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Record W4407859078 · doi:10.1007/s40261-025-01426-x

Economic Model of Uridine Triacetate Versus Supportive Care for the Treatment of Patients with Life-Threatening Early-Onset Severe Toxicity

2025· article· en· W4407859078 on OpenAlexaff
Alice Matthews Beers, Paige Reid, Salvatore Miragliotta, Suzanne Ward, Setareh A. Williams, Megan Bourque, Chantal M. Trepanier, Angela Griffin

Bibliographic record

VenueClinical Drug Investigation · 2025
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Treatments and Studies
Canadian institutionsEVERSANA (Canada)
Fundersnot available
KeywordsMedicineToxicityPharmacotherapyIntensive care medicinePediatricsInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Early-onset severe toxicity following the administration of 5-fluorouracil (5-FU) or capecitabine occurs in approximately 10-30% of patients receiving fluoropyrimidine therapy in the USA and is fatal to at least 0.5% of patients treated. Supportive care measures used to manage symptoms of toxicity are associated with extended hospital length of stay, high cost of care, and poor survival. Uridine triacetate is indicated as an emergency treatment for patients who exhibit early-onset, severe or life-threatening toxicity, and has been shown to significantly improve clinical outcomes. Despite its life-saving capability to reverse early-onset severe toxicity, uridine triacetate may be underutilized. PURPOSE: This study aims to evaluate the economic impact of uridine triacetate as a rescue therapy for adult patients from the US hospital payer perspective for early-onset severe toxicity, who are expected to die without treatment. METHODS: A decision tree model was developed to compare inpatient survival, hospital length of stay, and inpatient healthcare resource utilization for patients treated with and without uridine triacetate. Costs associated with hospitalization, including supportive care measures and monitoring were evaluated, considering medications and procedures commonly used to manage various severe toxicities experienced (e.g., gastrointestinal, hematological, etc.). The model compared the hypothetical current practice, in which approximately half of patients expected to die from early-onset severe toxicity receive uridine triacetate in addition to supportive care, with the proposed future practice in which all eligible patients receive uridine triacetate during their hospital stay. Hypothetical practical scenarios for US institutions were also considered. RESULTS: For each adult patient hospitalized for early-onset severe or life-threatening toxicity who would be expected to die without treatment, adoption of uridine triacetate as a rescue treatment was associated with clinical benefits, including increased inpatient survival (48.5%) and a 7.3-day reduction in total hospital length of stay per patient. Treatment of each additional patient with uridine triacetate was associated with an incremental cost of US$25,247 per patient. Seventy percent of the drug cost was offset by reduction in inpatient healthcare resources utilization. This cost offset is likely underestimated as it does not include additional savings from potential reimbursements associated with changes in hospital length of stay, readmissions and discounting. Hypothetical scenarios demonstrated that model outputs were most sensitive to changes in length of stay and hospitalization costs. CONCLUSION: Optimal treatment with uridine triacetate for all hospitalized patients in the USA expected to die from early-onset severe toxicity has the potential to improve inpatient survival at a minimal inpatient budget increase. The majority of the drug cost is offset by a reduction in the length of hospital stay and associated costs.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.305

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 head0.059
GPT teacher head0.348
Teacher spread0.289 · 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 routes1
Has abstractyes

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