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Systematic Review

The Out-of-Pocket Cost Burden of Cancer Care—A Systematic Literature Review

Institute of Health Policy, Management & Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada
The Canadian Partnership Against Cancer, Toronto, ON M5H 1J8, Canada
Centre for Health Economics and Hull York Medical School, University of York, Heslington, York YO10 5DD, UK
Centre for Addiction and Mental Health, Institute for Mental Health Policy Research and Campbell Family Mental Health Research Institute, Toronto, ON M6J 1H4, Canada
Author to whom correspondence should be addressed.
Received: 15 October 2020 / Revised: 5 March 2021 / Accepted: 11 March 2021 / Published: 15 March 2021


Background: Out-of-pocket costs pose a substantial economic burden to cancer patients and their families. The purpose of this study was to evaluate the literature on out-of-pocket costs of cancer care. Methods: A systematic literature review was conducted to identify studies that estimated the out-of-pocket cost burden faced by cancer patients and their caregivers. The average monthly out-of-pocket costs per patient were reported/estimated and converted to 2018 USD. Costs were reported as medical and non-medical costs and were reported across countries or country income levels by cancer site, where possible, and category. The out-of-pocket burden was estimated as the average proportion of income spent as non-reimbursable costs. Results: Among all cancers, adult patients and caregivers in the U.S. spent between USD 180 and USD 2600 per month, compared to USD 15–400 in Canada, USD 4–609 in Western Europe, and USD 58–438 in Australia. Patients with breast or colorectal cancer spent around USD 200 per month, while pediatric cancer patients spent USD 800. Patients spent USD 288 per month on cancer medications in the U.S. and USD 40 in other high-income countries (HICs). The average costs for medical consultations and in-hospital care were estimated between USD 40–71 in HICs. Cancer patients and caregivers spent 42% and 16% of their annual income on out-of-pocket expenses in low- and middle-income countries and HICs, respectively. Conclusions: We found evidence that cancer is associated with high out-of-pocket costs. Healthcare systems have an opportunity to improve the coverage of medical and non-medical costs for cancer patients to help alleviate this burden and ensure equitable access to care.
Keywords: out-of-pocket costs; economic burden; cancer; financial hardship; catastrophic expenditure out-of-pocket costs; economic burden; cancer; financial hardship; catastrophic expenditure

1. Introduction

Cancer is a major international health issue due to its considerable impact on mortality and morbidity. Over 22 million people are expected to be diagnosed with cancer in 2030, worldwide [1]. Similar to other chronic conditions, cancer patients require long-term medical attention, posing a considerable economic burden to healthcare systems, patients and their families [2]. Furthermore, rising costs of cancer care have been associated with higher out-of-pocket expenses, medical debt, and even bankruptcy [3]. As such, there is an imperative to understand and measure the economic burden to help mitigate the impact of cancer [4].
Conceptually, the economic burden of cancer can be divided into three categories: psychosocial costs, indirect costs (mostly productivity losses), and direct costs [5]. In turn, direct costs can be divided into medical and non-medical costs paid either by third-party payers (e.g., healthcare systems or private insurers), or by patients out-of-pocket. Studies have extensively evaluated the direct medical costs associated with cancer that are paid by healthcare systems [6,7]. However, there are less data on the medical and non-medical out-of-pocket expenses borne by cancer patients and their caregivers across international settings. Studies that have measured the out-of-pocket burden of cancer have usually focused on estimating a given cost category (e.g., medication copayments) among specific cancer patients (e.g., breast cancer survivors) from a single country perspective [8]. However, cancer is a heterogeneous condition, and the out-of-pocket burden is expected to depend on multiple factors, such as cancer site, patient age and sex, or insurance coverage arrangements in place in each context. Previous research has shown that out-of-pocket costs are expected to pose a heavier burden among cancer populations with lower income [9]. Moreover, out-of-pocket costs contribute to the economic burden of cancer patients, regardless of the country they live in. Although healthcare insurance coverage differs across jurisdictions, the literature suggests that medical debt is not just a problem in low- and middle-income countries (LMICs); it also extends to insured individuals in high-income countries (HICs) [10]. This is specifically due to new and costly therapies that create a greater demand on strained resources [11]. A synthesis of the evidence presents the opportunity to characterize and compare the out-of-pocket burden across settings, to help identify at-risk populations and understand which specific types of out-of-pocket expenses contribute more/less to the burden. Therefore, the objective of this study was to provide a comprehensive overview of the international literature on out-of-pocket costs associated with cancer and to provide a source that compiles these data and discusses the associated strengths and weaknesses of measuring these costs across diverse patient populations.

2. Methods

2.1. Data Sources and Search Strategies

A systematic review of electronic databases was conducted to identify studies, which estimated costs paid out-of-pocket by patients with cancer and their caregivers. In particular, we searched MEDLINE, EMBASE (Excerpta Medical Database), EconLit, and CINAHL, between database inception and 7 May 2019. Search terms combined medical subject headings (MeSH), Embase subject headings (Emtree), and keywords for out-of-pocket costs (e.g., deductibles, copayments), and cancer. No electronic search filters for date or language were used. The reference lists of all included papers were reviewed to identify potentially relevant papers. Google Scholar was searched using keywords from the main search strategy. The search strategies can be found in Supplementary 1. The review was registered in Prospero (ID: CRD42019133508). We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [12]; the checklist can be found in Supplementary 4.

2.2. Eligibility Criteria

We included any study that estimated out-of-pocket costs for patients with any type of cancer, paid either by patients or their caregiver(s). No restriction was applied to the study design or the type of cost (e.g., medication, transport, etc). Costs were identified across the entire cancer care continuum from diagnosis to end-of-life care. Studies were excluded if any of the following criterion was met: (a) the population of interest was not cancer patients or their caregivers; (b) out-of-pocket costs were not explicitly estimated as a primary or secondary outcome; (c) the studies included duplicate data sources; and (d) a full-text article was unavailable. The search results were screened first by title and abstract, then by full text by two independent reviewers (NI and BE). Any article that either reviewer included at the title and abstract review stage was included for full-text review. The kappa statistic was estimated to evaluate inter-observer agreement [13]. Disagreements between reviewers were settled by discussion with a third reviewer (CdO) until a consensus was reached.

2.3. Data Extraction

A data extraction template was designed from a sample of studies that measured different dimensions of the economic burden of cancer. We extracted the following study characteristics: authors, publication year, setting, country, data sources, study population, sample size, cancer site, cancer care continuum stage, mean age of patients, percentage of female population, percentage insured, and mean income of patients. The outcomes of interest were non-reimbursed medical and non-medical out-of-pocket costs, however defined. This included non-reimbursed co-payments and deductibles. The tool (e.g., surveys, cost diaries), time frame, currency, and currency year were extracted to estimate mean monthly out-of-pocket costs. Authors were contacted if further information was required.

2.4. Data Synthesis

The out-of-pocket costs reported by individual studies were reported and synthesized. Studies that estimated mean out-of-pocket costs per month per patient and reported the standard deviation were extracted and did not require further synthesis. Standard deviations were estimated from confidence intervals assuming critical values of t distributions [14]. Median estimates were transformed to mean costs using mathematical inequalities and statistical approximations, as described by Hozo et al. [15]. To do so, studies had to report a median cost, the interquartile range (or range), and the sample size. To ensure comparability, all mean costs were transformed to reflect monthly expenditure (e.g., annual mean out-of-pocket costs were divided by 12 to obtain a mean per-month estimate). Furthermore, exchange rates were used to convert all non-USD costs to USD costs, which were then adjusted for inflation to establish a single metric to allow controlling for any changes in nominal prices. Exchange rates and pharma consumer price indices from the World Bank’s Global Economic Monitor were used to convert costs to 2018 USD [16]. Once all costs were converted to a single measure (mean out-of-pocket cost per month per patient), estimates were stratified and presented separately by country, country income-level (as defined by the World Bank [17]), or type of healthcare system (e.g., HICs with and without universal health coverage), depending on data availability; where possible, estimates were stratified and presented by cancer site within country. Costs were reported or estimated only from studies that provided sufficient information (i.e., currency, currency year, mean cost, standard deviation/measure of spread, time frame). Studies that failed to provide a measure of spread (e.g., standard deviation), or a time frame, could not be used to compute a weighted average. Furthermore, we estimated a weighted average cost across expenditure categories (medications, medical consultations, in-hospital care, transport/travel, and caregiver costs) and across cancer sites. Finally, the proportion of household income spent on out-of-pocket expenses for cancer-related care was reported and calculated for the studies that reported a measure of income (distribution or mean value) among the studied population

2.5. Quality Assessment

Quality assessment was conducted in duplicate (NI and BE) using the Ottawa-Newcastle Assessment Tool for Cohort Studies [18]. Cross-sectional studies were evaluated with a variation of the Ottawa-Newcastle tool [18]. Three domains were evaluated for prospective cohort and cross-sectional studies: selection (i.e., representativeness of the sample), comparability (i.e., comparability of subjects, confounding factors), and outcome (i.e., assessment of outcome, statistical test used). Each domain was assessed for risk of bias (low, unclear, or high) by two reviewers (NI and BE).

