The Out-of-Pocket Cost of Breast Cancer Care in Nigeria: A Prospective Analysis

Abstract

BACKGROUND:

Most patients pay out-of-pocket for cancer care in Nigeria, which can result in a catastrophic health care expenditure (CHE). There is a paucity of economic data on the cost of care and the impact this may have on the household. This study provides a prospective analysis of direct and indirect out-of-pocket costs for breast cancer care at a single tertiary care institution in South West Nigeria.

METHODS:

Consecutive patients undergoing curative intent treatment for a new diagnosis of breast cancer between August 2019 and September 2022 were approached for enrollment. A novel questionnaire was delivered to patients during hospital admission and again during six-month follow-up. Patients self-reported annual household income, capacity-to-pay, and all direct and indirect expenditures associated with access care. A CHE was defined using three commonly used definitions, including total healthcare expenditure that exceeds 40% of a household’s capacity-to-pay, or exceeds the proportion of annual income set at thresholds of 10% and 25%.

RESULTS:

Data were collected from 71 eligible patients with a mean age of 49.5 years (SD 11.26). Sixty-six percent (47/71, 66.2%) of patients had ≥ Stage III disease at presentation, and 95.8% received systemic chemotherapy. Only 23.9% received adjuvant radiotherapy. The mean annual capacity-to-pay for the cohort was $2,866.93 (SD $2749.74). The mean cost of care was $5192.77 (SD $4567.71). Out of the 71 patients enrolled in the study, between 56 (78.9%) and 71 (100%) experienced a CHE, depending on the included costs (direct +/− indirect) and threshold used. Sixty-six percent of patients had no form of health insurance.

CONCLUSIONS:

Over 70% of breast cancer patients at a tertiary care facility in Nigeria experience a CHE because of out-of-pocket costs associated with accessing care.

POLICY SUMMARY:

A more effective and accessible health insurance mechanism is required in Nigeria to protect women with breast cancer from the cost of cancer care.

INTRODUCTION

Breast cancer is a significant public health issue in Nigeria. With an age-standardized incidence of 59.7 per 100,000, the disease is now the leading cause of cancer and cancer-related death among women in Nigeria [1–3]. Indeed, the overall incidence of breast cancer in Nigeria is higher than the pooled incidence for West Africa (24.2 per 100,000) or the continent as a whole (24.5 per 100,000) [2]. The aetiology of the excessive breast cancer-specific mortality rate in Nigeria is multifactorial. Delays in seeking treatment, advanced stage at diagnosis and geospatial access to care have all been attributable to poor breast cancer outcomes in Nigeria [4–7]. Considering the burden of the disease, it is critical to understand the cost of care and the distribution of those costs between relevant stakeholders within the healthcare system.

In 2001, the Nigerian government pledged to allocate 15% of the national budget to healthcare expenditure [8]. However, over the past twenty years, Nigeria has allocated, on average, 4.7% of its total budget to spending on healthcare [9]. This funding includes investment into the National Health Insurance Scheme (NHIS), which aims to improve access to healthcare for all Nigerians. However, due to a lack of awareness and the limited coverage of healthcare services, less than 10% of Nigerians are enrolled [10,11]. Most Nigerians pay out-of-pocket for the majority of their healthcare needs. Without an effective insurance mechanism, healthcare expenditures can quickly overwhelm personal and household savings [12]. A catastrophic health expenditure (CHE) occurs when an individual or household experiences financial hardship or impoverishment from accessing healthcare services [13]. It is a commonly used indicator to assess the financial burden of healthcare costs on individuals and households and as a performance metric for a healthcare system.

In the first phase of this study, a retrospective analysis quantified the out-of-pocket cost of breast cancer care at a public tertiary care center in South West Nigeria. In that study, >80% of women experienced a CHE as a result of accessing curative intent therapy for a new breast cancer diagnosis [14]. This study was designed to validate those results in a prospective cohort. We calculated the total direct and indirect out-of-pocket cost of breast cancer diagnosis and management at Obafemi Awolowo University Teaching Hospital, a public tertiary care center in South West, Nigeria. The degree of financial protection from the cost of care was then calculated as the incidence of CHE within the cohort. The patient-facing cost of cancer care and the sequelae of inadequate financial protection have anecdotally been a barrier to accessing cancer care but have hitherto been unquantified in an intentional, prospective manner. This study aims to address this knowledge gap, which continues to impede effective cancer system planning and health system development in Nigeria.

