Evidence map›Paper›PMID 41239488›Full record

ArticleBMC surgery2025

Identification of prognostic indicators for early recurrence of gastric cancer following laparoscopic gastrectomy.

Mingze Wu, Ningbo Liu, Shilong Li, Bang Liu, Zexuan Shen, Hengbin Zhao, Guozheng Ding, Weihua Fu

Abstract read
In one paragraph

Article in BMC 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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Mingze Wu *Department of General surgery, Tianjin Medical University General Hospital, 154 Anshan Road, Tianjin, 300052, People's Republic of China.
Ningbo Liu *Department of Gastrointestinal surgery, Handan First Hospital, Handan, Hebei, People's Republic of China.
Shilong LiDepartment of General surgery, Tianjin Medical University General Hospital, 154 Anshan Road, Tianjin, 300052, People's Republic of China.
Bang LiuDepartment of General surgery, Tianjin Medical University General Hospital, 154 Anshan Road, Tianjin, 300052, People's Republic of China.
Zexuan ShenDepartment of General surgery, Tianjin Medical University General Hospital, 154 Anshan Road, Tianjin, 300052, People's Republic of China.
Hengbin ZhaoDepartment of General surgery, Tianjin Medical University General Hospital, 154 Anshan Road, Tianjin, 300052, People's Republic of China.
Guozheng DingDepartment of General surgery, Tianjin Medical University General Hospital, 154 Anshan Road, Tianjin, 300052, People's Republic of China.
Weihua FuDepartment of General surgery, Tianjin Medical University General Hospital, 154 Anshan Road, Tianjin, 300052, People's Republic of China. tjmughgs_fwh@163.com.ORCID http://orcid.org/0000-0003-2576-865X

Funding

Beijing-Tianjin-Hebei Region of Natural Science Foundation of Tianjin 22JCZXJC00140Tianjin Health and Science and Technology Project-Clinical Key Specialty TJWJ2024ZK001Tianjin Science and technology planning project 21ZXJBSY00110
6 · The paper itself

Abstract

backgroundThe postoperative recurrence of gastric cancer, especially early recurrence, significantly impacts the prognosis of patients. We aimed to identify factors affecting patient post-recurrence survival and identify patients who would experience early postoperative recurrence, facilitating prompt preoperative intervention.

methodsClinical and pathological data from 295 gastric cancer patients who underwent gastrectomy and D2 lymphadenectomy were retrospectively analyzed. The classification of tumor and nodal status was updated on the basis of the 8th edition of the American Joint Committee on Cancer's tumor-node-metastasis (TNM) system for gastric cancer. Survival data were acquired from medical records and follow-up phone calls. Recurrence was diagnosed based on radiological imaging, endoscopic biopsy, and intraoperative findings during reoperation. Categorical variables were analyzed for differences via Fisher's exact test or Pearson's χ² test. And for survival analysis, we applied Kaplan‒Meier method curves, which were compared with the log-rank test. Further univariate and multivariate Cox regression analyses were employed to identify variables associated with post-recurrence survival and early recurrence. Time-dependent receiver operating characteristic (ROC) analysis and time-dependent area under the curve (AUC) analysis was performed to evaluate and compare the predictive performance of these factors.

resultsA total of 295 patients were included in this study, with a mean age of 65.6 years. K‒M survival curves revealed that the overall survival rate (OS) and post-recurrence survival (PRS) rate in the late recurrence group were significantly higher than those in the early recurrence group (P < 0.05). Cox regression analyses identified early recurrence (HR = 2.136, 95%CI: 1.291-3.534) and a postoperative albumin (ALB) level < 35 g/L (HR = 2.107, 95%CI: 1.187-3.741) as independent risk factors and a body mass index (BMI) ≥ 25kg/m

conclusionsPatients with early recurrence had a poorer prognosis than those with late recurrence. Decreased postoperative albumin was the other independent risk factor for PRS, with high BMI being an independent protective factor for PRS. Higher T stage, higher N stage and elevated serum CA19-9 were independent risk factors for early recurrence.

Indexed as

GastrectomyLaparoscopyNeoplasm Recurrence, LocalStomach NeoplasmsAgedFemaleHumansLymph Node ExcisionMaleMiddle AgedPrognosisRetrospective StudiesRisk FactorsGastric cancerPrognostic factorsRecurrenceTumor makers

Identifiers

PMID41239488
PMCPMC12619301

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.