3. Results

The systematic review identified 3639 records, of which 105 full-text studies were retrieved [8,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122]. The eligibility criteria and reasons for exclusion are presented in Figure 1. Duplicate records (n = 676) were excluded before the abstract review stage. Half of the reviewed abstracts reported costs that were not relevant (e.g., indirect costs) and 20% did not measure out-of-pocket costs. In total, 377 studies were selected for full-text review, of which 42% were not full-text articles (i.e., conference abstracts). No additional records were identified after searching the reference lists of the included articles. A high inter-observer agreement was measured for the title and abstract review and the full-text review (kappa = 0.71).
The study characteristics are summarized in Table 1. The year of publication ranged from 1979 to 2019. The total combined sample size of the identified studies was 774,135 cancer patients and/or caregivers and ranged from 11 to 200,000. The studies with the largest sample size usually identified patients through administrative data sources, such as linked cancer registries, medical claims data, and medical expenditure surveys. Costs were collected retrospectively in most studies (n = 73) using observational and cross-sectional study designs. On the other hand, prospective studies followed cohorts of cancer patients through time (n = 32). The mean age of pediatric cancer patients ranged from 5.6 to 9 years old, and from 37 to 80 years old among adults. Half of the studies were conducted in the U.S. (n = 55, 52%), followed by Australia (n = 12, 11%), Western Europe (France, Germany, Ireland, UK, and Italy) (n = 11, 10%), Canada (n = 9, 8%), and India (n = 6, 5%). A few were conducted in South East Asia (Laos, Vietnam, Malaysia, Philippines, Thailand, Cambodia and Myanmar) (n = 4, 4%), China (n = 3, 3%), Japan (n = 3, 3%) and in Latin America (Mexico) (n = 1, 1%). Half of the studies (n = 54) included patients with full or partial healthcare insurance (public healthcare systems with universal coverage, private, or a combination) and excluded uninsured patients. All patients from studies conducted in countries with universal healthcare coverage were publicly insured.
Most studies included patients receiving active treatment (any stage) (n = 50, 47%), followed by those on patients who were recently diagnosed (n = 25, 24%). A few studies focused on end-of-life and/or palliative care (n = 9, 8%), and survivorship (n = 9, 8%). Out-of-pocket costs were measured using different tools; some studies, usually those following cohorts of cancer patients, employed cost diaries and logbooks that patients used to register the out-of-pocket and non-reimbursed expenses related to their cancer care [20,23,59,68,75,78]. On the other hand, most observational studies were conducted using health administrative data, expenditure surveys, and medical expenditure claims from insurance companies and healthcare records.
Table 2 and Supplementary 2 summarize the individual out-of-pocket estimates across the 105 identified studies. Sixty-four estimates were reported and converted to mean out-of-pocket monthly costs per patient (2018 USD) for comparison through stratified analyses. Figure 2 summarizes the range of out-of-pocket costs estimated across countries for all cancer populations. Estimates for all cancers were lumped by country as there were not enough studies to present the findings by cancer site. The out-of-pocket cost for all adult cancer patients in the U.S ranged from USD 180 to USD 2598 per patient per month (around USD 300 per patient per month on average). Estimates for Western Europe (Germany, France, Ireland, Italy, and the UK) ranged between USD 4 and USD 609 per patient per month (average of USD 200 per patent per month). In Canada, costs ranged between USD 15 to USD 400 per patient per month (average of USD 187 per patient per month). Finally, the average out-of-pocket cost in Australia ranged between USD 58 and USD 438 per patient per month (average of USD 70). There was not enough information to estimate a range of costs (measured in 2018 USD) among studies conducted in other HICs (e.g., Japan), or in LMICs (Mexico, India, China, Vietnam, Thailand, etc.). Figure 3 summarizes the mean out-of-pocket cost for different expenditure categories among HICs (U.S., Germany, France, Italy, UK, Ireland, Canada and Australia). Furthermore, given the small number of studies by country, estimates were stratified by type of health-care system; that is, costs were reported separately for the U.S. and countries with universal healthcare coverage (Australia, Canada, and Western Europe) (unfortunately, estimates could not be presented by cancer site within country). In terms of non-reimbursable medical costs, the category that represented the highest out-of-pocket burden for the U.S. was medications, with an average monthly out-of-pocket cost per person of USD 288 (n = 15), compared with USD 40 (n = 13) in Canada, Australia, and Western Europe (combined). This was followed by expenditures in medical consultations (USD 72, n = 13), which was almost twice as high relative to countries with universal healthcare coverage (USD 39, n = 8). Finally, spending related to in-hospital care was similar between the two groups (~USD 60 and USD 70). Results were also estimated for non-medical expenditure categories. The out-of-pocket costs spent on travel/transportation and supportive care provided by caregivers were higher in countries with universal healthcare coverage compared with the U.S. (USD 205 vs. USD 66 and USD 189 vs. USD 152, respectively). Individual cost estimates per category were summarized and are presented in Supplementary 3.
Although most studies estimated costs across different categories, some focused on specific types of out-of-pocket costs. Several studies estimated medication costs only and exclusively followed patients throughout the cancer treatment pathway. These studies estimated the deductibles or co-payments associated with specific cancer medications (e.g., imatinib, bevacizumab) [86,100]. On the other hand, other studies focused on travel costs for outpatient treatment, which included non-medical fees associated with parking, lodging, accommodation, and public transportation [33,42,67,77,106]. Finally, a few studies identified other types of out-of-pocket costs such as medical devices, food, hair accessories, laboratory tests, and clothing [19,89,93,115]. However, insufficient data was provided to estimate a weighted mean for these categories.
The distribution of the identified patient populations across cancer sites was as follows: most studies (n = 33, 31%) evaluated all adult, followed by breast (n = 18, 17%), leukemia (n = 11, 10%), all pediatric (n = 8, 7%), colorectal (n = 6, 5%), lung (n = 5, 5%), head and neck (n = 4, 4%), prostate (n = 4, 4%), ovarian (n = 3, 3%), pancreatic (n = 2, 2%), anal (n = 1, 1%), and brain cancers (n = 1, 1%). Figure 4 and Figure 5 summarize the estimated costs across cancer sites.). Mean weighted costs were estimated and combined for all HICs (U.S., Canada, Australia, Italy, France, Germany, UK, Japan) (Figure 4) and estimated for the U.S. (Figure 5) across cancer sites due to lack of data; moreover, there was not enough data from LMICs. Breast and prostate cancer patients faced similar out-of-pocket costs at around USD 200 per patient per month. On the other hand, the mean costs were slightly higher for hematological and colorectal cancers, estimated at around USD 400 per month per patient. The highest average out-of-pocket cost was estimated among pediatric populations and their caregivers, at an estimated USD 800 per month. This represents a four-fold difference compared with breast and prostate cancers, and a two-fold difference compared with colorectal and hematological cancers.
We reported and estimated the total out-of-pocket costs as a proportion of the annual income in 33 studies (Table 2). Figure 6 summarizes these estimates per study and country income-level and presents a weighted average for HICs (U.S., Canada, Australia) and LMICs (China, Malaysia, India, Haiti, Brunei, Thailand, Indonesia, Philippines, Vietnam, Laos, Cambodia, Myanmar). Cancer patients and caregivers in HICs spent, on average, 16% of their annual income on out-of-pocket expenses related to cancer care, compared with 42% among LMICs. Most studies conducted in LMICs reported a mean estimate above 30%, and although most studies conducted in HICs were distributed in the lower end, 40% reported an annual expenditure of over 20% of the annual income. A study conducted in Canada among breast cancer patients estimated the lowest proportion of income spent as out-of-pocket costs at 2.3% [90]. At the other extreme, a study of pediatric cancer patients in India estimated that caregivers incurred considerable debt and spent over 175% of their annual income as medical and non-medical out-of-pocket costs [59]. However, this study had a small sample size and contributed relatively little to the estimated 42% weighted average income spent as out-of-pocket expenses in LMICs. Additionally, four studies defined explicit thresholds for catastrophic health expenditure [27,68,69,101]. They defined a threshold of annual income spent as out-of-pocket expenditures and estimated the proportion of patients exceeding it. In two studies, CHE was defined as 30% of the annual household income spent as non-reimbursed out-of-pocket costs in two studies conducted in different LMICs of South East Asia among an all cancer population [68,69]. This threshold was also defined at 40% in Haiti among breast cancer patients [101] and 10% in India among patients with pancreatic cancer [27]. The proportion of patients incurring CHE, however defined, ranged between 31% and 67%.
Equity considerations and distributional effects were explicitly evaluated by a third of the included studies (n = 32). Three studies evaluated the out-of-pocket costs among different age groups; young adults and patients over 60 years of age faced comparatively higher out-of-pocket expenses [64,102,119]. On the other hand, two Australian studies and a study conducted in the U.S. estimated higher out-of-pocket costs among ethnic minorities and lower access to cancer care among indigenous populations [28,36,79]. Furthermore, four studies estimated additional out-of-pocket costs among patients living in rural and remote areas mostly due to increased expenses related to travel and transportation [44,51,65,109]. In settings with private insurance schemes, like in the U.S., patients with limited insurance packages paid higher deductibles and co-payments, especially for treatment and medications [27,41,48,60,73,97,98,104]. Finally, lower-income patients and households had a greater burden imposed by out-of-pocket expenses, as measured by the proportion of the household income spent in the form of out-of-pocket costs [31,34,47,68,69,74,86,87,90,92,108,116].