METHODS

Study design

This study enrolled a prospective cohort to analyze the out-of-pocket costs of breast cancer management in Nigeria. A novel, context-specific questionnaire was developed and tested in our previously published, retrospective exploratory analysis [14]. The questionnaire was administered by trained personnel at Obafemi Awolowo University Teaching Hospital (OAUTH). The questionnaire asked participants to estimate monthly household income from all sources and expenditures. The questionnaire was delivered to patients and caregivers during hospital admission and again during a six-month follow-up. Patients were encouraged to reference hospital receipts and accounting records to minimize recall bias. All bills in the hospital were validated by the research assistant to reduce bias.

The questionnaire was administered between August 2019-September 2022 to patients undergoing curative intent treatment for a new breast cancer diagnosis at OAUTH. Consecutive patients were approached for enrollment. Oral and written consent was gathered from all patients and/or caregivers who agreed to participate in the study. Both the consent and the questionnaire were administered in either Yoruba or English.

Economic Assessment

Annual household income and expenditures

An estimate of annual household income as well as annual household expenditures, as a proxy for disposable income, was elicited from each patient and family. Annual income was extrapolated from self-reported monthly household income. Household spending, including spending on food, healthcare before illness, rent, education and transportation, was elicited in the questionnaire. Annual expenses were extrapolated from monthly estimates.

Capacity-to-pay

In many low- and middle-income countries (LMICs), where income may not be a reliable indicator of purchasing power, capacity-to-pay offers an alternative measure of effective income. Capacity-to-pay was calculated for each household as the sum of annual non-food expenditures. We also calculate capacity-to-pay as the sum of annual non-food and non-rent expenditures, which is considered a household’s annual non-subsistence expenditures [15,16]. Using a recent General Household Survey for the hospital’s catchment area, we compared our study’s population to the average capacity-to-pay for the geopolitical zone [17].

Out-of-pocket costs

Any payment for services associated with accessing care, which were not covered or reimbursed by an insurance provider were considered an out-of-pocket expense. For each patient, the total out-of-pocket costs (i.e. direct and indirect) for all three phases of care (i.e. pre-op, peri-op and post-op) were calculated from the questionnaire data provided. Direct out-of-pocket expenditures included pre-operative evaluation (i.e., laboratory investigations, consultations, biopsy, and diagnostic imaging), inpatient care (i.e., surgery, medications, etc.), post-operative care (i.e., food, bandages, additional imaging, etc.), and adjuvant therapy (i.e. chemotherapy and radiation). Indirect out-of-pocket expenditures included estimates of loss productivity / income as well as related non-medical costs such as travel and lodging. Indirect forms of financial toxicity were also elicited and included using debt financing or substantial forgone expenditures, such as childhood education.

Catastrophic Health Expenditure

Three commonly used definitions of a CHE were then applied to each household to determine the overall incidence of a CHE event across the cohort [18,19]. A CHE was defined as a total healthcare expenditure that exceeded 40% of a household’s capacity to pay [18]. Expenditures that exceeded a proportion of annual household income was also considered a CHE. For this analysis, 10% and 25% of annual household income where used as two separate thresholds for defining a CHE as per previously published work by [19, 20]. All monetary figures were collected in the local currency (Naira) and converted to USD using the Nigerian Central Bank conversion rate of 415.83N to 1 USD (exchange rate in 2022).

