, including those with breast cancer, at its inaugural cancer treatment facility, the Senkatana Oncology Clinic.¹¹ According to the 2022 annual report of Senkatana Oncology Clinic, the clinic registered 604 cancers in 2022, with 466 cases (77.2%) occurring in females and 138 (22.8%) in males. With the assistance from partners such as Elizabeth Glaser Pediatric AIDS Foundation¹² and Senkatana Screening Clinic is now providing full gynaecological services, focusing on cervical cancer screenings, diagnosis, pre-cancer treatment services and referrals to cancer treatment facilities, including chemotherapy. In addition, doctors and nurses in Lesotho were comprehensively trained on cervical cancer screening through Visual Inspection with Acetic Acid (VIA), Lugol’s Iodine and Pap smear.¹³ These healthcare professionals were further trained in thermocoagulation techniques for cervical cancer treatment to increase access to early treatment for patients who screened positive.

The cost of cancer treatment presents a significant challenge within the broader context of healthcare accessibility. The expenses associated with cancer treatment in Lesotho can be prohibitive for many individuals and families, particularly considering the country’s high poverty rates and limited financial resources.¹⁴ One of the significant challenges in Lesotho is the scarcity of specialised oncology facilities and trained medical personnel not only adds to the financial burden but also introduces logistical complexities for patients and their families.¹⁵ Treating cancer patients from Lesotho in Bloemfontein, a city in neighbouring South Africa, involves various costs and logistical challenges.⁴ According to Brown, a thesis by Phaaroe in 2007 indicated that the cost of referring all patients with invasive cancer in Lesotho to South African hospitals was ZAR108 000 (around $10 000) per patient, per course of treatment, thus, amounting to a total cost of ZAR10 692 000 at that time. Thus, Phaaroe proposed that primary-care screening and prevention could have saved most of this money for patients diagnosed with late-stage cancer. Currently, Lesotho spends around $7 million annually on the care and treatment of its cancer patients in South Africa and India.¹⁶

Lesotho’s overall health spending, 10.6% of gross domestic product (GDP) in 2014, was more than that of all its neighbours and slightly less than double the SSA average.¹⁷ At just 2.5% of GDP, private spending accounts for 24% of overall spending, followed by government spending at 44% and external spending (funded by donors and development partners) at 32%.¹⁷ Consequently, Lesotho patients pay less out-of-pocket expenses than most other SSA countries. Healthcare mainly comprises the public sector, fully sponsored by the government of Lesotho. The patients with cancer are referred to Universitas¹⁸ and Pelonomi,¹⁹ private hospitals in Bloemfontein, South Africa, which are Netcare hospitals in a public–private partnership with the Free State Department of Health. According to UNICEF and the World Bank, the Ministry of Health (MOH) provides funding for the delivery of specific medical treatments, such as cancer treatment, at the Universitas and Pelonomi hospitals in Bloemfontein because any hospital in Lesotho does not provide these services. Furthermore, in FY 2015/2016, Universitas received 30 million ZAR in payments, ranking as the fourth largest service provider. In FY 2015/2016, Pelonomi received 7.9 million ZAR in payments, ranking sixth among service providers. The cost of treating cancer patients from Lesotho in Bloemfontein includes consultation fees, professional fees, prescribing fees, diagnostic tests, chemotherapy, radiotherapy, surgeries, medications, hospitalisation and supportive care.^20,21,22 Furthermore, there are costs associated with transportation, accommodation and other living expenses for patients and their accompanying family members.²⁰

The sustainable development goals (SDGs) have set targets, specifically Goals 11 and Target 3.4, which call for the end of poverty in all its forms and the attainment of a one-third reduction in non-communicable diseases-related premature mortality by 2030, respectively.²² When the economic cost of cancer is known, relevant policies are formulated.²³ Appropriate resources are allocated for the healthcare system that will cope with the ever-increasing cancer burden.²³ Direct costs consist of medical and non-medical costs incurred because of resource utilisation from inpatient and outpatient healthcare events associated with illness detection, treatment and follow-up care.^23,24 These include transport and caregivers’ costs. On the other hand, indirect costs consist of productivity losses as a result of work absence because of morbidity and premature mortality from cancer.²⁵ The sum of the two types of costs (direct and indirect) expresses the economic burden associated with illness.²⁴ Therefore, the study aimed to evaluate the cost of cancer treatment for patients treated outside Lesotho from the perspective of the healthcare service provider.

