Cost of treatment for breast cancer in central Vietnam
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: In recent years, cases of breast cancer have been on the rise in Vietnam. To date, there has been no study on the financial burden of the disease. This study estimates the direct medical cost of a 5-year treatment course for women with primary breast cancer in central Vietnam. METHODS: Retrospective patient-level data from medical records at the Hue Central Hospital between 2001 and 2006 were analyzed. Cost analysis was conducted from the health care payers' perspective. Various direct medical cost categories were computed for a 5-year treatment course for patients with breast cancer. Costs, in US dollars, discounted at a 3% rate, were converted to 2010 after adjusting for inflation. For each cost category, the mean, standard deviation, median, and cost range were estimated. Median regression was used to investigate the relationship between costs and the stage, age at diagnosis, and the health insurance coverage of the patients. RESULTS: The total direct medical cost for a 5-year treatment course for breast cancer in central Vietnam was estimated at $975 per patient (range: $11.7-$3,955). The initial treatment cost, particularly the cost of chemotherapy, was found to account for the greatest proportion of total costs (64.9%). Among the patient characteristics studied, stage at diagnosis was significantly associated with total treatment costs. Patients at later stages of breast cancer did not differ significantly in their total costs from those at earlier stages however, but their survival time was much shorter. The absence of health insurance was the main factor limiting service uptake. CONCLUSION: From the health care payers' perspective, the Government subsidization of public hospital charges lowered the direct medical costs of a 5-year treatment course for primary breast cancer in central Vietnam. However, the long treatment course was significantly influenced by out-of-pocket payments for patients without health insurance.
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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) | 0.000 | 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