Clinical Effectiveness and Cost-Effectiveness of Multigene Panel Sequencing in Advanced Melanoma: A Population-Level Real-World Target Trial Emulation
Bibliographic record
Abstract
PURPOSE Targeted therapy and immunotherapy promise improved survival in patients with advanced melanoma, yet the effectiveness and cost-effectiveness of multigene panel sequencing compared with single-gene BRAF testing to guide therapeutic decisions is unknown. METHODS Our population-based quasi-experimental retrospective target trial emulation used comprehensive patient-level data for 364 British Columbia, Canada, adults with an advanced melanoma diagnosis receiving multigene panel sequencing or single-gene BRAF testing between September 1, 2016, and December 31, 2018. We 1:1 matched multigene panel patients to controls using genetic algorithm–based matching. Outcomes included 3-year overall survival (OS) and health care costs (2021 Canadian dollars [CAD]) with incremental net monetary benefit for life-years gained (LYG). Outcomes were analyzed using inverse probability of censoring weighted linear regression for the intention-to-treat (ITT) effect. The per-protocol (PP) effect estimation also included stabilized inverse probability of treatment weights. We then used Weibull regression and Kaplan-Meier survival analysis. RESULTS We matched 147 multigene panel patients to controls, achieving balance for all covariates. After matching, ITT incremental costs were $19,447 CAD (95% CI, -$19,045 to $50,683) and incremental LYG were 0.22 (95% CI, –0.05 to 0.49). We found uncertainty in differences on OS using Kaplan-Meier ( P = .11) and Weibull regression (hazard ratio [HR], 0.73 [95% CI, 0.51 to 1.03]) in the ITT. PP incremental costs were $25,457 CAD (95% CI, –$5,856 to $59,490) and incremental LYG were 0.39 (95% CI, 0.02 to 0.85), with corresponding differences in OS using Kaplan-Meier ( P = .06) and Weibull regression (HR, 0.62 [95% CI, 0.40 to 0.97]). The probability of multigene panels being cost-effective at $100,000/LYG CAD was 53% for ITT and 74% for PP. CONCLUSION The cost-effectiveness of multigene panels was evenly poised at higher thresholds, even when accounting for treatment initiation. Health systems reimbursing multigene panels and expensive therapies may be confronted with a value tradeoff, in which there may be improved survival albeit with a modest change in cost-effectiveness.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".