A cost-utility analysis of combined durvalumab and tremelimumab in patients with refractory metastatic colorectal cancer (mCRC) and high plasma tumour mutation burden (pTMB): A Canadian Cancer Trials Group (CCTG) study.
Bibliographic record
Abstract
e15581 Background: The randomized phase II CCTG CO.26 clinical trial investigated the use of combined durvalumab and tremelimumab vs. best supportive care (BSC) for patients with mCRC and suggested an increase in overall survival (OS). The largest benefit was seen in patients who were microsatellite stable (MSS) with a pTMB ≥ 28 variants per megabase. Considering significantly higher adverse event rates and costs associated with durvalumab and tremelimumab, it is important to evaluate its cost-effectiveness. Accordingly, we performed a cost-utility analysis of durvalumab and tremelimumab compared to BSC in the intention-to-treat (ITT) and biomarker-enriched populations using CO.26 trial data. Methods: We developed a 4-state microsimulation model to evaluate the expected health outcomes in life-years (LYs), quality-adjusted life-years (QALYs) and costs of the treatment group compared to BSC over a lifetime horizon (5 years). The incremental cost-utility ratio (ICUR) was used to compare treatment strategies. Direct trial data from CO.26 were used to inform model inputs, including OS curves, progression-free survival (PFS) curves, and adverse event rates. As health state utilities were not collected in CO.26, values from the CORRECT trial, a multi-centre randomized placebo-controlled phase III study for regorafenib in mCRC, were used. Costs of therapy, hospitalization due to adverse events, end-of-life care, and physician costs were derived from the literature and publicly available sources (in 2020 Canadian dollars). Since the monthly price of tremelimumab was unavailable, it was approximated with the price of another CTLA-4 inhibitor, ipilimumab. The base-case analysis evaluated these treatment strategies in the ITT population. Scenario analyses evaluated the cost-effectiveness in biomarker-enriched populations. Costs and effects were discounted at 1.5% as per Canadian guidelines. Results: In the base-case, expected LYs for combined durvalumab and tremelimumab and BSC were 0.75 and 0.51 (incremental (Δ) 0.24) respectively. Expected QALYs were 0.47 and 0.33 (Δ 0.14). Expected lifetime costs were $60 500 and $15 500 (Δ $45 000) for an ICUR of $320 000/QALY. In the biomarker-enriched subgroup, the expected LYs were 0.67 and 0.33 (Δ 0.34), expected QALYs were 0.43 and 0.22 (Δ 0.21), and expected lifetime costs were $62 000 and $15 200 (Δ $47 000). This represents an increase in the incremental QALYs by 50% and costs by 5% for an ICUR 30% lower than the base case at $220 000/QALY. Conclusions: Combined durvalumab and tremelimumab is not considered cost-effective in refractory mCRC under conventional willingness-to-pay thresholds. Cost-effectiveness is improved with biomarker enrichment for high pTMB, driven by the greater derived health outcomes in this subgroup.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".