Financial toxicity of cancer treatment in India: towards closing the cancer care gap

Revisiting a decade of inequality in healthcare financial burden in Cambodia, 2009-19: trends, determinants and decomposition

BACKGROUND

Out-of-pocket healthcare expenditure (OOPHE) without adequate social protection often translates to inequitable financial burden and utilization of services. Recent publications highlighted Cambodia's progress towards Universal Health Coverage (UHC) with reduced incidence of catastrophic health expenditure (CHE) and improvements in its distribution. However, departing from standard CHE measurement methods suggests a different storyline on trends and inequality in the country.

OBJECTIVE

This study revisits the distribution and impact of OOPHE and its financial burden from 2009-19, employing alternative socio-economic and economic shock metrics. It also identifies determinants of the financial burden and evaluates inequality-contributing and -mitigating factors from 2014-19, including coping mechanisms, free healthcare, and OOPHE financing sources.

METHODS

Data from the Cambodian Socio-Economic Surveys of 2009, 2014, and 2019 were utilized. An alternative measure to CHE is proposed: Excessive financial burden (EFB). A household was considered under EFB when its OOPHE surpassed 10% or 25% of total consumption, excluding healthcare costs. A polychoric wealth index was used to rank households and measure EFB inequality using the Erreygers Concentration Index. Inequality shifts from 2014-19 were decomposed using the Recentered Influence Function regression followed by the Oaxaca-Blinder method. Determinants of financial burden levels were assessed through zero-inflated ordered logit regression.

RESULTS

Between 2009-19, EFB incidence increased from 10.95% to 17.92% at the 10% threshold, and from 4.41% to 7.29% at the 25% threshold. EFB was systematically concentrated among the poorest households, with inequality sharply rising over time, and nearly a quarter of the poorest households facing EFB at the 10% threshold. The main determinants of financial burden were geographic location, household size, age and education of household head, social health protection coverage, disease prevalence, hospitalization, and coping strategies. Urbanization, biased disease burdens, and preventive care were key in explaining the evolution of inequality.

CONCLUSION

More efforts are needed to expand social protection, but monitoring those through standard measures such as CHE has masked inequality and the burden of the poor. The financial burden across the population has risen and become more unequal over the past decade despite expansion and improvements in social health protection schemes. Health Equity funds have, to some extent, mitigated inequality over time. However, their slow expansion and the reduced reliance on coping strategies to finance OOPHE could not outbalance inequality.

Economic Burden of Healthcare Services on Cancer Survivors in Bangladesh

BACKGROUND

Cancer is a critical public health issue that imposes a considerable economic burden, especially in low-resource countries. In Bangladesh, there has been a noticeable lack of research focusing on the economic burden associated with cancer.

AIMS

This study aimed to examine the economic burden of cancer care and the contributing factors.

METHODS

This cross-sectional study included 623 cancer patients. Data were collected between January and May 2022. The magnitude of the economic burden (no burden to extreme burden) was the outcome variable. A logistic regression model was performed to determine the associated factors of the economic burden of cancer.

RESULTS

Overall, 34% of cancer survivors experienced extreme economic burden due to treatment costs. Patients with prostate (relative risk ratio, RRR = 23.24; 95% confidence interval, CI: 1.97, 273.70), bone (RRR = 5.85; 95% CI: 1.10, 31.04), and liver cancer (RRR = 4.94; 95% CI: 1.29, 18.9) reported significantly higher extreme economic burden compared to patients with other cancers. The economic burden was significantly higher for patients diagnosed with Stage III (RRR = 38.69; 95% CI: 6.17, 242.72) and Stage IV (RRR = 24.74; 95% CI: 3.22, 190.11) compared to Stage 0. Patients from low-income households suffered from nine times more extreme burden (RRR = 8.85; 95% CI: 4.05, 19.36) compared with those from high-income households.

CONCLUSION

Our study found a disproportionately high economic burden among patients with cancer, across disease sites, stages, and income quintiles. The burden was significantly higher among patients with prostate, bone, and liver cancer, and those diagnosed with advanced stage. The findings underscore the importance of early cancer detection before metastasis which may lead to more efficient treatment, avoid disease progression, lower disease management costs, and better health outcomes. Patients from low-income households experience an extreme economic burden due to cancer, highlighting the need for affordable healthcare services, financial support, and healthcare subsidies.