Quality Assessment

Risk of bias was assessed and summarized separately for cohort and cross-sectional studies (Figure 7). Forty-four percent of prospective cohort studies had a low risk of bias. Studies with unclear and high risk of bias mainly depended on self-reported out-of-pocket costs that patients recorded in their cost diaries but lacked verification (e.g., bills or receipts). Furthermore, cohort studies with unclear and high risk-of-bias usually failed to include a non-exposed cohort or failed to account for important confounders such as the type of insurance and income level across patients and households. On the other hand, 25% of cross-sectional studies had a low risk of bias. Most studies with unclear or high risk of bias failed to explicitly include a representative or random sample, or to account for important risk factors, effect modifiers or confounders.

4. Discussion

To the authors’ knowledge, this is the first systematic review to summarize and synthesize the existing literature on the out-of-pocket burden faced by patients diagnosed with cancer and their caregivers. This review found cancer patients pay substantial out-of-pocket costs per month, most of which is spent on cancer medications, followed by caregiver expenses, and transport and travel expenses. Expenditures were highest among pediatric patients and their caregivers. Furthermore, the out-of-pocket cost burden was comparatively higher in LMIC countries, and among underserved populations, such as ethnic minorities, populations living in rural and remote areas, and low-income patients and caregivers. This trend was seen across various studies conducted in different countries. An important finding was that patients incurred substantial out-of-pocket expenses (especially non-medical costs) in countries with systems that provide universal healthcare coverage, such as Canada, France, the UK, and Australia.
The burden of paying out-of-pocket for medical care is a consequence of the varying degrees of comprehensiveness of public financing of cancer care in each setting. As an example, studies from countries that lack national insurance programs to cover essential medicines for the whole population (e.g., U.S.), usually reported high medication costs. This is further complicated by increasing costs of newer cancer-related medications that are usually covered by private insurance with considerable copayments [123]. However, although rising medication costs and their burden to the health care system remain an issue, this review focused primarily on costs incurred by patients/households. Patients also incurred substantial costs related to clinical consultations and in-hospital care (e.g., surgery) in HICs. In the U.S., these costs were likely an underestimate as the largest studies employed administrative datasets that included patients and caregivers with public and some private insurance. On the other hand, countries with universal healthcare coverage registered similar levels of expenditure for these categories, even though most of these procedures are considered medically necessary and are usually publicly funded.
Paying out-of-pocket for essential cancer-related medicines and medical care results in high and potentially, catastrophic, levels of expenditure for cancer patients and their households. This can lead to cancer care becoming unaffordable in settings where there is sub-optimal health insurance coverage as patients and families are responsible for carrying a large portion of the cost burden of care. This poses a financial barrier to accessing cancer care that can impact on whether patients can adhere to their treatment plans. In other cases, patients opt for sub-standard care (e.g., cheaper and less effective IV therapies instead of expensive oral medications) due to the associated high deductibles and copayments [123]. Copayments have an impact on health service utilization rates as patients are often not well-positioned to distinguish between care that is necessary and care that might otherwise be defined as unnecessary. Reductions in unnecessary care are often overshadowed by reductions in overall health service use as well as changes in provider behaviour that are responsive to the patient-related reductions in utilization due to price; both of which can impact on health outcomes [124,125]. This review reinforces the importance of ensuring that essential cancer treatments are included in all healthcare benefit packages that are being developed to support achieving universal healthcare coverage, including in countries that are further along in the development and implementation of national health insurance programs.
This review also identified substantial expenditures for transport/travel (usually reported together in the studies) and caregiving, which are important for enabling access to and use of cancer treatment. However, support for these types of non-medical out-of-pocket costs tends to be inconsistent and varied [65,76,93,109]; as a result, we found non-medical costs were a key component of the overall out-of-pocket cost burden faced by patients across all studies in this review. Furthermore, non-medical costs may be under-reported, considering that most studies were conducted using employer-based administrative datasets that usually fail to capture this dimension. As such, health financing policies should be supplemented with a strengthening of social support programs to better recognize and address the significant burden associated with non-medical out-of-pocket costs. There may be opportunities to indirectly address the burden associated with some of the non-medical out-of-pocket costs as new models of community-based cancer care are developed and implemented. For example, the integration of virtual care and telemedicine into routine care could help ease the burden associated with travel and transport costs and potentially decrease some of the caregiver time and support required [126]. Similarly, interventions that integrate palliative and end-of-life care in the home [127] also have the potential to reduce caregiver and travel-related costs (e.g., lodging, food, fuel, etc.). In making future decisions about new models of cancer control, decision-makers should consider information on the full spectrum of costs and benefits associated with these programs, including their potential to mitigate the burden posed by out-of-pocket costs.
The economic burden associated with cancer due to out-of-pocket spending has been more recently described as financial toxicity because of the impact that it has on the economic circumstances of households [128]. Previous systematic reviews found that financial toxicity was common among cancer survivors, partly due to the high out-of-pocket costs associated with their cancer care. However, these studies highlighted a lack of information regarding at-risk populations and intervention targets that would allow developing interventions capable of mitigating financial toxicity among cancer patients and their caregivers [129,130]. As such, this review confirms some populations are consistently more at risk of facing financial toxicity associated with cancer. Pediatric patients and their caregivers experienced considerably higher out-of-pocket costs mainly due to relatively longer and more resource-intensive treatment and costly survivorship care [131]. In particular, LMICs in general, and lower-income households (in both LMICs and HICs) were more heavily burdened and experienced financial toxicity more frequently. For example, low-income households with pediatric cancer patients in India paid more than twice their monthly earnings to cover the associated out-of-pocket expenses, thus incurring considerable debt [59]. This trend was also observed among patients who were unemployed and those who lacked or did not have private health insurance [27,41,48,60,73,97,98,104]. Some ethnic minorities and Indigenous communities, who often reside in rural and remote areas, experienced higher levels of out-of-pocket costs in Australia—other communities reported no costs due to a reduced, and almost non-existent access to health care [28,36]. These risk factors are not independent; most vulnerable populations often face multiple barriers to healthcare and an increasingly larger out-of-pocket burden. These are pressure points that healthcare and social care systems should seek to address to minimize the burden for patients and their caregivers, in particular those sub-groups who are most at risk of falling through the cracks [132].
This review makes an important contribution to the literature by estimating the magnitude and distribution of non-reimbursed costs that specific cancer populations face in different contexts; nonetheless, there are a few limitations. Our literature search focused on studies retrieved from only four databases; nonetheless, and based on prior reviews, these are the most relevant databases given the topic [129,133]. We reported and extracted an average cost across all included studies; however, the cancer populations examined and cost definitions were heterogeneous. Furthermore, not enough information was available to pool costs across countries and cancer types, or to estimate total out-of-pocket costs per treatment. Therefore, an overall estimate might not appropriately describe the distribution of out-of-pocket costs in all settings. Consequently, we estimated an average cost across spending categories, cancer sites, and different countries, to better understand how these costs were distributed among different populations and country income levels. Although a distinction between costs borne by cancer patients and their caregivers was of interest, it was not possible to explore this due to lack of individual category estimates. However, the ‘caregiver cost’ category provided an estimate of how much was spent on supportive care, daycare for pediatric patients, and other formal and informal care provided by caregivers. Furthermore, this review likely provides an underestimate of the out-of-pocket cost burden for cancer patients and their caregivers; many studies focused on single cost categories (e.g., medications), instead of evaluating multiple types of non-reimbursable expenditures. The review was also limited by the lack of evidence from LMICs. Most studies did not include enough information to allow estimating a weighted average. Additionally, presenting country-specific out-of-pocket costs stratified by cancer site and expenditure categories would have allowed for a direct comparison of more heterogeneous populations. However, in most cases, the sample size was only large enough to do so for the U.S. Finally, only one-third of the studies provided enough information to estimate the out-of-pocket cost burden. Absolute measures (i.e., total out-of-pocket cost) provide information regarding how much patients and caregivers are spending on cancer care but fail to account for the burden of this expenditure on the household’s resources. On the other hand, a relative measure such as the proportion of income spent on out-of-pocket medical costs allows an understanding of how a household might be burdened by these expenses;, e.g., a higher proportion is usually associated with financial debt and a reduction of spending on food, rent, clothes, and education [68,69,98]. Studies should seek to employ a consistent approach to measure the out-of-pocket burden as an absolute and a relative measure to allow for comparisons across heterogeneous jurisdictions and populations. Moreover, although the existing literature mostly focuses on the indirect and out-of-pocket burden of cancer, further studies should evaluate the relationships between out-of-pocket costs and the psychosocial burden of cancer. Studies have found that patients and caregivers who incur catastrophic health expenditures can experience financial strain and distress, which can contribute to the psychosocial burden [134,135]. Consequently, out-of-pocket costs not only pose a burden in terms of costs and potential nonadherence to treatment but might also affect patients’ quality of life. To fully understand this inter-relationship and the extent to which out-of-pocket costs contribute to the overall burden of cancer, the relationship between its components must be described.
This review supplements the growing body of literature on the economic burden of cancer for patients and their caregivers. It builds on this work by providing estimates of the out-of-pocket costs associated with cancer care and explores whether there is consistency in this burden across cancer populations and settings. The results of this study are an important input for advancing the agenda of addressing financial toxicity [128] as it provides estimates of how much patients pay for their cancer care while highlighting pressure points in the overall financing of cancer treatment across settings. Furthermore, this review confirms that patients are still key funders of cancer treatment in many countries, including in systems with universal healthcare coverage, despite varying abilities to afford these costs. The results also suggest the need for comprehensive out-of-pocket costing data for different cancer sites, and patient and caregiver populations across the cancer care continuum to inform planning and decision making. This review will help support planning and decision-making discussions, which should ensure that the economic burden on patients and families is accounted for when setting priorities to sustain the cancer care system.