Financial Toxicity

For each patient the impact of the healthcare expenditure on variables associated with household performance, including indebtedness and negative sequalae on household dependents such as childhood education was elicited. To quantify the impact of the unexpected healthcare expenditure on future household utility, a Lifetime Money Metric Utility Assessment (LMMU) was performed. This assessment quantifies the lifetime reduction in a household’s economic well-being due to out-of-pocket medical expenses, capturing the long-term financial burden on consumption. It highlights how medical costs can erode financial stability, with a disproportionate impact on lower-income households. The LMMU was calculated at 1, 3, and 5 years, using a discount rate of 7.8%, which is the 10-year average return of Nigerian Treasury Bills [21] to reflect the time value of money, adjusting future consumption losses to present-day terms and accounting for the compounding effect of medical expenses over time. [22].

Ethics Approval

The collection and maintenance of the prospective database was approved by the Independent Research Board (International REB:0004553) at OAUTH. A separate research protocol for this study, including the administration of the questionnaire, was granted ethical clearance by OAUTH (ERC/2018/10/03). Completed questionnaires were stored in a locked research office in a secure filing cabinet with limited access to study personnel. Only anonymized data was entered into a password protected excel spreadsheet that was utilized to facilitate the statistical analysis.

Statistical Analysis

Descriptive statistics were reported as counts and percentages for categorical variables and means ± standard deviation (SD) for normally distributed continuous variables for all sociodemographic and clinicopathological variables. The mean out-of-pocket cost of care for the cohort was calculated from the sum of all direct and indirect out-of-pocket costs divided by sample size. A one-sample T-test was used to compare the mean capacity-to-pay of the study cohort with the mean capacity-to-pay for the geopolitical zone and a Chi-square test to compare the rate of CHE between those with and those without health insurance. Univariate and multivariate logistic regression models were employed to assess the likelihood of CHE based on various patient characteristics and treatment-related variables. All statistical analyses were performed using IBM SPSS Statistical Software (Version 28.0.1.1) and RStudio (Version 2024.04.2). Unless otherwise specified, a two-sided p-value of <0.05 was the threshold for statistical significance.

RESULTS

Demographic information

In total, 71 patients were enrolled in the study, with a mean age of 49.6 years (SD 11.3). The median household size was 5 (SD 5.1), and the majority (76.1%) had completed at least secondary education (Table 1). Most patients had advanced disease at presentation (63.4% Stage III). Ninety-five percent (95%, 68/71) received systemic chemotherapy, while 24% (17/71) received adjuvant radiotherapy. Sixty-six percent (66%, 47/71) of patients had no form of health insurance.

Table 1.

Sociodemographic and clinical characteristics of the study cohort (n=71)

Variables	Mean	SD
Age	49.59	11.26
Size of Household	5.20	5.08
	N	%
Education
≤ Primary	17	23.9
Secondary	24	33.8
> Secondary	30	42.3
Stage of Disease at presentation
I	4	5.6
II	16	22.5
III	45	63.4
IV	2	2.8
Unknown	4	5.6
Immunohistochemistry performed
No	30	42.3
Yes	38	53.5
Unknown	3	4.2
Received chemotherapy (neo and/or adjuvant)
No	3	4.2
Yes	68	95.8
Received radiotherapy
No	54	76.1
Yes	17	23.9

Household income and capacity-to-pay:

The cohort’s mean annual household income was $3152.22 (SD $3638.95) (Table 2). The mean annual capacity-to-pay was $2866.93 (SD $2749.74), net the cost of food and housing $2548.21 (SD $2,408.21) (Table 2). In comparison to the average capacity-to-pay for the South West geopolitical zone, the study cohort was significantly more affluent ($2866.93 vs $652.51 South West, p <0.001) (Table 3).

Table 2.

Mean purchasing power.

Purchasing Power	Mean (SD)
Annual household income	$3,152.22* ($3,638.95)
Annual capacity-to-pay 1 †	$2,866.93 ($2,749.74)
Annual capacity-to-pay 2 ††	$2,548.21($2,408.93)

^*Local currency (Naira) was converted to US dollars ($) using the Nigerian Central Bank’s June 2022 conversion of USD=N 415.83

^†Annual Capacity-to-pay (1) was defined as annual household income net the annual cost of food

^††Annual Capacity-to-pay (2) was defined as annual household income net the annual cost of food and rent

Table 3.

