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Record W4416697794 · doi:10.1080/13696998.2025.2587415

Quantifying treatment value under IRA: a case study of rifaximin for the treatment of overt hepatic encephalopathy using QALY and non-QALY measures

2025· article· en· W4416697794 on OpenAlexafffund
Shanshan Wang, Leonardo Passos Chaves, Olamide Olujohungbe, Aditi Chaudhary, Jason Shafrin

Bibliographic record

VenueJournal of Medical Economics · 2025
Typearticle
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsBausch Health (Canada)
FundersBausch Health
KeywordsRifaximinHepatic encephalopathyValue (mathematics)Symptomatic treatmentEncephalopathy

Abstract

fetched live from OpenAlex

BACKGROUND: Traditional cost effectiveness analyses frequently use quality-adjusted life years (QALYs) to quantify health benefits. The Medicare Drug Price Negotiation program, however, cannot use QALYs, but may consider alternative, non-discriminatory metrics. OBJECTIVE: To examine the impact of using alternative quantitative health benefit metrics on the economic value of new medications. The framework was applied to assess the cost-effectiveness of rifaximin for preventing overt hepatic encephalopathy (OHE) recurrence in adults. METHODS: A cost-effectiveness analysis evaluated the economic value of rifaximin ± lactulose versus standard of care ± lactulose in preventing recurrent OHE in adults over a lifetime horizon from US payer and societal perspectives. Clinical outcomes included time in remission and overt health states, number of liver transplants, and life years (LYs). Health benefit was quantified using QALYs, health years in total (HYT), equal-value of life years gained (evLYG), and generalized risk-adjusted cost-effectiveness (GRACE). Treatment value was measured using incremental cost effectiveness ratio (ICER). A societal perspective scenario added productivity and caregiving impacts to the model. RESULTS: Rifaximin patients spent >3 times as long in remission (54.4 vs. 17.3 months), comparable time in the overt health state (1.44 vs. 1.44 months), and had twice as many liver transplants (20 vs. 9), driven by longer survival (8.80 vs. 4.17 LYs), resulting in incremental gains of 3.12 QALYs, 3.26 HYT, 2.78 evLYG, and 3.16 GRA-QALYs. Total costs were higher with rifaximin ($182,369 vs. $38,313, Δ = $144,056), mainly due to drug costs (Δ = $133,330). Including caregiving and productivity reduced the incremental cost to $136,866. From a payer perspective, rifaximin ICERs were $46,215/QALY, $44,198/HYT, $51,847/evLYG, and $45,609/GRA-QALY. After incorporating societal costs, ICERs improved to $43,908/QALY, $41,992/HYT, $49,259/evLYG, and $43,332/GRA-QALY. CONCLUSION: Rifaximin is a cost-effective treatment for preventing OHE recurrence in adults using QALY and non-QALY health benefit measures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.086
GPT teacher head0.363
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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