Use of stents in patients undergoing chemotherapy for borderline resectable pancreatic cancer-causing biliary obstruction while awaiting surgery: A cost-effectiveness analysis
Bibliographic record
Abstract
Abstract Background and study aims Biliary stenting is indicated to relieve obstruction from borderline resectable pancreatic cancer while patients receive preoperative neoadjuvant therapy. We compared the cost-effectiveness of plastic versus metal biliary stenting in this setting. Methods A decision tree analysis compares two competing types of biliary stents (initially metal vs. initially plastic) to treat malignant distal biliary obstruction while receiving neoadjuvant therapy with different scenarios including possible complications as bridge till the patient undergoes curative surgical attempt. Using published information, effectiveness was chosen as the probability of successfully reaching a state of being ready for surgery once chemotherapy was completed. Costs (2018 US$) were based on national data. A third-party payer perspective was adopted, and sensitivity analyses were performed over a time-horizon of one year. Results Initially inserting a metal versus a plastic biliary stent was more efficacious with a higher probability of reaching the readiness for surgery endpoint (96 % vs. 85 %), on average 18 days earlier while also being less expensive (US$ 9,304 vs. US$ 11,538). Sensitivity analyses confirmed robustness of these results across varying probability assumptions of plausible ranges and remained a dominant strategy even when lowering the willingness-to-pay threshold to US$ 1,000. Conclusions Initial metal stenting to relieve malignant biliary obstruction from borderline resectable pancreatic cancer in patients undergoing neoadjuvant therapy prior to surgery is a dominant intervention in economic terms, when compared to initially inserting a plastic biliary stent as it results in a greater proportion of patients being fit for surgery earlier and at a lower cost.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.010 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".