Nationwide cost-effectiveness and quality of life analysis of minimally invasive distal pancreatectomy
Bibliographic record
Abstract
BACKGROUND: This study analyzed the Quality of Life (QoL) and cost-effectiveness of laparoscopic (LDP) versus robotic distal pancreatectomy (RDP). METHODS: Consecutive patients submitted to LDP or RDP from 2010 to 2020 in four high-volume Italian centers were included, with a minimum of 12 months of postoperative follow-up were included. QoL was evaluated using the EORTC QLQ-C30 and EQ-5D questionnaires, self-reported by patients. After a propensity score matching, which included BMI, gender, operation time, multiorgan and vascular resections, splenic preservation, and pancreatic stump management, the mean differential cost and Quality-Adjusted Life Years (QALY) were calculated and plotted on a cost-utility plane. RESULTS: The study population consisted of 564 patients. Among these, 271 (49%) patients were submitted to LDP, while 293 (51%) patients to RDP. After propensity score matching, the study population was composed of 159 patients in each group, with a median follow-up of 59 months. As regards the QoL analysis, global health and emotional functioning domains showed better results in the RDP group (p = 0.037 and p = 0.026, respectively), whereas the other did not differ. As expected, the median crude costs analysis confirmed that RDP was more expensive than LDP (16,041 Euros vs. 10,335 Euros, p < 0.001). However, the robotic approach had a higher probability of being more cost-effective than the laparoscopic procedure when a willingness to pay more than 5697 Euros/QALY was accepted. CONCLUSION: RDP was associated with better QoL as explored by specific domains. Crude costs were higher for RDP, and the cost-effectiveness threshold was set at 5697 euros/QALY.
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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 | 0.001 |
| 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".