A Canadian Cost-Utility Analysis of Epcoritamab Versus Current Therapies in Third-Line or Later Large B-Cell Lymphoma
Bibliographic record
Abstract
Background: Patients with third-line or later (3L+) large B-cell lymphoma (LBCL) face a dismal prognosis, with high rates of refractory disease. Rituximab-based chemoimmunotherapy (R-CIT), or targeted therapies approved in Canada (polatuzumab vedotin + bendamustine + rituximab [pola-BR], and tafasitamab + lenalidomide [tafa-len]) present significant limitations in terms of clinical outcomes, with low overall survival and high toxicity. Although chimeric antigen T-cell (CAR-T) therapies are now approved and funded in Canada, not all patients are eligible for CAR-T, and even eligible patients face access barriers due to the intensive monitoring and complex processes required. This analysis examines the subcutaneous bispecific antibody epcoritamab for patients who are unable to receive (whether due to clinical ineligibility or other reasons, such as access barriers or patient preference) or have previously received CAR-T in the Canadian 3L+ LBCL treatment setting, from a public payer perspective. Methods: A cost-utility partitioned survival model was developed to follow 3L+ LBCL patients over a lifetime. Epcoritamab efficacy was based on extrapolations of Kaplan-Meier data from the pivotal phase 1/2 EPCORE NHL-1 (NCT03625037) study, while comparator efficacy was informed by matching-adjusted indirect comparisons (MAICs) in three key populations: the overall intention-to-treat (ITT) 3L+ LBCL population (base case scenario, n=157), and two subgroups consisting of patients with no prior CAR-T (Key Scenario 1 [n=96]; including both CAR-T eligible and ineligible patients), and CAR-T eligible patients with no prior CAR-T (Key Scenario 2 [n=57]). Comparator selection in each population was based on the availability of comparative data to be used in MAIC analyses. In the base case, available comparators were pola-BR, glofitamab, and tafa-len; in Key Scenario 1, available comparators were R-CIT, pola-BR, and CAR-T therapies. In Key Scenario 2, the available comparators were CAR-T therapies. Comparison to pola-BR was performed using two different data sources, based on data availability. In the base case (ITT) population, the only available dataset for comparison to pola-BR was an observational real-world dataset (Liebers et al, Blood Adv 2021), while imputed data from a randomized control trial (EUnetHTA PTJA06, 2020) was used to inform the comparison to pola-BR in Key Scenario 1. Costs were reported in 2023 Canadian dollars, and were based on Canadian governmental resources, health technology assessments, and published literature. Utilities were derived from the NHL-1 study. The base case was probabilistic (n=1000 simulations); multiple sensitivity and scenario analyses were performed to assess model uncertainty. Results: At a traditional willingness to pay threshold of $50,000 per quality-adjusted life year (QALY), epcoritamab was cost-effective as compared to R-CIT, pola-BR, tafa-len, and the bispecific antibody glofitamab. In the base case, epcoritamab exhibited incremental cost-utility ratios (ICURs) of $12,200/QALY, $4,917/QALY, and $36,166/QALY versus pola-BR, tafa-len, and glofitamab respectively; in Key Scenario 1, epcoritamab had ICURs of $37,794/QALY and $44,963/QALY versus R-CIT and pola-BR respectively. These results were consistent across multiple sensitivity analyses, the majority of which produced an ICUR less than $50,000/QALY. Similarly, epcoritamab was consistently dominant or cost-saving versus CAR-T therapies in Key Scenarios 1 and 2, irrespective of variation in scenario inputs. In all three populations assessed in this analysis, epcoritamab was shown to be cost-effective at a threshold of $50,000/QALY as per the cost-effectiveness acceptability curve in Canada. Conclusion: Epcoritamab is a consistently cost-effective (as compared to R-CIT, pola-BR, tafa-len, or glofitamab) or dominant/cost-saving (versus CAR-T) option in the high-risk, difficult-to-treat 3L+ LBCL setting, demonstrating its economic value to the healthcare system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".