Cost-effectiveness of precision molecular diagnostic tests for stage II colorectal cancer
Bibliographic record
Abstract
Background: In colorectal cancer, inappropriate use of adjuvant chemotherapies may lead to significant increases in healthcare costs and harms to patients. Genome-based interventions are being increasingly used in the stratification of patients according to their risk profiles. However, earlier cost-effectiveness analyses of precision molecular diagnostics have indicated a paucity of data on comparative health economic outcomes. Our aim was to compare the cost-effectiveness of marketed genomic tests used in the prognosis of stage II colorectal cancer patients. Methods: A Markov model was developed to compare the cost-effectiveness of treatment guided by any one of the following genomic tests: 12-gene assay or the 18-gene expression assay or the 482-gene signature or the Immunoscore assay in a hypothetical cohort of patients (n=1,000) with stage II colorectal cancer. Our study investigated outcomes in three health states: no recurrence, recurrence and death. This study was conducted from a societal perspective, and a 3% discount was applied to the costs and health outcomes. Sensitivity analyses were performed to assess the uncertainty of model parameters on the results. Results: The cost of the Immunoscore assay strategy in stage II colorectal cancer patients was estimated to be US $23,564 with a gain of 3.903 quality-adjusted life years (QALYs) as compared with the 12-gene assay strategy at US $24,545 and 3.903 QALYs; the 18-gene assay strategy at US $28,374 and 3.623 QALYs; and the 482-gene signature treatment strategy at US $33,315 with 3.704 QALYs. Sensitivity analyses indicated that incremental cost-effectiveness ratio (ICER) values were sensitive to costs of genomic tests and adjuvant chemotherapies; and utilities related to patients in the no-recurrence health state. Conclusions: Overall, the Immunoscore assay seems to be a dominant strategy at a threshold willingness-to-pay of $50,000 per QALY, but in the US other tests have been used for longer. Thus, the 12-gene assay may generate cost savings compared to the 18-gene expression assay. The findings of our study may provide useful information to policymakers regarding selection of the most appropriate genomic test, and resource allocation decisions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".