Cost-Utility Of Bortezomib In Induction Treatment Prior To Autologous Stem-Cell Transplantation (ASCT) In Previously Untreated Multiple Myeloma Patients In Canada
Bibliographic record
Abstract
Abstract Introduction The effectiveness of bortezomib for induction treatment prior to ASCT in multiple myeloma (MM) patients has been demonstrated in a number of randomized, open-label phase III trials, including the IFM 2005-01 trial (Harousseau et al., J Clin Oncol 2010;28(30):4621-9). This trial showed that the addition of bortezomib as part of an induction treatment prior to ASCT resulted in statistically significant improvements in post-induction response rates and longer progression-free survival (PFS) compared to a non-bortezomib containing regimen (NBCR). The objective of this study was to assess the cost-utility of a bortezomib-containing regimen (BCR) vs. a NBCR for induction treatment in previously untreated MM patients prior to ASCT from a Canadian public payer perspective, based on the results of the IFM 2005-01 study. Methods A Markov model was developed to estimate the cost-utility over a lifetime horizon (50 years) in previously untreated MM patients undergoing induction and ASCT. The model simulated disease progression of patients with previously untreated MM through three health states: “progression-free”, “progression” and “death”, with all patients beginning in the progression-free state. The PFS and overall survival (OS) curves from the IFM 2005-01 trial were extrapolated beyond the study follow-up period to estimate the timeframe spent in each health state. Each health state was associated with a utility value and direct medical costs. Utilities for the progression-free and progression health states were derived from a previous cost-utility analysis for bortezomib and were 0.81 and 0.645, respectively (Hornberger et al., Eur J Haematol 2010;85(6):484-91). Transition probabilities between health states were estimated by calibrating the model to the PFS and OS curves from the IFM 2005-01 trial. In the base case, transition probabilities beyond the trial follow-up period were conservatively assumed to be equal for both treatment groups. Medical resource utilization was estimated using the IFM 2005-01 trial, and supplemented by published literature and clinical advisors. Clinical advisors also provided input on management of adverse events (> grade 3) and treatment of patients who progressed after induction and ASCT. Resource costs were estimated using Canadian sources ($CAN 2012) and costs and outcomes were discounted at 5% annually. Because patients in each group incurred similar costs (i.e. cost of an ASCT), only incremental costs between the two arms were included in the analysis. One-way sensitivity analyses and probabilistic sensitivity analyses were performed to test the robustness of the model. Results The mean total MM-related cost over the lifetime analysis in the model was $68,800 per patient treated with a BCR and $47,000 per patient treated with a NBCR. Addition of bortezomib to the induction regimen increased costs by $21,700 (see table). Over the model lifetime, a delay in progression with a BCR led to 0.25 years of additional survival compared to a NBCR and a quality-adjusted life-year (QALY) gain of 0.22 years. The incremental cost-utility ratio for induction using a BCR compared to a NBCR approach was $99,200/QALY. Sensitivity analyses identified the major factors impacting the cost-utility ratio as: transition probabilities beyond the trial follow-up period, discounting, utilities and bortezomib costs. The probability of a BCR being cost-effective compared to a NBCR was 43.9% at a threshold of $100,000/QALY. Conclusions A number of phase 3 trials have demonstrated the effectiveness of bortezomib as part of an induction regimen prior to ASCT. This analysis indicates that, from a Canadian perspective, induction treatment with a BCR in previously untreated MM patients prior to ASCT can be cost-effective at conventional decision thresholds with a cost-utility ratio of $99,200/QALY. Disclosures: Kouroukis: Janssen Inc.: Honoraria. White:Janssen Inc.: Consultancy, Honoraria. Kruse:OptumInsight: Employment. Lawrence:OptumInsight: Employment. Trambitas:Janssen Inc.: Employment.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".