Clinical and economic benefits of lenzilumab plus standard of care compared with standard of care alone for the treatment of hospitalized patients with COVID-19 in the United States from the hospital perspective
Bibliographic record
Abstract
AIMS: Estimate the clinical and economic benefits of lenzilumab plus standard of care (SOC) compared with SOC alone in the treatment of patients hospitalized with COVID-19 pneumonia from the United States (US) hospital perspective. MATERIALS AND METHODS: A per-patient cost calculator was developed to report the clinical and economic benefits associated with adding lenzilumab to SOC in newly hospitalized COVID-19 patients over 28 days. Clinical inputs were based on the LIVE-AIR trial, including failure to achieve survival without ventilation (SWOV), mortality, time to recovery, intensive care unit (ICU) admission, and invasive mechanical ventilation (IMV) use. Base case costs included the anticipated list price of lenzilumab, drug administration, and hospital resource costs based on the level of care required. A scenario analysis examined projected one-year rehospitalization costs. RESULTS: In the base case and all scenarios, lenzilumab plus SOC improved all specified clinical outcomes relative to SOC alone. Lenzilumab plus SOC resulted in estimated cost savings of $3,190 per patient in a population aged <85 years with C-reactive protein (CRP) levels <150 mg/L and receiving remdesivir (base case). Per-patient cost savings were observed in the following scenarios: (1) aged <85 years with CRP <150 mg/L, with or without remdesivir ($1,858); (2) Black and African American patients with CRP <150 mg/L ($13,154); and (3) Black and African American patients from the full population, regardless of CRP level ($2,763). In the full modified intent-to-treat population, an additional cost of $4,952 per patient was estimated. When adding rehospitalization costs to the index hospitalization, a total per-patient cost savings of $5,154 was estimated. CONCLUSIONS: The results highlight the clinical benefits for SWOV, ventilator use, time to recovery, mortality, time in ICU, and time on IMV, in addition to an economic benefit from the US hospital perspective associated with adding lenzilumab to SOC for COVID-19 patients.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".