Economic Evaluations of Radioembolization With Itrium-90 Microspheres in Hepatocellular Carcinoma: a Systematic Review
Bibliographic record
Abstract
Abstract Background: Transarterial radioembolization (TARE) with yttrium-90 microspheres is a clinically effective therapy for hepatocellular carcinoma (HCC) treatment. This study aimed to perform a systematic review of the available economic evaluations of TARE for the treatment of HCC.Methods: The Preferred Reported Items for Systematic reviews and Meta-Analyses guidelines was followed by applying a search strategy across six databases. All studies identified as economic evaluations with TARE for HCC treatment in English or Spanish language were considered. Conversions were performed using 2020 purchasing-power-parity ($US PPP).Results: Among 423 records screened, 20 studies (6 cost-analyses, 3 budget-impact-analyses, 2 cost-effectiveness-analyses, 8 cost-utility-analyses, and 1 cost-minimization analysis) were finally included (13 European, 6 USA and 1 Canadian). The assessed populations included early- (n=4), and intermediate-advanced-stages patients (n=15). Included studies were evaluated from a payer perspective (n=20) and included both payer and social perspective (n=2). TARE was compared with transarterial chemoembolization (TACE) (n=9) or sorafenib (n=11). Life-years gained for TARE ranged from 1.3 to 3.1 vs. TACE and from 1.1 to 2.53 for TARE vs. sorafenib. TARE was associated with lower treatment cost in ten studies. TARE cost varied widely according to Barcelona Clinic Liver Cancer (BCLC) staging system and ranged from 1,311 PPP/month (BCLC-A) to 71,890 PPP/horizon time 5 years (BCLC-C). The incremental cost-utility ratio for TARE vs TACE resulted in a $PPP 17,397/Quality-adjusted-Life-Years (QALY) (n=1) and for TARE vs. sorafenib ranged from dominant (more effectiveness and lower cost) to 3,363 PPP/QALY.Conclusions: Economic evaluations of TARE for HCC treatment are heterogeneous. Overall, TARE is a cost-effective short- and long-term therapy for the treatment of intermediate-advanced HCC.
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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 | 0.011 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.014 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".