Incremental Effectiveness of Iptacopan Compared with C5 Inhibitors in Adult Patients with Paroxysmal Nocturnal Hemoglobinuria: Results from a Modelling Analysis
Bibliographic record
Abstract
Objective Intravenous infusion complement-5 inhibitors (C5i; eculizumab, ravulizumab) have been the primary therapies for patients with paroxysmal nocturnal hemoglobinuria (PNH). New treatments with different mechanisms of action have been approved recently, including iptacopan, a Factor B proximal complement inhibitor that is the first oral monotherapy for the treatment of adult patients with PNH. Health technology assessments (HTA) are regularly conducted to inform decision making regarding the funding or reimbursement of new drugs and often include cost-effectiveness analyses, which compare costs and outcomes (such as effectiveness) of different interventions based on an economic model. Outcomes are expressed in quality-adjusted life years (QALYs) which capture both the quality, and length of life with each intervention. The objective of this analysis was to estimate the incremental effectiveness of iptacopan compared to C5i for the treatment of adult patients with PNH over a lifetime horizon. Methods A semi-Markov cost-effectiveness model was developed with four mutually exclusive health states: ‘No Transfusion and No Anemia’; ‘No Transfusion and Anemia’ (defined as hemoglobin <10 g/dL); ‘Transfusion’; and ‘Death’. Data from two Phase 3 studies of iptacopan were used: APPLY-PNH (NCT04558918) in C5i-experienced patients with persistent anemia (iptacopan vs. C5i) and APPOINT-PNH (NCT04820530) in C5i-naïve patients (single-arm iptacopan trial). Data from a real-world cohort of C5i-treated patients in France and UK (APPEX study; NCT05842486) was also used. Using individual patient-level data from these studies, a regression model was developed to predict the probability of patients transitioning between health states in 4-weekly intervals for each treatment. Quality of life in each health state was incorporated as treatment-specific utility values based on EQ-5D data from APPOINT-PNH and APPLY-PNH. QALYs were calculated by multiplying the proportion of patients in each health state over time by the number of years spent in the respective health state, and the corresponding utility value, and discounted at 3.5% annually. Here we report the overall QALYs associated with each treatment and the difference between them (incremental QALYs) for the C5i-naïve and C5i-experienced populations separately, considered over a lifetime horizon. Results In the C5i-naïve population, at 10 years, a higher proportion of patients treated with iptacopan (95%) were in the ‘No Transfusion and No Anemia’ health state compared to C5i (40%). Less than 1% of patients treated with iptacopan were in the ‘Transfusion’ state compared to 16% of patients treated with C5i. Over a lifetime horizon, this resulted in total QALYs of 17.37 with iptacopan and 14.95 with C5i, with incremental QALYs of 2.42 in favour of iptacopan. Similarly, in the C5i-experienced population with persistent anemia, at 10 years, a higher proportion of patients treated with iptacopan (87%) were in the ‘No Transfusion and No Anemia’ health state compared to C5i (11%). Less than 1% of patients treated with iptacopan were in the ‘Transfusion’ state compared to 41% of patients treated with C5i. Over a lifetime horizon, this resulted in total QALYs of 15.20 with iptacopan and 12.67 with C5i, with incremental QALY of 2.53 in favour of iptacopan. Conclusion In this modelling analysis, iptacopan demonstrated improved effectiveness in terms of more patients achieving freedom from transfusions and anemia, and more QALYs gained, compared to C5i in both C5i-naïve and -experienced patients with PNH. To determine the cost-effectiveness of iptacopan compared to C5i, further consideration of all costs associated with these treatments is required in country-specific analyses aligned with local HTA requirements.
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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 | 0.000 | 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".