Methods

Study design

The study followed a quantitative cross-sectional retrospective design using cancer care medical files and treatment medical bills from hospitals outside of Lesotho, where Lesotho patients were diagnosed and treated for cancer.

Study setting

The study was carried out at the MOH headquarters using payment bills and the Senkatana Oncology Clinic using the patients’ clinical files. The MOH covers the cost of cancer care and treatment offered inside and outside the country. The costs include patients’ clinical care and accommodation. The study focussed on the costs of care and treatment outside Lesotho. Senkatana Oncology Clinic is the first cancer treatment clinic in Lesotho. This clinic is a gateway for cancer patients to be referred outside the country for care and treatment of cancer. Information regarding cancer staging and treatment outcomes is kept at the clinic and was used in the study.

Study population and sample determination

The medical bills belonging to patients with cancer were reviewed, and data were extracted from patients diagnosed and treated in hospitals outside Lesotho.

Sample size

The MOH gave a total of 1000 medical bills to the research assistants. These medical bills were packed in 11 boxes according to the month the bill was issued. About 492 medical bills were included in the study, covering 200 patients with an average of 5 (1–13) medical bills per patient. Each medical bill comprised patient demographic information and all medical information on the cost of chemotherapy, radiotherapy, surgery, laboratory tests, accommodation and prescribing fees, professional fees, consultation and medicines used for various purposes. All the medical bills belonging to one patient covering different types of treatment in different months were used to calculate the total cost of treating a cancer patient outside Lesotho. Telephone numbers from the medical bills were recorded and used as unique identifiers to search and match patients’ medical records at Senkatana Oncology Clinic. Information regarding staging and treatment outcomes for individual patients was recorded and formed part of the data collected.

Data collection instruments

Data collection forms (DCFs) were developed and revised several times to suit the medical bills and minimise errors and variations. International Classification of Diseases, tenth revision (ICD 10) codes were used for cancer types, and costs were expressed in Rand (ZAR) monetary terms. The Rand dollar exchange used was 1 USD, equivalent to 18 ZAR. The collection form included patient demographic information, different types of cancers using ICD 10 classification and their treatments, professional fees, laboratory tests, accommodation and transportation. The cost of each item was calculated where necessary and recorded on the DCF. Clinical staging and the Eastern Cooperative Oncology Group (ECOG) score and treatment outcome were recorded from the medical files at the Senkatana Oncology Clinic.

Data gathering process

Data collection forms were used to collect data from medical bills. There were 1000 medical bills in 11 boxes. The first step was to write all patients’ names in each box for identification purposes. If one patient’s medical bill were picked, all other medical bills would be picked from all the boxes in which their name appeared. All the details from the medical bill were recorded in the DCF and information from other medical bills from different boxes was also included. This was performed to ensure that all the medical bills were included to show how much each patient was treated with. All the identified medical bills were used to calculate the total cost for one patient and about 492 medical bills were used for 200 patients.

Cost determination

The Government of Lesotho pays for all expenses for patients treated outside Lesotho. The costs retrieved from medical bills from hospitals outside Lesotho are kept in the finance department of the MOH. The medical bills covered 4 years (2019–2022). All the costs were direct medical costs. For this study, the total costs were calculated from direct medical and therapy-related costs, which are in the results section. The total cost of treatment comprised direct medical costs plus therapy-related costs. Direct medical costs included pre- and post-chemotherapy, chemotherapy, radiotherapy, surgery and related medicines, injections and solutions, and palliative care medication. Therapy-related (for chemotherapy, radiotherapy or surgery) costs included prescribing, professional, consultation, ambulatory and accommodation fees. The reason for separating these costs was that all were direct medical costs, but the other related costs would highlight whether providing treatment in-country would have been less costly.

Data analysis

Data were captured onto a Microsoft Excel^® spreadsheet. Altair AI Studio Educational 2024.1 was used to analyse data using descriptive and inferential statistics. The inferential statistics used included the Correlation Matrix, Analysis of Variance (ANOVA) and Logistic Regression Model.

Ethical considerations

Ethical approval was granted by the Lesotho MOH, National Research and Ethics Committee (NHREC) (reference no.: 04-2023). Permission was sought from the MOH to conduct the study. No informed consent forms were filled out because only records were used. The research assistants and researcher signed the confidentiality form to keep information from the bill confidential. Data collection took place at the MOH and bills were returned to the relevant office. All research data were encrypted and stored in a password-protected computer system.

Results

Demographic information

The MOH provided 1000 medical bills for patients with cancer treated outside Lesotho between 2019 and 2022. The study included 492 medical bills belonging to 200 patients with cancer, representing 49.2% of the medical bills.