Supplementary Materials

The following are available online at, Supplementary 1: Search strategies, Supplementary 2: Total cost conversion and estimation, Supplementary 3: Cost conversion and estimation across categories, Supplementary 4: Preferred reporting items for systematic reviews and meta-analyses (PRISMA) checklist.

Author Contributions

All authors made substantial contributions to the conception, design of the work; data acquisition, analysis synthesis, interpretation of data; and drafting of the manuscript. All authors have read and agreed to the published version of the manuscript.


This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.


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Figure 1. Preferred Reported Items for Systematic Reviews and Meta-Analyses (PRISMA) diagram. Note: This diagram shows the flow of information through the different sections of the systematic review, including the identified, excluded and included studies after the title/abstract and full-text reviews.
Figure 1. Preferred Reported Items for Systematic Reviews and Meta-Analyses (PRISMA) diagram. Note: This diagram shows the flow of information through the different sections of the systematic review, including the identified, excluded and included studies after the title/abstract and full-text reviews.
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Figure 2. Range of monthly out-of-pocket costs per patient by country. Countries in the European Union (EU) include Italy, France, Ireland, and Germany. Costs are expressed in 2018 USD. Not enough data were available to include a range of costs (in 2018 USD) for other countries. Average costs per patient per month were also estimated: USD 300 in the U.S., USD 200 in Canada, USD 180 in the E.U. and USD 70 in Australia Not enough data were available to stratify these estimates by cancer site.
Figure 2. Range of monthly out-of-pocket costs per patient by country. Countries in the European Union (EU) include Italy, France, Ireland, and Germany. Costs are expressed in 2018 USD. Not enough data were available to include a range of costs (in 2018 USD) for other countries. Average costs per patient per month were also estimated: USD 300 in the U.S., USD 200 in Canada, USD 180 in the E.U. and USD 70 in Australia Not enough data were available to stratify these estimates by cancer site.
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Figure 3. Average monthly out-of-pocket costs per patient by spending categories. Note: The medical expenditure categories were defined as prescription or over-the-counter drugs and medications, home and clinical medical visits, and in-hospital care. The non-medical categories included transport, travel and lodging, and formal and informal caregiver costs (e.g., daycare for pediatric patients). Costs are presented for comparison between the U.S. and countries with universal healthcare coverage. Not enough data was available to estimate costs for low- and middle-income countries. Costs are expressed in 2018 USD. Not enough data were available to stratify these estimates by cancer site.
Figure 3. Average monthly out-of-pocket costs per patient by spending categories. Note: The medical expenditure categories were defined as prescription or over-the-counter drugs and medications, home and clinical medical visits, and in-hospital care. The non-medical categories included transport, travel and lodging, and formal and informal caregiver costs (e.g., daycare for pediatric patients). Costs are presented for comparison between the U.S. and countries with universal healthcare coverage. Not enough data was available to estimate costs for low- and middle-income countries. Costs are expressed in 2018 USD. Not enough data were available to stratify these estimates by cancer site.
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Figure 4. Average monthly out-of-pocket costs per patient by cancer site with 95% confidence intervals from high-income countries. Note: Studies that included patients with multiple cancer sites are reported under the ‘All cancer’ and ‘pediatric cancer’ categories. Costs are expressed in 2018 USD. Not enough data were available to report average costs per cancer site for low- and middle-income countries, or for individual high-income countries.
Figure 4. Average monthly out-of-pocket costs per patient by cancer site with 95% confidence intervals from high-income countries. Note: Studies that included patients with multiple cancer sites are reported under the ‘All cancer’ and ‘pediatric cancer’ categories. Costs are expressed in 2018 USD. Not enough data were available to report average costs per cancer site for low- and middle-income countries, or for individual high-income countries.
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Figure 5. Average monthly out-of-pocket costs per patient by cancer site in the U.S. Note: Studies that included patients with multiple cancer sites are reported under the ‘All cancer’ category. Costs are expressed in 2018 USD. Not enough data were available to report average costs per cancer site for low- and middle-income countries, or for other high-income countries.
Figure 5. Average monthly out-of-pocket costs per patient by cancer site in the U.S. Note: Studies that included patients with multiple cancer sites are reported under the ‘All cancer’ category. Costs are expressed in 2018 USD. Not enough data were available to report average costs per cancer site for low- and middle-income countries, or for other high-income countries.
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Figure 6. Average out-of-pocket costs per patient as a percentage of income. Legend: LMIC = low- and middle-income countries; HIC = high-income countries; ASG = Action Study Group; blue bars represent studies from HICs; green bars represent studies from LMICs. Note: This figure shows the costs from individual studies that estimated out-of-pocket expenditures relative to annual income. A weighted average was calculated for high-income countries (in green) and low-and middle- income countries (blue). Studies conducted in high-income countries include the U.S., Canada, and Australia. Studies conducted in low- and middle-income countries include China, Malaysia, India, Haiti, Brunei, Thailand, Indonesia, Philippines, Vietnam, Laos, Cambodia, and Myanmar.
Figure 6. Average out-of-pocket costs per patient as a percentage of income. Legend: LMIC = low- and middle-income countries; HIC = high-income countries; ASG = Action Study Group; blue bars represent studies from HICs; green bars represent studies from LMICs. Note: This figure shows the costs from individual studies that estimated out-of-pocket expenditures relative to annual income. A weighted average was calculated for high-income countries (in green) and low-and middle- income countries (blue). Studies conducted in high-income countries include the U.S., Canada, and Australia. Studies conducted in low- and middle-income countries include China, Malaysia, India, Haiti, Brunei, Thailand, Indonesia, Philippines, Vietnam, Laos, Cambodia, and Myanmar.
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Figure 7. Quality assessment of individual studies. Note: This figure shows the proportion of studies with low, unclear or high risk of bias, as per the Ottawa-Newcastle Assessment Tool for cohort and cross-sectional studies. The dimensions evaluated for risk of bias were patient selection, comparability, and outcome assessment.
Figure 7. Quality assessment of individual studies. Note: This figure shows the proportion of studies with low, unclear or high risk of bias, as per the Ottawa-Newcastle Assessment Tool for cohort and cross-sectional studies. The dimensions evaluated for risk of bias were patient selection, comparability, and outcome assessment.
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Table 1. Study characteristics.
Table 1. Study characteristics.
First AuthorYearCountry Cancer Care ContinuumSample SizeMean Age (SD)% over 60 Years% Female% InsuredType of InsuranceMeanStudy DesignStudy Population
All cancer (adults)
