Positron Emission Tomography–Computed Tomography (PET-CT) Versus No PET-CT in the Management of Potentially Resectable Colorectal Cancer Liver Metastases: Cost Implications of a Randomized Controlled Trial
Bibliographic record
Abstract
PURPOSE: To evaluate whether positron emission tomography (PET) combined with computed tomography (PET-CT) is cost saving, or cost neutral, compared with conventional imaging in management of patients with resectable colorectal cancer liver metastases. METHODS: Cost evaluation of a randomized trial that compared the effect of PET-CT on surgical management of patients with resectable colorectal cancer liver metastases. Health care use data ≤ 1 year after random assignment was obtained from administrative databases. Cost analysis was undertaken from the perspective of a third-party payer (ie, Ministry of Health). Mean costs with 95% credible intervals (CrI) were estimated by using a Bayesian approach. RESULTS: The estimated mean cost per patient in the 263 patients who underwent PET-CT was $45,454 CAD (range, $1,340 to $181,420) and in the 134 control patients, $40,859 CAD (range, $279 to $293,558), with a net difference of $4,327 CAD (95% CrI, -$2,207 to $10,614). The primary cost driver was hospitalization for liver surgery (difference of $2,997 CAD for PET-CT; 95% CrI, -$2,144 to $8,010), which was mainly a result of a longer length of hospital stay for the PET-CT arm (median, 7 v 6 days; P = .03) and a higher postoperative complication rate (20% v 10%; P = .01). Baseline characteristics were similar between groups, including the number of liver segments involved with cancer, number of segments resected, and type of liver resection performed. No difference in survival was detected between arms. CONCLUSION: PET-CT was associated with limited clinical benefit and a nonsignificant increased cost. Universal funding of PET-CT in the management of patients with resectable colorectal cancer liver metastases does not seem justified.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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".