Table 1 provides an overview of participants’ demographics and cancer-related conditions, highlighting trends in gender, age distribution and cancer types within the sample. Female participants were 152 individuals, constituting 76.0% of the total sample. Male participants were 48 (24.0%). Participant’s age groups (years) ≤ 30 years: 17 individuals (8.5%), indicating a small proportion of younger participants. A total of 112 individuals of 31–60 years (56.0%) represent the majority of participants indicating that middle-aged individuals dominate the sample. A total of 71 individuals ≥ 61 years (35.5%) represent a significant portion of the older participants. Breast cancer accounted for 47 cases, representing 23.5% of the total. Cervical cancer had 48 cases, representing 24.0% of the total. Prostate cancer includes 12 cases, making up 6.0% of the total. Other cancers include different cases of cancers (46.65%, n = 93).

The correlation matrix between the average cost of treatment modalities and independent variables

Figure 1 shows a correlation matrix between the cost of chemotherapy, radiotherapy, surgery, accommodation and professional fees against the participants’ district, gender, marital status, and the number of chemotherapy cycles and radiotherapy sessions. What can be highlighted is the positive correlation between accommodation and professional fees (0.895), accommodation and the number of radiotherapy sessions (0.729). Another positive correlation to notice is the one between radiotherapy and the number of radiotherapy sessions (0.981).

FIGURE 1: Correlation matrix between average costs of five highest cost categories (ZAR) and age, gender, marital status, district and type of cancer.

Table 2 shows costs associated with different treatment categories for patients, analysed by cancer type, gender and age category. It also includes F-statistic and p-values for statistical analysis. Other cancers (n = 93) generally have the highest average costs across accommodation, professional fees, radiotherapy and surgery. Cervical cancer (n = 48) has negligible surgery average costs. F-statistics and p-values are recorded and p-values marked with an asterisk (*) indicate significant average cost differences among cancer types, where accommodation (p = 0.000), professional fees (p = 0.001), radiotherapy (p = 0.000) and surgery (p = 0.000) show significant differences. Male patients (n = 48) generally incur lower average costs in chemotherapy and higher average costs in radiotherapy than females. Younger patients (below 30) face the highest chemotherapy average costs, while older patients (above 61) tend to have lower chemotherapy and accommodation average costs. Radiotherapy average costs are highest for the 31–60 years age group. F-Statistics and p-values of radiotherapy average costs significantly differ by age group (p = 0.017*).

Logistic regression model

Table 3 shows the results of a logistic regression analysis that is intended to explain the relationship between dependent and independent variables. The independent variables are the type of cancer, gender, age, marital status, the number of chemotherapy cycles and the number of radiotherapy sessions. The dependent variables are the average cost of various treatment modalities, accommodation and professional fees. The coefficient of 21.861 indicates that older age positively affects the average costs, but it is not statistically significant (p = 0.732). Number of radiotherapy session coefficient (3.058) indicates the positive relationship between the average costs and statistically significant (p = 0.019), meaning the number of radiotherapy sessions is positively associated with the average cost of radiotherapy.

Correlation matrix between professional fees, accommodation and treatment modalities

Figure 2 shows the results correlation matrix indicating a positive correlation between the number of chemotherapy cycles (0.744) highlighted in red and radiotherapy sessions (0.770) and also highlighted in red and a combination of radiotherapy, chemotherapy, professional fees and accommodation average costs. To a lesser extent, blue signifies a negative correlation, which is prominent to the number of chemotherapy cycles (−0.45) and radiotherapy sessions (−0.42) against the combination of average costs of professional fees, accommodation and radiation.

FIGURE 2: Correlation matrix showing the number of chemotherapy cycles, radiotherapy sessions and treatment modalities, including professional fees and accommodation average costs.

Males (n = 6) consistently show lower or no costs across treatment categories than females (n = 91). Statistically significant differences were observed in radiotherapy, professional fees and accommodation (p = 0.000), where females (37018.84) have much higher average costs than males (Table 4). For those who received a combination of radiotherapy, chemotherapy, professional fees and accommodation (p = 0.053), females (36827.34) had significantly higher average costs, and males had no cost. In terms of professional fees, surgery and accommodation (p = 0.001), males (27848.27) had a significantly higher average cost than females (8206.56). Average costs against age categories showed no significant differences across age groups (p > 0.05 for all categories). Even though average costs varied, the differences did not reach statistical significance. Cervical cancer (n = 29) shows moderate average costs across categories. Prostate cancer (n = 6) had the highest average costs (49342.17) for professional fees, accommodation and surgery. Other cancer types (n = 53) show relatively moderate average costs, with high expenses in radiotherapy, professional fees and accommodation (35599.03). A statistically significant difference is observed in radiotherapy, professional fees, chemotherapy and accommodation (p = 0.000).