Mean purchasing power of the study cohort compared to South West region

	Study Cohort (Mean)	South West Cohort (Mean)	p-value
Annual capacity-to-pay 1 †	2866.92529	1230.90	<0.001
Annual capacity-to-pay 2 ††	2548.20988	776.11	<0.001

^†Annual Capacity-to-pay (1) was defined as annual household income net the cost of annual subsistence needs, such as food

^††Annual Capacity-to-pay (2) was defined as annual household income net the cost of annual subsistence needs, such as food and rent

Out-of-pocket and catastrophic health expenditure

The mean cost of care, including direct and indirect expenditure, was $5192.77 (SD $4567.71). Direct health expenditures, including consultation and diagnostics, pre-, intra and post-operative care, and neoadjuvant and adjuvant therapies (chemotherapy and radiation) accounted for 59.8% of the total cost. For patients able to afford radiotherapy, the mean cost of adjuvant treatment was $2,074.16 (SD $392.55). Indirect health expenditures including travel, lodging, and lost income, accounting for 40.2% of the total cost (Table 4). Patient-reported lost income due to time spent accessing and recovering from treatment accounted for most indirect expenses.

Table 4.

Direct and indirect out-of-pocket costs associated with breast cancer diagnosis and management

Component of care		N	Mean*	SD
	Direct Expenditures
	Consultation, laboratory tests, biopsy, and diagnostic imaging	71	280.71	223.77
	Chemotherapy	66	1743.97	3133.34
	Radiation	17	2074.16	392.55
	Medications pre-operative care	71	227.42	246.85
	Surgery + immunohistochemistry	68	256.16	246.69
	Post-operative care	71	236.50	247.28
	Indirect expenditures
	Travel	70	105.67	117.61
	Lodging	71	73.95	177.52
	Lost income	70	1934.14	3001.24

^*Local currency (Naira) was converted to US dollars ($) using the Nigerian Central Bank’s June 2022 conversion of USD=N 415.83

The incidence of CHE was calculated using three commonly defined thresholds (i.e., 10% and 25% of total household income, 40% of capacity-to-pay) and the results are outlined in Table 5. One hundred percent of patients experienced a CHE when defined as healthcare related expenditures that exceed 10% of annual self-reported income. At a threshold of 25% of annual income, 98.6% experienced a CHE. When lost-income is excluded from the above analysis, 98.6% and 93% of patients experienced a CHE, respectively.

Table 5.

Threshold for a catastrophic healthcare expenditure (%)

	10% annual income	25% annual income	40% capacity-to-pay (food only)	40% capacity-to-pay (food and rent)
Total cost of care	100	98.6	93	94.4
Total cost without lost income	98.6	93	78.9	81.7
Surgery alone	43.7	22.5	12.7	14.1

A CHE was experienced by 93.0% of patients at a 40% capacity-to-pay. When cost of care is calculated without lost income, 78.9% of patients experience a CHE using the 40% capacity-to-pay threshold. The mean direct cost, associated with histopathology, including immunohistochemistry, and surgery was $256.16 (SD $246.69). This cost alone resulted in a CHE for 43.7%, 22.5%, and 12.7% of the households at the 3 pre-determined thresholds (10%, 25% annual income; 40% capacity-to-pay). There was no statistically significant difference in the rate of CHE between those with and without NHIS (p = 0.731). On univariate and multivariate logistic regression, the only cost variable associated with a CHE was receipt of trastuzumab systemic therapy (p = 0.008). Length of stay (p = 0.645), stage of disease at diagnosis (p = 0.209) and age at diagnosis (p = 0.778) were not associated with CHE.

Impact of out-of-pocket expenditures

The financial toxicity associated with the cost of breast cancer care can be found in Table 6. As a result of accessing treatment, 54.9% (39/71) of households had to borrow money, and 19.7% (14/71) had to sell land and possessions. Fifty-eight percent (41/71) of patients incurred debt, seven percent (5/71) withdrew their children from school, and 11.3% (8/71) declined recommended treatment. A larger proportion of lowest-income quartile patients (35.3%) were in the highest LMMU quartile, indicating that medical expenses had a more substantial negative impact on the poorest households’ utility from the index year through 5 years post-treatment. This is presented as a matrix in Table 7.

