Assessing the Value for Money of Enzyme Replacement Therapy in Gaucher Disease Types 1 and 3b: Can Expanded Coverage Be Justified?
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The Health Intervention and Technology Assessment Program was commissioned to conduct a cost-utility and budget impact analysis of enzyme replacement therapy (ERT) for Gaucher disease types 1 and 3b. The findings from this assessment are to support the decision-making process regarding the potential expansion of ERT coverage within Thailand's public health system. METHODS: The analysis compared the current policy, which provides treatment with imiglucerase only for patients with Gaucher disease type 1, as listed in the National List of Essential Medicine, with a proposed policy that extends coverage to include Gaucher disease types 1 and 3b with either imiglucerase or velaglucerase. Cost-utility analysis of these policy options was performed using decision tree and Markov models over a lifetime horizon from a societal perspective. The financial implications for the relevant budgetary authority over 5 years were estimated. The research methodology adheres rigorously to Thailand's health technology assessment guidelines. RESULTS: The study found that the incremental cost-effectiveness ratios for treating both Gaucher disease types 1 and 3b are 6,769,000 and 9,359,000 baht per quality-adjusted life year (QALY) for imiglucerase and velaglucerase, respectively, which is well beyond Thailand's cost-effectiveness threshold of 160,000 baht per QALY. Such an expansion would incur an additional budgetary burden of approximately 81 million baht for imiglucerase and 138 million baht for velaglucerase. Increasing the rate of hematopoietic stem cell transplantation (HSCT) can improve the cost-effectiveness of the expansion. CONCLUSIONS: The study concludes that expanding ERT with either imiglucerase or velaglucerase to treat both Gaucher disease types 1 and 3b is not cost-effective at current prices in Thailand; however, it could become cost-effective with a reduction of approximately 60% in drug prices or if all eligible patients undergo HSCT.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".