Discussion

The demographic data collected from patients with cancer treated outside of Lesotho between 2019 and 2022 shows that 76% of the patients were female, which is indicative of the high incidence of breast and cervical cancers in the general population. Male patients consist of 24% of the participants, which is consistent with a lower incidence of prostate cancer than malignancies peculiar to women. Most patients (56%) are in the age range of 31 to 60 years, with those over 60 coming in second (35.5%). Similarly, a study conducted in selected regions of SSA found that one-third of all patients with cancer were elderly (60 years and above).²⁶ The findings of this study further indicate that only 8.5% of patients were younger than 30 years old, suggesting that cancer incidence is lower in this age range. Among the listed types of cancers were prostate cancer (6.0%), cervical cancer (24.0%), breast cancer (23.5%) and other cancers (46.5%). This distribution highlights the substantial incidence of cervical and breast cancer in women, whereas prostate cancer was least represented. According to the ICO/IARC HPV Information Centre, cervical cancer is the most common cancer among women in Lesotho and the most common cancer among women aged 15 to 44.²⁷

In this study, several factors and treatment average costs are strongly correlated. The average cost of accommodation was positively correlated with the number of radiotherapy sessions (0.729) and professional fees (0.895), indicating the logistical difficulties of obtaining extended treatment outside the country. A similar relationship between high transportation costs and financial stress was found in some studies that examined the financial toxicity associated with transportation for patients receiving radiation treatment.^28,29 In addition, in this study, the cost of radiotherapy showed a substantial correlation with the number of sessions (0.981), highlighting the direct effect of session frequency on total expenditures. These associations demonstrate the substantial cost burden of cancer treatment, especially for long-term therapies. Similarly, some studies that analysed the average cost of treatment per procedure in Brazil revealed that patients who received radiotherapy and surgery and only radiotherapy had the highest costs.^30,31,32

This study also revealed differences in treatment costs by gender where the average cost of radiotherapy was greater for female patients (16904.74 ZAR) than for male patients (10942.44 ZAR), most likely because more cervical cancer cases required intense radiation treatment. In contrast, although not statistically significant, the average cost of surgery for men was marginally greater (1530.36 ZAR) than for women (1087.02 ZAR). A Brazilian study found that the cost of treatment for male patients was 14% more than that of female patients (β = 0.14, p < 0.001).³⁰

Furthermore, the findings of this study indicate that patients under 30 years of age had the lowest accommodation costs (2055.23 ZAR) but the greatest chemotherapy expenditures (6293.11 ZAR), most likely because of shorter treatment durations. Patients aged 31 to 60 had the highest radiotherapy costs (18386.01 ZAR, p = 0.017*), reflecting treatment intensity throughout middle age. Likewise, a study by De Oliveira et al. found that the age of a patient can affect the cost of cancer because younger patients may have more aggressive treatments.³³ This study further reveals that patients over 60 years had the lowest chemotherapy costs (1999.33 ZAR), which may have been caused by treatment limits associated with ageing. In agreement, some studies indicated that the cost of treatment decreased with increasing age, higher levels of deprivation and more comorbidities.^30,33 This is likely because of frailty and a lack of perceived suitability for treatment, which may have prevented these groups from accessing or utilising treatment.³⁴

Moreover, the findings of this study reveal that the highest average cost of radiotherapy was for cervical cancer (41505.06 ZAR, p = 0.000*), which indicates the complex and intensive nature of the treatment. Prostate cancer consistently had the lowest average costs across all treatment modalities, while breast cancer had somewhat high chemotherapy expenses (4575.75 ZAR). Similarly, in a Brazilian study, Lana et al. revealed that, in terms of type of cancer, patients with cervix cancer had the greatest mean cost (PPP $16656.0), while patients with breast cancer had the lowest (PPP $5782.1).³⁰ Furthermore, this study indicates that other patients with cancer had the greatest total costs for various forms of treatment, highlighting the diverse and sometimes challenging nature of treating these patients. The expenditures of professional fees, accommodation and treatment varied statistically significantly throughout cancer types, highlighting the necessity of focussed resource allocation.