Bates2018AustraliaPost diagnosis25,530NR57.20%44NRNRNRRetrospective observational studyAll cancer patients in Queensland
Callander2019AustraliaPost diagnosis42957.4 (15.4)NR49100%PublicNRRetrospective observational studyAll cancer patients in Queensland
Gordon2009AustraliaDiagnosis onwards43957 (12)NR6147%Private55% of households earned < AUD 40,000 per yearCross-sectionalAdults diagnosed or treated for cancer at the Townsville Hospital Cancer Centre
Newton2018AustraliaDiagnosis40064 (11)53% over 6549100%AnyAUD 919 weekly per household Cross-sectionalCancer patients who resided in rural regions of Western Australia
Action Study Group2015Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Thailand, VietnamTreatment (post-surgery)45845113% over 657244%AnyNRProspective cohort studyAll cancer patients with planned surgery
Yu2015CanadaPalliative care186NR61% over 7054.84100%PublicNRCohortEnd of life
Dumont2015CanadaPalliative care25258NR73100%PublicNRLongitudinal, prospective design with repeated measuresPatients enrolled in a regional palliative care program and their main informal caregivers
Longo2011CanadaTreatment onwards28261.6NR47100%Public11% of households earned < USD 20,000 CAD per yearCross-sectional designUrban and rural patients in 5 of the 8 cancer clinics in the province of Ontario
Koskinen2019FinlandDiagnosis onwards197866 (26–96 range)NR45100%PublicNRCross-sectional registry and survey studyPatients having either prostate, breast or colorectal cancer
Buttner2018GermanyTreatment onwards50246 (8)0%46.6100%Any33.3% households earned <USD 1000 Euros per yearProspective cohort studyWorking age cancer patients
Mahal2013IndiaDiagnosis onwards821NRNRNR3.41%PrivateNRCross-sectional surveyHousehold with at least one person living with cancer, or hospitalized due to cancer
Collins2017IrelandTreatment onwards151Median 58 (range 20–79)NR60NRNRNRRetrospective cohort studyCancer patients, 18 years or older
Baili2015ItalySurvivorship296NR17% over 8059NRNRNRRetrospective cohort studyPatients diagnosed between 2003 and 2007
Isshiki2014JapanTreatment52163NRNRNRNRNRObservational descriptive studyCancer patients receiving anti-cancer treatment
Action Study Group2016Singapore, Brunei, Malaysia, Thailand, Indonesia, Philippines, Vietnam, Laos, Cambodia, MyanmarDiagnosis onwards9513Median 52 (IQR = 26)NR3743Any41% of households earn 0–75% of mean national incomeProspective cohortNewly diagnosed adult cancer patients recruited from 47 public and private hospitals
Marti2015UKSurvivorship298NR56%55100%PublicNRProspective cohort studyPatients diagnosed with potentially curable breast, colorectal or prostate cancer
Bernard2011USATreatment onwards4110NR43% over 556294%AnyUSD 62,026 year in 2004 per householdCase–controlPersons 18 to 64 years of age who received treatment for cancer
Chino2018USATreatment245Median 60—Range 27–91NR55100%AnyNRRetrospective cohort studyPatients with solid tumour cancers receiving chemotherapy or hormonal therapy
Colby2011USATreatment329NRNR94.9100%PublicNRRetrospective cohort studyCancer patients who discontinued medication
Davidoff2012USADiagnosis onwards1868NR94% over 65 49100%PublicUSD 35,356 per year per patientRetrospective, observational studyMedicare beneficiaries with newly diagnosed cancer
Dusetzina2017USATreatment63,780NRNR57.2100%AnyNRRetrospective, observational studyPatients aged 18 through 64 years who had prescription drug coverage
Dusetzina2016USATreatment3344NRNRNR 100%AnyNRRetrospective, observational studyOrally administered anticancer medications
Finkelstein2009USATreatment onwards67950 (10.1)NR6979.80%AnyUSD 49,240 per year per householdRetrospective, observational studyWorking age cancer patients (age 25–64)
Guy2018USADiagnosis onwards4271NR65% over 506589.30%AnyNRRetrospective observational studyAdults with a cancer diagnosis
Houts1984USATreatment13957NR66NRNRNRProspective observational studyPatients receiving outpatient chemotherapy treatments in seven oncology practices
John2016USASurvivorship297761.9 (0.8)44.7% over 654894%AnyNRCross-sectionalAdults who self-reported ever having received any cancer diagnosis
Kircher2014USATreatment660770.1 (0.2)NR48100%AnyNRCase–controlIndividuals aged over 55 years with cancer coded in the condition file in MEPS
Langa2004USATreatment onwards98880 (0.3)100%54100%PublicNRObservational descriptive studyCancer patients over 70 years old
Narang2016USADiagnosis onwards1409Median 73 (IQR 69–79)NR46.4100%Any25% of households earned < USD 22,380 per yearProspective cohort studyUS residents older than 50 years
Raborn2012USATreatment609453 (13)NR54.4100%AnyNRA retrospective claims-based analysisPatients over 18 years with at least one claim of an oral oncolytic therapy
Shih2015USATreatment200,16852NRNR100%PrivateNRCohortPatients undergoing chemotherapy, in Lifelink Health Plan Claims Database
Shih2017USATreatment42,11172.17 (9.93)100% over 65 50.9100%PrivateNRCohortMedicare beneficiaries, insured
Stommel1992USATreatment19258.7 (12.2)NR49.5NRNRUSD 34,473 per household per yearCross-sectionalStudy sample had at least one dependent in an activity of daily living and caregiver
Tangka2010USANR24,654NRNRNR100%AnyNRCohortPanel survey population
Tomic2013USATreatment28,97959 (12)29% over 6571100%AnyNRCohortAdult patients who received chemotherapy and granulocyte colony-stimulating factors in the outpatient setting in the United States
Kaisaeng2014USATreatment378175 (7)NR97100%PublicNRCross-sectionalMedicare beneficiaries who filled a prescription for imatinib, erlotinib, anastrozole, letrozole, or thalidomide during 2008.
Markman2010USANR1767NR42%58NRNR7% of households earned < USD 20,000 per yearObservational descriptive studyBreast, colon, lung, and prostate cancer who joined the NexCura program
Jung2018USATreatment148,26576 (7.3)NR51100%PublicUSD 61,317 per yearNatural experimental designElderly Medicare beneficiaries with cancer
Chang2004USADiagnosis onwards5867 (12)NR30100%AnyNRRetrospective matched-cohort controlIndividuals insured by private or Medicare supplemental health plans
All cancer (pediatric)
Cohn2003AustraliaDiagnosis onwards1008.9 (range 0.8–18)0%50100%AnyNRCross-sectionalChildren with cancer and their families
Tsimicalis2013CanadaTreatment7837.38 (parents)NRNR100%PublicAssumed: USD 73,500 per household per yearCohort, cost of illnessConvenience sample
Tsimicalis2012CanadaTreatment997.85 (5.28)NRNR100%PublicAssumed: USD 73,500 per household per yearCohort, cost of illnessConvenience sample
Ahuja2019IndiaDiagnosis onwards11NRNRNRNRNRNRProspective cohortChildren with cancer and their families
Sneha2017IndiaTreatment707.8 (2.2)0%310%Private15% of households earned< 60,000 Rs. per year Cross-sectionalClinical setting
Ghatak2016IndiaTreatment onwards505.6 (2.9)024NRNR239 USD per month per householdProspective observational studyFamilies with children with acute lymphoblastic leukemia
Bloom1985USADiagnosis onwards569NRNRNRNRNRUSD 25,790 annual family income Retrospective observational studyChildren with malignant neoplasms
Lansky1979USATreatment707 (4.5)034NRNRUSD 13,500Prospective cohort studyParents of children in treatment for cancer by the pediatric hematology department
Boyages2016AustraliaTreatment361NR56% over 55100NRNR20.6% households earned < USD 45,000 (AUD 2016) per year Cross-sectionalFemales with primary stage I, II, or III breast cancer; had completed treatment at least 1 year prior to recruitment; and fluent in English
Gordon2007AustraliaDiagnosis onwards28757 (9.6)62% over 5010070%Private29% of patients earned < USD 26,000 AUD per yearLongitudinal, population-based studyWomen with breast cancer 0–18 months post-diagnosis
Housser2013CanadaTreatment onwards301NR47% over 654364.60%Private14.1% of patients earned less than CAD 20,000 per yearObservational descriptive study19 years of age or older, residents of Newfoundland, and diagnosed with breast or prostate cancer
Lauzier2012CanadaDiagnosis-treatment1191NR31.60%67100%Public58% of households earned < USD 50,000 per yearProspective cohort studyWomen with breast cancer and their spouses