Treatment challenges and outcomes of older patients with acute myeloid leukemia from India

Globally, overall survival (OS) of older patients with AML continues to be suboptimal with very little data from India. In a multicenter registry analysis, we evaluated 712 patients with AML older than 55 years. Only 323 (45.3%) underwent further treatment, of which 239 (74%) received HMAs, and 60 (18%) received intensive chemotherapy (IC). CR was documented in 39% of those receiving IC and 42% after HMAs. Overall, 100 (31%) patients died within 60 days of diagnosis, most commonly due to progressive disease (47%) or infections (30%). After a median follow-up of 176 days, 228 (76%) of patients had discontinued treatment. At one year from diagnosis, 211 (65%) patients had died, and the median OS was 186 days (IQR, 137-234). Only 12 (3.7%) patients underwent stem cell transplantation. Survival was significantly lower for those older than 60 years (p < 0.001). Patients who died had a higher median age (p = .027) and baseline WBC counts (p = .006). Our data highlights suboptimal outcomes in older AML patients, which are evident from 55 years of age onwards, making it necessary to evaluate HMA and targeted agent combinations along with novel consolidation strategies to improve survival in this high-risk population.

Assessment of Financial Toxicity and Coping Strategies Associated With Cancer Treatment Among Caregivers of Patients With Cancer From a Lower-Middle-Income Country

PURPOSE

The rising cost of cancer treatment causes out-of-pocket spending among patients or caregivers in lower-middle-income countries, resulting in acute misery and insolvency. This study aimed to assess the financial toxicity associated with cancer treatment and the coping strategies for cancer treatment adopted among the caregivers of patients with cancer in a tertiary cancer care center.

MATERIALS AND METHODS

This prospective cross-sectional study was conducted among the primary caregivers of patients with cancer undergoing curative treatment from March to June 2023. The estimated sample size was 403 caregivers. The financial toxicity was assessed using a modified Comprehensive Score for Financial Toxicity-Functional Assessment of Chronic Illness Therapy tool, and coping strategies were explored using a validated questionnaire of 20 questions. Univariate and multivariate analyses investigated the associations and factors influencing financial toxicity.

RESULTS

The caregivers recruited in the study were 403; 83.8% were younger than 50 years, and 66.5% were male. The common cancer types included were breast cancer (27.3%), GI cancer (17.9%), head and neck cancer (12.4%), and gynecological cancer (11.6%). The mean financial toxicity score was 22.32 (standard deviation, 9.55), with 64% experiencing moderate to severe financial toxicity. The most common coping strategies used were spending a portion or all of the savings, borrowing money from others, restructuring their spending habits, seeking financial assistance from the cancer center, and resorting to gold loans.

CONCLUSION

Screening patients and their primary caregivers using a modified COST tool can help identify families experiencing severe financial toxicity and provide necessary intervention.

Exploring the financial burden due to additional mobility among cancer patients: A cross-sectional study based on National Sample Survey

BACKGROUND

Cancer imposes a substantial economic burden due to treatment costs, supportive care, and loss of productivity. Besides all the affecting factors, major concerns lead to significant financial burdens of cancer treatment, bringing unwanted huge unbearable direct and indirect treatment costs. The aim was to explore the nature of additional mobility/travel required for accessing health care for cancer patients and also to assess financial burden due to additional mobility/travel costs for cancer treatment.

METHODS

This study employed unit-level cross-sectional data from the 75th round (2017-18) of India's National Sample Survey (NSS). The primary analysis commenced with descriptive and bivariate analyses to explore mean health spending and out-of-pocket expenses. Subsequently, multivariable logistic regression models were utilized to estimate the associations between catastrophic health expenditure, distress financing, and the treatment location.

RESULTS

The findings highlight distinct healthcare utilization patterns: inpatient treatments predominantly occur within the same district (50.4 %), followed by a different district (38.8 %), and a smaller share in other states (10.8 %). Outpatients largely receive treatment in the same district (65.5 %), followed by a different district (26.8 %), and around 8 % percent in other states. Urban areas show higher inpatient visits within the same district (41.8 %) and different districts (33.5 %). Outpatients, particularly those seeking treatment in other states, experience higher total expenditures, notably with higher out-of-pocket expenses. Distress financing is more common among inpatients (20.6 %) and combined inpatient/outpatient cases (23.9 %), while outpatients exhibit a lower rate (6.8 %).

CONCLUSION

The findings collectively suggest the importance of developing local healthcare infrastructures to reduce the additional mobility of cancer patients. The policy should focus to train and deploy oncologists in non-urban areas can help bridge the gap in cancer care proficiency and reduce the need for patients to travel long distances for treatment.