Cost-Effectiveness of Adding Cetuximab to Platinum-Based Chemotherapy for First-Line Treatment of Recurrent or Metastatic Head and Neck Cancer
Bibliographic record
Abstract
PURPOSE: To assess the cost effectiveness of adding cetuximab to platinum-based chemotherapy in first-line treatment of patients with recurrent or metastatic head and neck squamous cell carcinoma (HNSCC) from the perspective of the Canadian public healthcare system. METHODS: We developed a Markov state transition model to project the lifetime clinical and economic consequences of recurrent or metastatic HNSCC. Transition probabilities were derived from a phase III trial of cetuximab in patients with recurrent or metastatic HNSCC. Cost estimates were obtained from London Health Sciences Centre and the Ontario Case Costing Initiative, and expressed in 2011 CAD. A three year time horizon was used. Future costs and health benefits were discounted at 5%. RESULTS: In the base case, cetuximab plus platinum-based chemotherapy compared to platinum-based chemotherapy alone led to an increase of 0.093 QALY and an increase in cost of $36,000 per person, resulting in an incremental cost effectiveness ratio (ICER) of $386,000 per QALY gained. The cost effectiveness ratio was most sensitive to the cost per mg of cetuximab and the absolute risk of progression among patients receiving cetuximab. CONCLUSION: The addition of cetuximab to standard platinum-based chemotherapy in first-line treatment of patients with recurrent or metastatic HNSCC has an ICER that exceeds $100,000 per QALY gained. Cetuximab can only be economically attractive in this patient population if the cost of cetuximab is substantially reduced or if future research can identify predictive markers to select patients most likely to benefit from the addition of cetuximab to chemotherapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".