Cost-Effectiveness of Acthar Gel Versus Standard of Care for the Treatment of Exacerbations in Moderate-to-Severe Systemic Lupus Erythematosus
Bibliographic record
Abstract
INTRODUCTION: Gel (repository corticotropin injection) versus SoC treatment in patients with active, moderate-to-severe SLE from the US payer and societal perspectives over 2 and 3 years. METHODS: Cost-effectiveness model was developed using a probabilistic cohort-level state-transition approach. Patients received Acthar Gel in an exacerbation state, and the outcomes were assessed at the end of a 3-month cycle for response achievement based on the probability of treatment success with Acthar Gel. Patients may sustain the response or experience an exacerbation. For the base case scenario, moderate-to-severe SLE was defined as British Isles Lupus Assessment Group (BILAG)-2004 ≥ 20 or SLE Disease Activity Index 2000 (SLEDAI-2K) ≥ 10 and clinical response was based on SLE responder index (SRI)-4. Clinical response, productivity loss, and utility were derived from a phase 4 SLE trial; cost and disutility estimates were sourced from the literature. RESULTS: From a payer perspective, Acthar Gel versus SoC resulted in an incremental cost-effectiveness ratio (ICER) of $133,110 per quality-adjusted life-year (QALY) and $94,818 per QALY over 2 and 3 years, respectively. From a societal perspective, Acthar Gel versus SoC results in an ICER of $70,827 per QALY and $32,525 per QALY over 2 and 3 years, respectively. Results from the sensitivity and scenario analyses are consistent with those of the base case model. CONCLUSIONS: Acthar Gel is a cost-effective, value-based treatment option for appropriate patients with moderate-to-severe SLE at a willingness-to-pay threshold of $150,000 over 2-3 years from the US payer and societal perspectives. Acthar Gel results in the reduction of direct medical and indirect 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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".