ArticleFrontiers in surgery2025
SEER-based hypothesis-generating research for minimum lymph node evaluation in early-stage pancreatic ductal adenocarcinoma patients.
Article in Frontiers in surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Invasive ductal carcinoma of the pancreas (IDCP) is one of the most lethal of all solid cancers, with regional lymph nodes contributing to recurrent IDCP. Given the dismal prognosis of IDCP, the number of ELNs plays a vital role in patient prognosis. However, the optimal number of examined lymph nodes (ELNs) for stage I and II IDCP patients has not been defined by the 7th and 8th editions of the American Joint Committee on Cancer. Methods: All patients diagnosed with invasive ductal carcinoma pancreatic cancer were identified from the Surveillance, Epidemiology, and End Results (SEER) database (http://seer.cancer.gov/) using SEER*Stat Software (version 8.3.9.2). The minimum number of ELNs or ELN/regional nodes positive (RNP) ratio threshold for optimal survival of IDCP patients was calculated using the R packages "survminer" and "survival" and propensity score matching. Subgroup survival analysis based on the best cut-off values for ELNs was assessed for the following groups: age >69 years, age ≤69 years, female, male, N0, N1, T3, and stage I or II. We used a machine learning model (XGboost) to demonstrate that ELNs are the most significant prognostic factor in patients with IDCP. We also demonstrated significant prognostic effects and predictive models for the truncated values of ELNs using multivariate Cox regression. Finally, we assessed the correlation between ELN/RNP ratio and IDCP mortality using restricted cubic spline. Results: The present study demonstrates the following points: (1) ELNs are some of the most important factors affecting the prognosis of stage I and II IDCP patients. (2) The minimum cut-off value for stage I and II IDCP patients to achieve the best survival is ELNs ≥10, which is more suitable for surgical treatment options for stage II IDCP patients. (3) The optimal threshold of survival benefit for T3N1M0 patients is ELNs >12, with ELNs >7 for T3N0M0 patients. (4) Taking into consideration the effect of the number of RNP on the value of ELNs, the ELN/RNP ratio of 9 is the minimum threshold for optimal survival benefit in stage I or II IDCP patients. Conclusion: The minimum threshold for optimal survival of stage I or II IDCP patients in ELNs ≥10 and ELN/RNP ratio = 9, which is more appropriate for stage II IDCP patients. The optimal threshold of survival benefit for T3N1M0 patients is ELNs >12, with ELNs >7 for T3N0M0 patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.