The Invisible Costs of Cancer Treatment: Quantifying Non-Medical Economic Consequences for Cancer Survivors Undergoing Systemic and Radiation Therapies

The Invisible Costs of Cancer Treatment: Quantifying Non-Medical Economic Consequences for Cancer Survivors Undergoing Systemic and Radiation Therapies

Background: The non-medical economic consequences of cancer on individuals and families in low- and middle-income countries, including Bangladesh, remain poorly quantified. This study measures the non-medical economic consequences of cancer survivors and their families, including sacrifices in essential family consumption, social participation and family members' schooling.
Methods: We conducted a cross-sectional survey between January and May 2022, involving 607 adult patients receiving cancer treatment at two tertiary specialised cancer hospitals in Bangladesh. Participants reported any occurrence of non-medical economic consequences: reduction in essential goods (REG) consumption, avoidance of social events (ASE) and cessation of schooling (CS) of family members. We used a multivariable logistic regression model to assess the associations between each non-medical economic consequence and clinical and socioeconomic factors. Additionally, we fitted a Poisson regression to model the count of non-medical economic consequence events as a function of disease stage and relevant covariates.
Results: Overall, 39% of patients reported REG, 36% ASE, and 38% CS. After adjusting for co-variates, advanced cancer (stage IV) was a significant predictor of non-medical economic consequence (REG: OR = 5.58, 95% CI 0.99–31.44, p = 0.051; ASE: 11.35, 1.81–71.07, p = 0.009; SS: 101.56, 2.47–4173.90, p = 0.015) compared with early cancer (stage I). Compared with the highest-income families, patients from low- and lower-middle-income families had significantly higher odds of experiencing all outcomes (REG: OR = 7.57, 3.01–19.06, p < 0.001 and 7.23, 1.81–28.89, p = 0.005; ASE: 10.21, 3.81–27.36, p < 0.001 and 17.99, 4.26–75.96, p < 0.001; CS: 11.37, 3.23–40.00, p < 0.001 and 12.58, 1.90–83.19, p = 0.009). Employed patients were also at markedly higher risk, with substantially increased odds of REG (18.27 times), ASE (41.01 times) and CS (72.34 times) compared with non-employed patients (all p < 0.01).
Conclusion: Cancer treatment in Bangladesh imposes substantial and inequitable non-medical economic consequences, disproportionately affecting patients with advanced-stage cancer, lower-income families and those in active employment. Policymakers may prioritise strengthening early cancer detection programs, expanding targeted financial protection schemes and introducing workplace and educational support mechanisms to safeguard family welfare and promote more equitable outcomes during cancer treatment.