Table 6.

Impact of out-of-pocket costs for breast cancer diagnosis and management on patients and families

Impact	Proportion Affected (%)
Borrowed money	54.9
Declined recommended treatment	11.3
Sold land and/or possessions	19.7
Lost job because of treatment	5.6
Withdrew children from school	7
Incur any debt	57.7

Table 7.

Relationship between income-quartile and Lifetime Money Metric Utility Assessment

	Income Quartile
	1	2	3	4
LMMU Quartile
	1	38.9%	16.7%	16.7%	27.8%
	2	5.6%	27.8%	38.9%	27.8%
	3	23.5%	35.3%	23.5%	17.6%
	4	35.3%	23.5%	17.6%	23.5%

DISCUSSION

Among a cohort of consecutive women at a public tertiary care hospital in South West Nigeria, the mean out-of-pocket cost for the curative intent treatment of a new breast cancer diagnosis was $5192.77 (SD $4567.71), despite a mean capacity-to-pay of just $2866.93 (SD $2749.74). The financial burden of care resulted in ≥ 98% of the study population experiencing a CHE. Over 90% of women in the study spent more than 40% of their self-declared annual non-subsistence family income on their care. Enrolment in the national insurance program did not provide protection from a CHE. Our findings corroborate previously published, retrospective data from Nigeria, which found that 86–95% of households experience a CHE as a result of their breast cancer diagnosis and management.

The findings presented in this study are the first comprehensive report of out-of-pocket expenses and associated economic sequelae for breast cancer care in a contemporary, prospective cohort of Nigerian women. The findings are congruent with a recent systematic review that found that across low- and middle-income countries (LMIC), cancer patients and caregivers spend 42% of their annual income on out-of-pocket expenses to cover cancer costs [23]. In Ghana, the out-of-pocket cost for breast cancer management has been estimated at $3426.11 [24]. In Kenya, the average out-of-pocket cost for breast cancer care was $1349.40, while in Pakistan, it amounted to $1846.44 [25,26]. The observed out-of-pocket costs reported in these studies were significantly lower than those in our study. Unfortunately, it is difficult to compare the out-of-pocket cost of breast cancer treatment among other LMICs due to limited data from these countries, especially those in sub-Saharan Africa [27]. Moreover, the variations in study methodologies, which often exclude indirect expenses such as travel and lost income, pose challenges in facilitating meaningful comparisons.

Our findings are similar to data from LMICs in Asia, which found that approximately 60% of breast cancer patients experienced an expenditure that exceeded 30% of annual household income (Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Thailand, Vietnam) [28]. In India, 84% of households may experience out-of-pocket expenses that exceed 40% capacity-to-pay [29]. In a systematic review and meta-analysis, the pooled rate of financial toxicity across 10 LMICs for patients with breast cancer was 78.8% [30]. Further qualitative studies in Kenya and Northern Nigeria have found that patients experience significant distress due to the financial burden of cancer care [31,32].

Financial toxicity captures the adverse financial burden and distress experienced by individuals or families due to the costs associated with medical care. In our study, the sequelae of inadequate financial protection from the cost of breast cancer care was significant. Over 50% incurred debt, and children were withdrawn from school to afford care. Additionally, 1:10 patients declined a recommended treatment due to cost. Several studies from SSA have demonstrated a relationship between financial toxicity and survival, which may be related to both late presentation and poor outcomes due to incomplete treatment [30,33,34].