Liao2017ChinaDiagnosis-treatment274649.67% over 65 100100%AnyUSD 8722Multicentre cross-sectional studyPatients with breast cancer diagnosis at a hospital affiliated with the CanSPUC project
O’Neill2015HaitiDiagnosis onwards6149 (9.8)NR98NRNRUSD 1333 per year per patientCross-sectionalPatients from Hopital Universitaire de Mirebalais
Bargallo-Rocha2017MexicoTreatment69Median 56 (IQR 11.5)NR100NRNRUSD 548 in Mexico/ monthCross-sectionalFemale patients who underwent breast cancer surgery
Bekelman2014USATreatment15,643NR34.2100100%Private13.5% households earned <USD 40,000/yearRetrospective observational studyWomen with breast cancer with breast conserving surgery
Chin2018USATreatment6900NR21%100100%PublicNRRetrospective cohort studyFemale patients aged 18 to 64 years
Dean2018USASurvivorship12965 (8)NR10098%Any13% patients earned <USD 30,000 per yearProspective, longitudinal studyWomen with stages I–III invasive breast cancer, completion of active breast cancer treatment, > 1 lymph node removed
Farias2018USATreatment6863NR17.30%100100%PrivateNRRetrospective, observational studyWomen under the age of 64 with at least 1 prescription claim
Giordano2016USADiagnosis onwards14,643Median 5412.2% over 65100100%AnyNRObservational Cohort StudyWomen aged over 18 years with breast cancer diagnosed between 2008 and 2012
Jagsi2014USADiagnosis onwards1502NR28% over 65100NRNRUSD 50,000 per yearLongitudinal cohort studyPatients age 20 to 79 years diagnosed with stage 0 to III breast cancer
Jagsi2018USADiagnosis onwards2502NR57%10095%Any37% of households earned < USD 40,000 per yearCross-sectional surveyPatients with early stage breast cancer
Leopold2018USATreatment—end of life5364NR58% over 50100100%AnyUSD 50,054Longitudinal time seriesInsured women with metastatic breast cancer
Pisu2016USASurvivorship432NR47.7% over 6510094%Public19.3% lowest income (<20,000 per year)Prospective cohort studyStage 0–III breast cancer, within the first three years after completing primary cancer treatment
Pisu2011USASurvivorship261NR16% over 65100NRNR11.5% lowest income (<20,000 per year)Cross-sectionalPatients diagnosed with stage I–II breast cancer, with a minimum of 1 month after treatment completion
Roberts2015USATreatment18,57553.6 (7.5)NR100100%PrivateNRA retrospective claims-based analysisWomen (ages 18–64) with at least two health encounter claims for breast cancer
Kodama2012JapanTreatment577Median 61 (15–94 range)NR35100%PublicUSD 36,731 USD per yearObservational descriptive studyPatients with CML who were prescribed imatinib
Wang2014SingaporeTreatment367NR8% over 6162.1NRNRNRCohortSecondary analysis of a prospective study
Darkow2012USATreatment99562NR47100%AnyNRRetrospective cohort studyAdult patients (aged >18 years) with an initial diagnosis of CML during 1997 to 2009
Doshi2016USADiagnosis onwards105373 (8)96% over 6547100%PublicNRA retrospective claims-based analysisMedicare patients with newly diagnosed CML
Dusetzina2014USATreatment154148(11)NR45100%AnyNRRetrospective, observational studyAdults (age 18 to 64 years) with CML who initiated imatinib therapy
Goodwin2013USATreatment onwards101561 (9.2)NR3997%AnyNRObservational descriptive studyPatients who had received intensive treatment for MM at the study site
Gupta2018USATreatment16256 (13)NR4997%Any42% patients earned less than USD 50,000 USD per yearCross-sectionalAdult patients with MM taking medication
Shen2017USATreatment89870 (12)NR4738%PublicNRRetrospective cohort studyPatients with Chronic Myeloid Leukemia Taking Targeted Oral Anticancer Medications
Olszewski2017USATreatment3038Median76 (IQR 71–82)NR50100%PublicUSD 29,700 per yearObservational descriptive studyPatients with Part D coverage at diagnosis
Huang2017ChinaDiagnosis onwards235657.428.3% over 6543100%AnyCNY 54,525 per patient per yearCross-sectional surveyPrimary prevalent CRC patients undergoing treatment in hospitals
Hanly2013IrelandDiagnosis and treatment154NR60% over 5582NRNRNRRetrospective observational studyCarers of colorectal cancer patients
O Ceilleachair2017IrelandSurvivorship4976746% over 703852%PrivateNRCase reportAll cases of primary, invasive colorectal cancer in Ireland diagnosed October 2007–September 2009
Shiroiwa2010JapanTreatment1319NRNRNR100%PublicNRRCT, EETrial population, XELOX or XELOX plus bevacizumab and second-line therapy with XELOX
Azzani2016MalaysiaDiagnosis onwards138Median 63 (IQR = 19)35.5% over 70 499%Private2000 RM/monthProspective, longitudinal studyCRC patients seeking treatment at the University of Malaya Medical Centre (UMMC) in the first year following diagnosis
Sculpher2000UKTreatment49561NR36NRNRNRRandomized-controlled trialColorectal cancer patients treated with Raltitrexed or Fluorouracil
Ezeife2018CanadaTreatment—Palliative care200NR50% over 655645.10%PrivateUSD 41,000-USD 80,000 CADCross-sectionalPatients with advanced lung cancer (stage IIIB/IV)
Andreas2018France, Germany and the United KingdomTreatment onwards831NR67%38100%PublicNRRetrospective observational studyPatients ≥18 years of age that had undergone complete resection of stage IB-IIIA NSCLC
Wood2019France, Germany, ItalyTreatment145764.5 (10.1)NR34.1NRNRNRCross-sectionalNR
Van Houtven2010USAInitial treatment, Continuing, Terminal, overall1629NR42.1% over 6575.8100%AnyUSD 39,554 per year per householdCross-sectionalInformal caregivers—Patients participating in the Share Thoughts on Care survey
Hess2017USADiagnosis onwards47,20765 (10.4)NR45100%AnyNRRetrospective observational study18 years of age or older at the time of initial diagnosis of lung cancer
Head and neck
Burns2017AustraliaSurvivorship-integrated care8265 (7.4)NR26NRNRNRRandomized-controlled trialPatients with head and neck cancer enrolled in speech pathology programs
Chauhan2018IndiaTreatment410NRNRNRNRNRNRRetrospective observational studyHead and cancer patients undergoing radiotherapy
de Souza2017USATreatment onwards7360 (26–79)NR21.9100%AnyUSD 81,597 per year per householdProspective observational studyHead and neck cancer patients with locally advanced stage
Massa2019USADiagnosis onwards16,77165 (95CI 63.1–66.8)NR35.597.40%AnyUSD 24,056Case controlAdult patients with cancer
Gordon2015AustraliaDiagnosis onwards28965 (8.4)78%071%Private38% households had incomes between USD 37,000 and AUD 80,000 per yearCross-sectionalMen who self-reported they had previously been diagnosed with prostate cancer
de Oliveira2013CanadaSurvivorship5857392.50%0100%Public40% earned <USD 40,000 per yearRetrospective, observational studyAll patients initially diagnosed with PC in 1993–1994, 1997–1998, and 2001–2002
Geynisman2018USATreatment11665 (range 27–88)NR1598%AnyNRRetrospective, observational studyAdvanced renal and prostate cancer patients
Jayadevappa2010USADiagnosis—Treatment51259 (6.3)NR0NRNR19% of patients earned < USD 40,000 per yearProspective cohort study45 years of age, newly diagnosed with PCa within the prior 4 months and yet to initiate\ treatment
Gordon2018AustraliaTreatment onwards41955NR5474%PrivateNRRetrospective, observational studyConsenting Qskin study participants
Gordon2018AustraliaTreatment onwards53956NR64NRNRNRRetrospective, observational studyConsenting Qskin study participants
Thompson2019AustraliaTreatment8613NRNRNR100%PublicNRCohortAdmin data linked to study population
Grange2017France, Germany and the United KingdomSurvivorship and Palliative care558NR54.50%44100%PublicNRRetrospective observational studyPatients with advanced melanoma
Bercow2018USADiagnosis onwards5031NR41.40%100100%PrivateNRRetrospective cohort studyOvarian cancer patients enrolled in commercial insurance sponsored by over 100 employers in the United States
Calhoun2001USATreatment83NRNR100NRNRNRProspective cohort studyOvarian cancer patients who experienced chemotherapy-associated hematologic or neurologic toxicities
Suidan2019USATreatment12,761NR44%100100%PrivateNRCohortAll ovarian cancer patients in MartketScan database undergoing first line treatment
Basavaiah2018IndiaTreatment9854.5 (10–87 range)41.8% over 603329.60%AnyNRProspective cohortPatients undergoing pancreatic-duodenectomy
Bao2018USAEnd-of-life3825NR100%55100%PublicNRRetrospective cohort studyPatients 66 years or older when diagnosed with Stage IV pancreatic cancer in 2006–2011