The findings of this study further reveal that overall expenditures are positively correlated with the number of radiotherapy sessions (coefficient = 0.682, p = 0.019*), highlighting the importance of this factor in driving costs. In contrast, there is a negative correlation between the outcome variable and higher radiation costs (coefficient = −7.465, p = 0.031*), indicating possible inefficiencies or limitations in the affordability of treatment. Accommodation costs show a positive but statistically insignificant association with outcomes, while baseline costs vary significantly depending on the predictors.

Limitations of the study

The results of this study should be interpreted with caution as there was no access to information from patients’ medical records that could have been used to fill in some of the missing information and verify some of the queries on treatment outcomes. In addition, the study examined previous medical bills, noting that there may be missing information; thus, generalisation of the results should be avoided. It is also worth mentioning that the medical bills used fall under the coronavirus disease 2019 (COVID-19) period; even though treatment referrals continued, some of the patient treatment might have been postponed upon receipt of positive test results of COVID-19, affecting the continuity of care. Lastly, it is worth mentioning that with the inferential statistics used, correlation does not imply causation.

Conclusion

The demographic and financial data analysis reveals key insights into the characteristics and cost implications of treating patients outside Lesotho. A higher proportion of female patients was observed across all age groups, with most patients over 30. Patients originated from all three regions of Lesotho, with Maseru being the most represented. Significant correlations were identified between accommodation costs and professional fees, accommodation and the number of radiotherapy sessions, and radiotherapy costs with the number of sessions. Younger patients under 30 years incurred the highest average costs for chemotherapy, while those aged 31–60 faced the highest radiotherapy costs. The statistically significant difference (p = 0.001) observed in the combination of radiotherapy, chemotherapy, professional fees and accommodation highlights high variability, possibly because of diverse cancer types such as prostate cancer. The findings indicate that treating patients outside the country increases treatment costs because of professional fees and accommodation costs, which adds financial burden to the treatment modalities. These insights underscore the potential for significant cost savings by strengthening in-country healthcare infrastructure to manage cancer treatment locally, thereby reducing reliance on external facilities and associated costs. A proposed study is a cost-effectiveness evaluation, which can compare cost and treatment outcomes and also compare in-country and outside-the-country care, which could provide valuable insights for policymakers to improve healthcare access and quality.

Recommendations

The study was based on the provider’s perspective, which is the MOH. Based on the results, the following recommendations are made:

• Data-driven informed decisions could guide the MOH’s financial spending on patients in Lesotho who are referred for treatment abroad, such as introducing chemotherapy services in all the districts.
• The construction of a Cancer Centre to provide radiotherapy should be prioritised and fast-tracked.
• The MOH should come up with a retention strategy for cancer experts trained by the country.
• The MOH can also consider strengthening data collection and monitoring systems to enhance patient tracking and outcome assessment, which would lead to better cancer care delivery in Lesotho.

Acknowledgements

The authors would like to express their gratitude to Dr P. Ntsekhe, T. Mpo, M. Matsoso, A. Masilo and M. Tlebere for their valuable support. They would like to also to thank the staff from Senkatana satellite clinics and the study participants. Special appreciation goes to the data collectors and supervisors for their hard work. This research is part of a study on ‘Quantifying the burden of cancer care and treatment in Lesotho.’

The author received funding from the Bristol Myers Squibb Foundation’s Global Cancer Disparities (Africa) programme which may be influenced by the research reported in the enclosed publication. The authors have fully disclosed these interests and have implemented an approved plan to manage any potential conflicts arising from their involvement. The terms of these funding arrangements have been reviewed and approved by the affiliated university in accordance with its policy on objectivity in research.

M.M.R. is one of the principal investigators and was involved in preparing and proofreading the manuscript as well as supervising the study. M.C.M is a co-principal investigator and supervised data collection and manuscript preparation. M.A.S. is the co-principal investigator and contributed to preparing and typesetting the manuscript. M.S. was responsible for data analysis and the methodology of the article. K.M. assisted with the formulation of questionnaires, obtaining ethics approval, and supervising the study. L.J.M. contributed to data cleaning and proofreading.

The authors disclosed the following financial support for this research. This work was funded by the Bristol Myers Squibb Foundation’s Global Cancer Disparities (Africa) programme (grant no.: R324-9009).

The data that support the findings of this study are available on request from the corresponding author, M.M.R.

The views and opinions expressed in this article are those of the authors and are the product of professional research. The article does not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The authors are responsible for this article’s results, findings and content.

References