Pasireotide for the Prevention of Pancreatic Fistula Following Pancreaticoduodenectomy
Bibliographic record
Abstract
OBJECTIVE: To determine the cost-effectiveness of perioperative administration of pasireotide for reduction of pancreatic fistula (PF). SUMMARY: PF is a major complication following pancreaticoduodenectomy (PD), associated with significant morbidity and healthcare-related costs. Pasireotide is a novel multireceptor ligand somatostatin analogue, which has been demonstrated to reduce the incidence of PF following pancreas resection; however, the drug cost is significant. This study sought to estimate the cost-effectiveness of routine administration of pasireotide to patients undergoing PD, compared with no intervention from the perspective of the hospital system. METHODS: A decision-analytic model was developed to compare costs for perioperative administration of pasireotide versus no pasireotide. The model was populated using an institutional database containing all PDs performed 2002 to 2012 at a single institution, including data regarding clinically significant PF (International Study Group on Pancreatic Fistula Grade B or C) and hospital-related inpatient costs for 90 days following PD, converted to 2014 $USD. Relative risk of PF associated with pasireotide was estimated from the published literature. Deterministic and probabilistic sensitivity analyses were performed to test robustness of the model. RESULTS: Mean institutional cost of index admissions was $67,417 and $31,950 for patients with and without PF, respectively. Pasireotide was the dominant strategy, associated with savings of $1685, and a mean reduction of 1.5 days length of stay. Univariate sensitivity analyses demonstrated cost-savings down to a PF rate of 5.6%, up to a relative risk of PF of 0.775, and up to a drug cost of $2817. Probabilistic sensitivity analysis showed 79% of simulations were cost saving. CONCLUSIONS: Pasireotide appears to be a cost-saving treatment following PD across a wide variation of clinical and cost scenarios.
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 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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".