Chin2017USATreatment1025NRNR65100%PublicNRRetrospective cohort studyPatients with anal cancer treated with Intensity-modulated radiotherapy
Kumthekar2014USATreatment43Median 57 (range 24–73)NR4295%AnyUSD 75,000 per yearProspective observational studyPatients within 6 months of diagnosis or tumor recurrence
AUD = Australian dollar; CML = chronic myeloid leukemia; CNY = Chinese Yuan; NSCLC = Non-small-cell lung carcinoma; IQR = interquartile range; MM = multiple myeloma; NR = not reported; RM = Renminbi; Rs. Rupees; SD = standard deviation; USD = United States Dollar.
Table 2. Out-of-pocket estimates.
Table 2. Out-of-pocket estimates.
First AuthorYearDefinition of out-of-Pocket CostTotal out-of-Pocket Cost Estimate (Mean—SD)Time Frame of out-of-Pocket EstimateOut-of-Pocket as % of IncomeCurrencyCurrency Year
The Action Study Group2016Financial catastrophe was defined as OOP costs at 12 months exceeding 30% of annual household incomeNR3- and 12-month follow-ups48% of cancer patients reported Financial catastrophe at 12 monthsNRNR
The Action Study Group2015Financial catastrophe (out-of-pocket costs of >30% of annual household income)NR3 months31% of participants incurred Financial catastropheNR2015
Ahuja2019Direct costs incurred by families of children being treated for cancer651 (356)14 weeksNRUSD2013
Andreas2018Cost of childcare, and non-reimbursed transportation costs incurred by the patient or their family/friends.UK = 71 monthNREuro2013
Germany = 6
France = 0
Azzani2016Payments for expenses such as hospital stays, tests, treatment, travel and food.83061 year42% of the median annual income in Malaysia.RM2013
Baili2015Direct expenses which were not entirely covered or only partially covered by the NHS160 (372)1 monthNREuro2015
Bao2018Costs incurred by patients 30 days before death1930 (with chemotherapy)1 monthNRUSD2011
Bargallo-Rocha2017Patient borne costs on transportation, housing, and salary due to breast cancer5351 monthNRUSD2017
Basavaiah2018Catastrophic expenditure was defined as the percentage of households in which OOP health payments exceeded 10% of the total household incomeNRFrom the first hospital visit to postoperative recoveryA total of 76.5% of the sample incurred catastrophic expenditureUSD2015
Bates2018Patient co-payments for primary healthcare and prescription pharmaceuticals1000 (2000)1 yearNRAUD2017
Bekelman2014Summing deductible, co-payment, and coinsurance amounts.3421 (95% CI 3158–3706)1 yearNRUSD2013
Bercow2018Out-of-pocket (OOP) payment was calculated as the sum of deductibles, copayments, and coinsuranceMedian 2988 (IQR 1649–5088)1 yearNRUSD2013
BerNRrd2011OOP expenditures on health insurance premiums in addition to OOP expenditures on healthcare services4772NR6%USD2008
Bloom1985Direct medical and nonmedical expenses borne by the family97871 year37.7% of family incomeUSD1981
Boyages2016The financial cost of lymphedema care borne by women9771 yearNRAUD2014
Burns2017Costs associated with return travel to the regional speech pathology service256NRNRAUD2015
Buttner2018Direct payments for health services or treatments which are not covered by health insurance and need to be paid by the patients themselves205 (346)3 monthsNREuro2018
Calhoun2001Direct medical costs borne by patients33023 monthsNRUSD2001
Callander2019Patient co-payments for primary healthcare and prescription pharmaceuticals1191 (3099)1 yearNRAUD2017
Chang2004Copays and deductibles to caregivers302 (634)1 monthNRUSD2004
Chauhan2018Only the direct OOP expenditure was assessed849NRNRUSD2015
Chin2018Copayments for oral anticancer medication191 monthNRUSD2014
Chin2017The sum of Medicare Part A and Part B reimbursements, third-party payer reimbursements, and patient liability amountsMedian 6967 (5226–9076)1 yearNRUSD2011
Chino2018Insurance premiums; medication copays; physician office charges; copays for procedures, tests, and studies; and costs related to travel for treatmentMedian 393 (Range—0–26,586)1 month7.80%USD2018
Cohn2003Travel, accommodation, and communication costs19,604 (32,976)40 monthsNRAUD2003
Colby2011Patient spending on ani cancer drugs6453 monthsNRUSD2011
Collins2017Personal expenditure on regular and non-regular indirect costs during treatment.1138 (range 21–7089)1 monthNREUR2017
Darkow2012Copayment for anti cancer medication1241 monthNRUSD2012
Davidoff2012Costs incurred by patients4727 (202)2 years23.90%USD2007
de Oliveira2013Medical costs associated with health Professional visits, and nonmedical costs such as travel, parking, food, and accommodation200 (95% CI USD 109–290)1 year10%CAD2006
de Souza2017Insurance premiums; deductibles; direct medical costs805 (range 6–10,156)1 month15.10%USD2017
Dean2018Co-payments for outpatient physician visits, physical and occupational therapy visits, complementary and integrative therapy visits23061 yearNRUSD2015
Doshi2016Direct medical costs borne by patients26001 monthNRNR2016
Dumont2015NR576 (46)6 monthsNRCAD2015
Dusetzina2017Copayment, coinsurance, and deductibles, adjusting to reflect spending on a median monthly dosage1431 monthNRUSD2012
Dusetzina2016Copayments for orally administered anticancer medications3101 monthNRUSD2014
Dusetzina2014Monthly copayments for imatinib108 (301)1 monthNRUSD2011
Ezeife2018Expenses for prescription drugs, travel, childcare/babysitting, copayments, and deductiblesMedian 1000–50001 yearFrom 2–12% (median)CAD2018
Farias2018Sum of the copayments, deductibles, and coinsurance paid for AET medication193 (97)1 monthNRUSD2018
Finkelstein2009Copayments, deductibles, and payments for noncovered services1730 (2710)1 yearNRUSD2005
Geynisman2018Co-pays for oral anti cancer medications81.261 monthNRUSD2018
Ghatak2016Direct medical, living (rent, food, clothes), and transport costsMedian 524 (395–777 IQR)1 month3.5 times–7 times the monthly incomeUSD2013
Giordano2016Drug and insurance-related costs borne by patients322618 monthsNRUSD2013
Goodwin2013Direct and indirect patient expenditureNR1 year38% and 31% annually for patients receiving/not receiving chemotherapy, respectively.NR2013
Gordon2007Direct costs (garments and aids), health services (e.g., co-payments, pharmaceuticals) and paid home services1937 (3210) 18 monthsNRUSD2005
Gordon2018Melanoma treatment costs borne by patients625 (575)3 yearsNRAUD2016
Gordon2018Medical expenses for Medicare services borne by patients3514 (4325)2 yearsNRAUD2016
Gordon2009Medical and non-medical costs borne by patients4826 (5852)16 monthsNRAUD2008
Gordon2015Medical and non-medical costs borne by patients9205 (14,567)16 monthsNRAUD2012
Grange2017Childcare and non-reimbursed transportation costsFrance = 01 monthNREUR2013
Germany = 332 (95% CI 271–401)
UK = 533 (477–594)
Gupta2018Costs for doctor visits, prescriptions, over-the-counter medications, transportation709 (1307)3 monthsNRUSD2018
Guy2018Expenditures toward any healthcare service, such as coinsurance, copayments, and deductibles2171 (95% CI 1970–2373)1 year4.3% had OOP > 20% of household incomeUSD2012
Hanly2013Parking, meals and accommodation, domestic-related caring activities79.2 (151)1 weekNREUR2008
Hess2017Copayments, deductibles and patient borne costs315 (95% CI 106–523)1 monthNRUSD2014
Housser2013Costs not covered by insurance or assistance programsProstate: 910 (1025)
Breast: 864 (1220)
3 months17% had OOPC >7.5% of income (16% prostate, 19% breast)CAD2008
Houts1984Nonmedical expenses borne by patientsMedian 21 (0–204 range)1 week28% of respondents were spending over 25% of their weekly incomesUSD1984
Huang2017Overall medical and non-medical expenditure32,6491 year59.9% of their previous-year household incomeCNY2014
Isshiki2014Travel/transport costs per outpatient treatment791 monthNRUSD2014
Jagsi2014Medical expenses related to breast cancer, including copayments, hospital bills, and medication costsMedian <20004 yearsNRUSD2014
Jagsi2018Medical and non-medical expenses related to breast cancer (including copayments, hospital bills, and medication costs)Median <2000NR17% of patients reported spending ≥10% of household income on out-of-pocket medical expensesUSD2018
Jayadevappa2010Medication and non-medical costs paid by patients703 (2500)3 monthsNRUSD2010
