Neoadjuvant Treatment versus Upfront Surgery for Primary Resectable Pancreatic Cancer: An Update Meta-Analysis of Comparative Studies
Bibliographic record
Abstract
Abstract Background The role of neoadjuvant chemotherapy with or without radiotherapy in resectable pancreatic cancer has yet to be defined. Aims This meta-analysis aims to explore the benefit of a neoadjuvant treatment in resectable pancreatic cancer compared with upfront surgery in terms of overall survival. Methods MEDLINE, Embase and the Cochrane Library were searched for studies reporting median overall survival by intention to treat in patients with primary resectable pancreatic cancer treated with or without neoadjuvant treatment from January 2000 to December 2022. The quality assessment of the included studies was based on the Newcastle–Ottawa quality scale. Secondary outcomes included disease free survival, pathological lymph-node rate, overall and R0 resection rate. Results A total of eleven studies (seven randomized controlled trials and four cohort studies) with 9774 patients were included. Neoadjuvant treatment was found to be significantly associated to increased overall survival (p<0.001; OR: 0.82; 95% CI: 0.73–0.92) and disease-free survival (p<0.001; OR: 0.73; 95% CI: 0.59–0.89). The association of radiotherapy showed no additional benefit to chemotherapy alone in terms of overall survival in the subgroup analysis. Patients undergoing neo-adjuvant treatment were also found to be significantly associated with a higher R0 resection rate (p<0.001; OR: 1.67; 95% CI: 1.31–2.15) and negative lymph-node status (p<0.001; OR: 0.41; 95% CI: 0.26–0.64). Conclusions Neoadjuvant treatment seems to offer an advantage in terms of overall and disease-free survival in comparison to patients undergoing up-front surgery for primary resectable pancreatic cancer. Further RCTs should confirm these findings to generalize the indication of neoadjuvant treatment in this setting.
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 | 0.026 | 0.053 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.052 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".