Evidence map›Paper›PMID 41924230›Full record

ArticleCancer management and research2026

A Real-Time Online Nomogram Integrating Systemic Inflammatory Response Index and Lactate Dehydrogenase to Predict Pathological Response in Gastric Cancer Patients Receiving Neoadjuvant Chemoimmunotherapy.

Long Li, Weiwen Cai, Haobo Han, Shigong Chen, Bo Long, Gengyuan Zhang, Xiangyan Jiang, Huinian Zhou, Long Qin, Zeyuan Yu and 1 more

Abstract read
In one paragraph

Article in Cancer management and research, 2026. 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

11 authors.

Long LiDepartment of General Surgery, The Second Hospital of Lanzhou University, Lanzhou, People's Republic of China.ORCID 0009-0000-8230-6975
Weiwen CaiDepartment of General Surgery, The Second Hospital of Lanzhou University, Lanzhou, People's Republic of China.
Haobo HanDepartment of General Surgery, The Second Hospital of Lanzhou University, Lanzhou, People's Republic of China.
Shigong ChenDepartment of General Surgery, The Second Hospital of Lanzhou University, Lanzhou, People's Republic of China.
Bo LongDepartment of General Surgery, The Second Hospital of Lanzhou University, Lanzhou, People's Republic of China.
Gengyuan ZhangDepartment of General Surgery, The Second Hospital of Lanzhou University, Lanzhou, People's Republic of China.
Xiangyan JiangDepartment of General Surgery, The Second Hospital of Lanzhou University, Lanzhou, People's Republic of China.ORCID 0000-0002-7558-0228
Huinian ZhouDepartment of General Surgery, The Second Hospital of Lanzhou University, Lanzhou, People's Republic of China.
Long QinThe Second Clinical Medical School, Lanzhou University, Lanzhou, People's Republic of China.
Zeyuan YuDepartment of General Surgery, The Second Hospital of Lanzhou University, Lanzhou, People's Republic of China.
Zuoyi JiaoDepartment of General Surgery, The Second Hospital of Lanzhou University, Lanzhou, People's Republic of China.ORCID 0000-0001-8090-1279

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Globally, gastric cancer is a significant health burden. Neoadjuvant chemoimmunotherapy (NACI) has emerged as a promising strategy for locally advanced gastric cancer, but responses vary substantially among patients. Predicting major pathological response (MPR) is crucial for treatment personalization. Objective: To develop and validate a web-based nomogram that integrates readily available clinical and serological markers to predict MPR in gastric cancer patients receiving NACI. Methods: This retrospective study analyzed 325 gastric cancer patients who underwent NACI and radical resection. A nomogram was constructed using R software and validated with metrics including receiver operating characteristic curve (ROC), area under curve (AUC), calibration curves, and decision curve analysis (DCA), compared to the use of a single biomarker. Results: The MPR was 53.5%. Multivariate analysis identified lower stomach location (odds ratio (OR) = 2.90; 95% confidence interval (CI): 1.35-6.22; Conclusion: We developed and internally validated a nomogram that accurately predicts MPR after NACI. Implemented as a user-friendly web-based calculator, this model enables real-time, individualized estimation of MPR probability and may assist clinicians in tailoring treatment strategies for patients with gastric cancer. Further external and prospective validation is warranted.

Indexed as

gastric cancerlactate dehydrogenasemajor pathological responsenomogramsystemic inflammatory response indexweb calculator

Identifiers

PMID41924230
PMCPMC13035740

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.