Jung2018Costs of specialty cancer drugs paid by patients3860 (1699)1 yearNRUSD2013
John2016Alternative medicine costs borne by patients and not covered by insurance4451 yearNRUSD2012
Kaisaeng2014Copayments for oral anti cancer drugs154 (407)1 monthNRUSD2008
Kircher2014Direct payment for all prescription drugs724 (42)NRNRUSD2010
Kodama2012Copayment for medical expensesMedian 11,548 1 yearNRUSD2008
Koskinen2019Out of pocket fees for outpatient visits, inpatient care, home care, and surgical procedures280 (603 for palliative care—383 metastatic disease—224 remission—264 rehabilitation—263 treatment)6 monthsNREuro2010
Kumthekar2014Medical and nonmedical expenses that were not reimbursed by insurance2451 (2521)1 monthNRUSD2014
Langa2004Cost paid by patients on hospital services, outpatient care, home care, and medication4656 (3890)1 yearNRUSD1995
Lansky1979Non-medical costs paid by the patient’s family56 (54)1 week26% of weekly incomeUSD1979
Lauzier2012Costs for treatments and follow-up, consultations with other practitioners, home help, clothing, and natural health products1365 (1238)1 yearOut-of-pocket costs represented an average of 2.3% of annual family incomeCAD2003
Leopold2018Patient expenditures including coinsurance, copayment, and deductible amounts4247—95% CI (3956–4538) among low deductible health plan1 year13% of the 2011 real median income householdUSD2012
6642—95% CI (6268–7016) among High deductible health plan
Liao2017Medical expenditure (self-pay and healthcare costs), non-medical expenditure (i.e., transportation, accommodation)8449Since diagnosis to treatment49% (overall OOP expenditure/annual income)USD2014
Longo2011Patient borne costsBreast 392 (830)1 monthNRCAD2001
Other 149 (265)
Mahal2013Patient medical and non-medical spending5311 (4514–6108 95CI)1 yearNRINR2004
Markman2010Cancer related costs paid by patients12% spent between USD 10,000–25,000Since diagnosisNRUSD2010
4% spent between USD 25,000–50,000
2% spent between USD 50,000–100,000
Marti2015Medical and non-medical costs borne by patients, such as medications, travel, and childcare Full Sample 39.8 (95% CI 14.5–65.3)3 monthsNRUSD2012
Colorectal 52 (22–126)
Breast 49 (12–86)
Prostate 11 (3–19)
Massa2019Total non-reimbursed cost of cancer patientsMedian 929 (95% CI 775 to 1084) for HNC1 yearMedian 3.93% of total income spent on OOP (95% CI 3.21 to 4.65)USD2014
918 (885 to 951) for other cancer
Narang2016Costs paid by patients on inpatient hospitalization, nursing homes, clinic visits, outpatient surgery3737 average1 yearUninsured: 23%USD2012
2116 MedicaidMedicaid: 8.5%
5492 employer-sponsored insuranceEmployer-sponsored insurance: 12.6%
8115 uninsuredNR
Newton2018Direct medical and nonmedical expenses borne by the patient2179 (3077) (95% CI 1873–2518)21 weeks11% spent over 10% of household incomeAUD2016
O Ceilleachair2017OOPCs survivors had incurred as a result of their diagnosis, and which were not recouped from PHI or other sources1589 (3827)1 yearNREuro2008
Olszewski2017Patient’s cost sharing on medicationNo low-income subsidy: median 5623 (IQR 3882–9437)1 year23% of annual income among non-subsidizedUSD2012
Low-income subsidy: median 6 (IQR 3–10)
O-Neill2015Medical and nonmedical costs related to the hospital visit coinciding with the interview717 (95% CI 619–1171)1 year>67% patients had catastrophic expenses (>40% of household income)USD2014
Pisu2016Out of pocket costs for medical careTotal at baseline: 232 (82)1 monthNRUSD2015
Total at 3 months 186 (71)
Pisu2011Expenses since diagnosis, including monthly insurance premiumsTotal: 316.1 (411.5)1 month31% for lowest income level (<20,000 per year)USD2008
Caucasian: 297 (296)
Minority: 204 (405)
Raborn2012Deductibles and co-payments for anticancer medicationGeneric versions: 171 (652)Per claimNRUSD2009
No available generic versions: 31 (130)
Roberts2015Deductibles, copayments, and coinsurance payments175 (484)1 yearNRUSD2012
Sculpher2000Travel expenses for treatment appointmentsTreated with Raltitrexed: 12.25 (41.87)
Treated with Fluorouracil: 10.70 (20.16)
Per patient-journeyNRGBP2000
Shen2017Patient out of pocket expenses on targeted oral anti-cancer medicationsMedian 401 (IQR 1029)1 monthNRUSD2014
Shih2015Patient OOP payments were calculated as allowed minus paidUSD 647 per month in 20111 monthNRUSD2011
Shih2017Patient pay amount is the amount paid by beneficiaries that is not reimbursed by a third party; therefore, it captures the OOP payments for Medicare beneficiaries who are enrolled in the Part D program. 8501 monthNRUSD2012
Shiroiwa2010Co-paymentPatients JPY 328,000 (95% CI: 323,000–334,000)11 monthsNRJPY2009
Patients ≥ 70 years JPY 61,000 (95% CI: 60,000–63,000)NR
Sneha2017Medical expenses and nonmedical out-of-pocket expenses incurred by the families in the course of careNRPer dayNon-medical expenses—Urban: 22%INR2012
Rural: 46%
Stommel1992Out-of-pocket payments for services: hospital and physician services, nursing homes, medications, visiting nurses, home health aides, and purchases of special equipment, supplies, and foods and supplements660 (624)3 monthsNRUSD1993
Suidan2019Patient out-of-pocket expenses, in addition to insurance payments made.Neoadjuvant chemotherapy: USD 2519 8 months NRUSD2017
Primary debulking: USD 2977NR
Tangka2010OOP cost (inpatient, outpatient, other noninpatient (costs related to emergency room visits, home healthcare, vision aids, and other medical supplies), Rx) attributable to cancer = difference between expenditures for persons with cancer and persons without cancer, adjusted for sociodemographic and comorbidities39961 yearNRUSD2007
Thompson2019Costs to items associated with the excision, including consultations, skin cancer treatment, Anatomical pathology, skin flaps and Anesthesia;Excluding bulk-billed patients were co-payment would be USD 0Private clinical rms: 80 (34, 170) Treatment episode (up to 3 days post-discharge)NRAUD2018
Public hospital: 35 (30, 104)
Private hospital: 350 (196, 596)
Tomic2013Out-of-pocket costs for G-CSF per patient100–150: pegfilgrastim
50–80: filgrastim
3 monthsNRUSD2010
Tsimicalis2013Direct costs included health services, prescription medications, over-the-counter medications, complementary medicines, supplies, equipment, family medical fees and medications, as well as travel, food, communication, accommodations, moving or renovations, provider for the child with cancer, domestic labour (e.g., sibling child care), funeral, and other cost categories not yet captured in the literature730 (1520)3 monthsNRCDN2007
Tsimicalis2012Direct costs as well as travel, food, communication, accommodations, moving or renovations, provider for the child with cancer, domestic labour (e.g., sibling childcare), funeral, and other costs5446 (6659)3 monthsNRCDN2007
Van Houtven2010Out-of-pocket expenditures for the patient’s medical care as well as nonmedical expendituresOverall: 1243By phaseNRUSD2005
Initial: 921NR
Continuing: 1545NR
Terminal: 1015NR
Wang2014Ward charges, laboratory charges, radiology charges, prescription charges, surgical charges, and other charges2230 (95% CI: 1976–2483)Per episodeNRUSD2012
Wood2019Direct out-of-pocket expenses were defined as wage losses (per week); non-medical expenses associated with general practitioner or hospital visits (in the last 3 months); costs of treatments for conditions linked to NSCLC (in the last week), such as those for pain or symptom relief; and other non-medical costs arising from the diagnosis (per week), including additional childcare costs, assistance at home (cleaner, housekeeper, gardener), and travel costs.Patient: 823
Caregivers: 1019
3 months, reported as annualNREUR2018
Yu2015Out-of-pocket costs: costs paid by the patient/family for travel, supplies, medications, etc.NREntire palliative trajectoryNRCDN2012
AUD = Australian dollar; CAD = Canadian dollar; CI = confidence interval; CNY = Chinese yuan; GBP = Great Britain Pound; INR = Indian Rupee; IQR = interquartile range; JPY = Japanese Yen; NR = not reported; OOP = out-of-pocket; RM = Renminbi; SD = standard deviation; USD = United States Dollar.
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