Cost-effectiveness analysis of transarterial chemoembolization combined with stereotactic body radiation therapy versus transarterial chemoembolization for inoperable hepatocellular carcinoma: A markov modelling study
Bibliographic record
Abstract
Abstract Background Transarterial chemoembolization (TACE) and Stereotactic body radiation therapy (SBRT) might both provide survival benefits for inoperable hepatocellular carcinoma (HCC). Adopting combined therapy as a solution carries major cost and resource implications. We aimed to estimate the cost-effectiveness of TACE plus SBRT and TACE alone in inoperable HCC. Methods A Markov model was constructed in a hypothetical cohort of patients aged 60 years with inoperable HCC and Child-Pugh A/B cirrhosis over a lifetime frame. Two strategies (TACE plus SBRT and TACE) were compared. Transition probabilities, utility and costs were extracted from published literature. Incremental cost-effectiveness ratios (ICER) were measured. Deterministic and probabilistic sensitivity analyses were conducted to assess the robustness of the findings. Results TACE plus SBRT and TACE respectively produced 12.26 and 9.67 quality-adjusted life years (QALYs). The ICER of TACE plus SBRT versus TACE was $3,133/QALY. One-way sensitivity analysis revealed that the utility of TACE combined with SBRT progress survival, probability of death from progress survival in TACE, and the initial cost of TACE combined with SBRT were the most sensitive parameters. The Monte-Carlo simulation demonstrated that the probability of cost-effectiveness at a willingness to pay threshold of US$ 29,440 per QALY was 95% and 5% for TACE plus SBRT and TACE. Conclusions This study indicated that TACE plus SBRT is cost-effective compared to TACE for inoperable HCC patients at a willingness to pay threshold as defined by WHO guidelines in China.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".