The majority of the study population lacked any form of health insurance. Interestingly, even amongst those with NHIS coverage, there was still a high rate of CHE. Despite breast cancer being the leading cause of cancer-related mortality in Nigeria, the NHIS is inadequate in terms of breadth and depth of coverage. The NHIS covers some chemotherapy agents and surgery, but radiation therapy and immunotherapy are not. Compared to Ghana and Kenya, with similar GDPs, Nigerian patients have higher out-of-pocket expenditures. Nigeria’s government has previously committed to spending 15% of its annual budget on healthcare; however, it currently only spends 4.7%. The recent Lancet Nigeria Commission found that even a modest increase could significantly impact affordability and access [35]. The coverage provided by the NHIS should include the essential diagnostic and treatment components for managing breast cancer as outlined by the NCCN resource-stratified guidelines, including access to the WHO essential medications list. Most standard chemotherapy regimens for the treatment of breast cancer are included in the WHO essential medications list, as are selective estrogen receptor modulators such as Tamoxifen. Increasing the breadth of coverage to include the most prevalent cancers and with sufficient depth to allow free at the point of use access to the basic components of care would increase uptake and build the pool of contributors – essential components of a healthy, sustainable insurance mechanism. The Nigerian government has a new funding initiative for low income patients called Cancer Health Fund. Successful applicants can access up to 2 million Naira for systemic and radiotherapy if treated at six pilot facilities. Given this study’s high rate of CHE, the eligibility criteria for the Cancer Health Fund should be expanded. Indeed, universal coverage of essential cancer care should be considered within the scope of the NHIS. It is important to note that an effective health insurance mechanism for cancer care may not address the high burden of indirect cost captured in this study. However, a significant reduction in CHE would be actualized with a more robust insurance mechanism for direct costs alone.

The cost of travel to access care is an important component of overall cost in Nigeria. This is particularly important for resources like radiotherapy, located in only a few major urban centers. This may exaggerate the inequity of outcomes and financial toxicity for breast cancer patients between regions in Nigeria [35]. Future research is needed to create a comprehensive picture to compare the disparities in CHE between urban and rural patients and between geopolitical zones.

Our study is not without limitations. First, the study’s population was limited to a single tertiary institution in the South West geopolitical zone, and the results may not be generalizable across Nigeria. The relationship between cancer-treatment seeking behavior and gender-based cultural norms and expectations are beyond the scope of this analysis. Relevant cultural and/or religious differences in the South East or North of Nigeria may have an impact on CHE or financial toxicity. The sample size was relatively small (n=71), and although we sought to capture consecutive patients, our sample was notably wealthier than average for the region. Our study may have underestimated the financial toxicity due to out-of-pocket costs for breast cancer management and treatment for the average individual from South West Nigeria. The catchment area draws from a predominately semi-urban population around a tertiary care facilitate and large public university. This may explain the relative affluence of our cohort compared to the broader geopolitical zone. It is expected to be more reflective of the cost of living and treatment than a population from a hyper-urban environment such as Lagos or Abuja. Third, the income and financial toxicity sequelae (e.g., household debt) were self-reported and unverified. These estimates may be affected by social desirability bias as captured by face-to-face interviews with research personnel. Finally, due to the nature of the questionnaire, recall bias is possible. Self-reported lost income may be particularly biased due to the high incidence of non-formal sector employment in the cohort. We attempted to minimize this by administering the survey at diagnosis and post-six-month diagnosis and corroborating cost estimates with receipts and known hospital charges where possible.

CONCLUSION

There are significant out-of-pocket costs associated with accessing breast cancer diagnosis and treatment in Nigeria. These high out-of-pocket costs resulted in over 90% of breast cancer patients at a tertiary care facility in Nigeria experiencing a CHE. This appears to limit access to evidence-based adjuncts (i.e. radiotherapy) and negatively impacts the well-being of the broader household. There is a need for more granular data on healthcare expenditure for the most prevalent cancers in Nigeria. These data will allow policymakers to make informed decisions about expanding Nigeria’s nascent health insurance system. There is considerable room for future growth in this aspect of the healthcare system, and it is anticipated that breast cancer outcomes will improve with more effective protection from financial catastrophe.

Highlights.

• Breast cancer is the leading cause of cancer related mortality in Nigeria.

• As a result of paying out-of-pocket for diagnosis and treatment, >70% of women in Nigeria will experience a catastrophic healthcare expenditure during their breast cancer journey.

• Enrollment in the Nigerian National Health Insurance Scheme does not provide protection from catastrophic healthcare expenditure for breast cancer treatment.

• The burden of out-of-pocket payments for essential cancer care has an impact on the wider household, including withdrawing children from school to afford treatment and future household wellbeing.