The Effect of Celiac Neurolysis and Splanchnicectomy on Survival in Unresectable Pancreatic Cancer: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Intractable pancreatic pain is one of the most common symptoms of patients with pancreatic ductal adenocarcinoma (PDAC). Celiac neurolysis (CN) and splanchnicectomy were already described as effective methods to manage abdominal pain in unresectable PDAC, but their impact on overall survival (OS) has not yet been established. OBJECTIVE: We aimed to investigate the impact of CN and splanchnicectomy on the survival of patients with unresectable pancreatic cancer. METHODS: A systematic review of PubMed and Cochrane Library according to predefined searching terms was conducted in March 2020. Hazard ratios (HR) of OS data were calculated using the Mantel-Haenszel model for random effects or fixed effects. RESULT: Four randomized-controlled trials (RCTs) and 2 non-RCTs with a total of 2,507 patients were identified. The overall pooled HR did not reveal any relevant effect of CN and splanchnicectomy on OS (HR: 1.03; 95% CI: 0.81-1.32), which was also underlined by the sensitivity analysis of RCTs (HR: 1.0; 95% CI: 0.72-1.39) and non-RCTs (HR: 1.07; 95% CI: 0.71-1.63). However, subgroup analyses depending on tumor stage revealed that CN or splanchnicectomy was associated with a worsened OS in AJCC (American Joint Committee on Cancer) stage III patients with unresectable PDAC (HR: 1.22; 95% CI: 1.03-1.45), but nor for AJCC stage IV patients (HR: 1.27; 95% CI: 0.9-1.80). CONCLUSION: Although only few data are currently available, this systematic review with meta-analysis showed that in unresectable PDAC, CN or splanchnicectomy is associated with a worsened survival in stage III PDAC patients, with no effect on stage IV PDAC patients. These data call for caution in the usage of CN or splanchnicectomy in stage III PDAC and for further studies addressing this observation.
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.032 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".