Outcomes of Neoadjuvant Chemotherapy for Invasive Intraductal Papillary Mucinous Neoplasm Compared with de Novo Pancreatic Adenocarcinoma
Bibliographic record
Abstract
BACKGROUND: The management of invasive intraductal papillary mucinous cystic neoplasm (I-IPMN) does not differ from de novo pancreatic ductal adenocarcinoma (PDAC); however, I-IPMNs are debated to have better prognosis. Despite being managed similarly to PDAC, no data are available on the response of I-IPMN to neoadjuvant chemotherapy. METHODS: All patients undergoing pancreatic resection for a pancreatic adenocarcinoma from 2011 to 2022 were included. The PDAC and I-IPMN cohorts were compared to evaluate response to neoadjuvant therapy (NAT) and overall survival (OS). RESULTS: This study included 1052 PDAC patients and 105 I-IPMN patients. NAT was performed in 25% of I-IPMN patients and 65% of PDAC patients. I-IPMN showed a similar pattern of pathological response to NAT compared with PDAC (p = 0.231). Furthermore, positron emission tomography (PET) response (71% vs. 61%; p = 0.447), CA19.9 normalization (85% vs. 76%, p = 0.290), and radiological response (32% vs. 37%, p = 0.628) were comparable between I-IPMN and PDAC. A significantly higher OS and disease-free survival (DFS) of I-IPMN was denoted by Kaplan-Meier analysis, with a p-value of < 0.001 in both plots. In a multivariate analysis, I-IPMN histology was independently associated with lower risk of recurrence and death. CONCLUSIONS: I-IPMN patients have a longer OS and DFS after surgical treatment when compared with PDAC patients. The more favorable oncologic outcome of I-IPMNs does not seem to be related to early detection, as I-IPMN histological subclass is independently associated with a lower risk of disease recurrence. Moreover, neoadjuvant effect on I-IPMN was non-inferior to PDAC in terms of pathological, CA19.9, PET, and radiological response and thus can be considered in selected patients.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".