ArticleFrontiers in immunology2026
Macrophage morphology in the tumor microenvironment predicts metachronous liver metastasis in gastric cancer: establishment and validation of a predictive model.
Article in Frontiers in immunology, 2026. 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
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Gastric cancer patients with metachronous liver metastasis (MLM) generally pose a significant clinical challenge, with 5-year survival below 10%. Macrophages are key components of a tumoral microenvironment, but the predictive value of their morphological features for MLM remains unexplored. This study aimed to construct a risk predictive model for MLM based on macrophage morphology in the tumor microenvironment. Methods: To reduce major baseline imbalances between patients with and without MLM, propensity score matching (PSM) was performed. After matching, a retrospective analysis of 233 gastric cancer patients who underwent radical surgery between 2016 and 2020 was conducted. Macrophage morphological parameters in different tissues were quantified by Qupath. Patients were randomly divided into training (70%) and validation (30%) datasets. The optimal cutoff values for the continuous variables were determined using the Youden index. Univariate and multivariate logistic regression analyses in the training set were used to identify risk factors for MLM. A nomogram was constructed for clinical applications. The model's value was validated through receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results: The incidence of MLM was similar in the training (38.7%, 63/163) and validation cohorts (32.9%, 23/70). The optimal cut off value of macrophage areas and perimeters in the tumor invasive front (IF) region, tumor region, peritumoral stroma (PS) region were 76.75 μm Conclusion: Macrophage morphology parameters, particularly in the IF and tumor regions, are significantly associated with MLM in gastric cancer. The morphology-based nomogram developed in this study provides an exploratory tool for risk stratification and may help inform individualized postoperative surveillance.
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.