Economic burden of breast, cervical, and oral cancer in Bangladesh: a cost-of-illness study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Breast, cervical, and oral cancers are leading causes of morbidity and mortality in Bangladesh, placing a heavy economic burden on households and the health system. Yet, this burden remains poorly understood, as no prior study has comprehensively examined their economic impact. Moreover, the profound psychological suffering experienced by patients are often overlooked in existing global evidence. Therefore, this study aims to estimate the comprehensive economic burden of breast, cervical, and oral cancers in Bangladesh from the household perspective. METHODS: Using a cross-sectional design, primary data were collected through structured interviews with 346 cancer patients. A cost-of-illness approach was employed. Direct medical and direct non-medical costs were estimated based on respondent-reported expenditures. Indirect costs, i.e.income loss, were calculated using the human capital approach. Intangible costs, reflecting pain and discomfort, were quantified using the willingness-to-pay method. RESULTS: The average total cost per patient was US$12,117, with breast cancer accounting for the highest burden. Intangible costs comprised 47.7 % of the total, underscoring the substantial psychological impact of cancer on patients. The combined national economic burden exceeded US$1.17 billion. Catastrophic health expenditure was nearly universal (99.1 %), with average treatment costs exceeding the catastrophic threshold by 44-fold. Expenditures were significantly higher among wealthier households, patients with longer disease duration, and those seeking care from multiple facilities. CONCLUSION: Breast, cervical, and oral cancers impose a major financial and psychological burden on households in Bangladesh. The near-universal catastrophic health expenditure and high intangible costs highlight the urgent need for accessible and affordable cancer care. POLICY SUMMARY: Policies should strengthen financial protection, decentralize diagnosis and treatment, introduce insurance with cancer-specific benefits, establish an effective referral system, integrate psychosocial support and strengthen early detection programs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it