Evidence map›Paper›PMID 39180668›Full record

ArticleAbdominal radiology (New York)2025

Association between calcification and risk stratification in gastric gastrointestinal stromal tumors.

Xiao Luo, Jinyao Chen, Yicheng Fang, Qinhui Xu, Fei Jiang, Guanliang Wang

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Article in Abdominal radiology (New York), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Xiao Luogrid.469636.8Zhejiang Taizhou Hospital, Linhai, China.
Jinyao Chengrid.469636.8Zhejiang Taizhou Hospital, Linhai, China.
Yicheng Fanggrid.469636.8Zhejiang Taizhou Hospital, Linhai, China.
Qinhui Xugrid.469636.8Zhejiang Taizhou Hospital, Linhai, China. xuqh@enzemed.com.
Fei Jianggrid.469636.8Zhejiang Taizhou Hospital, Linhai, China.
Guanliang Wanggrid.469636.8Zhejiang Taizhou Hospital, Linhai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRisk assessment of gastric gastrointestinal stromal tumors (GISTs), particularly those with a diameter ≤ 5 cm, remains a clinical challenge. Previous research has primarily focused on tumor size, ulceration, necrosis, and enhancement patterns, with less emphasis on the role of tumor calcification, which remains controversial regarding its correlation with malignancy risk.

objectiveThis study aims to explore the characteristics of calcification in gastric GISTs and its correlation with risk stratification as defined by the National Institutes of Health (NIH), to improve preoperative risk assessment for gastric GISTs ≤ 5 cm.

methodsA retrospective analysis of 385 pathologically confirmed gastric GIST patients, including 178 with small gastric GISTs (< 2 cm), was conducted. Tumors were categorized into low-risk (very low / low) and high-risk (intermediate / high) groups based on NIH criteria. Variables such as age, gender, tumor long-axis diameter, calcification rates, calcification size, the number and distribution of calcification, calcification to tumor long-axis diameter ratio were analyzed. Logistic regression was used to identify independent predictors of malignancy for gastric GISTs, with predictive values assessed via receiver operating characteristic (ROC) curves.

resultsSignificant differences were found between high-risk and low-risk groups in treatment methods, tumor long-axis diameter, the ratio of calcification to tumor long-axis, and calcification distribution (P < 0.05). Calcification rates varied across risk categories, with 23.6% in very low-risk, 31.6% in low-risk, 9.8% in intermediate-risk, and 31.7% in high-risk categories (P < 0.05). In GISTs ≤ 5 cm, both tumor long-axis diameter (OR = 3.07, 95% CI: 2.29-4.10) and calcification (OR = 0.36, 95% CI: 0.13-0.97) were independent predictors of malignancy risk (both P < 0.05). ROC curve analysis yielded areas of 0.849 for tumor long-axis diameter, 0.578 for calcification, and 0.862 for their combination.

conclusionThe study indicates lower calcification rates in intermediate-risk gastric GISTs and higher rates in other risk categories. Additionally, tumors of different sizes exhibit two distinct calcification patterns, suggesting possible differing mechanisms of calcification in tumors. Calcification in gastric GISTs ≤ 5 cm acts as a protective factor against higher malignancy risk, and when combined with tumor long-axis diameter, significantly enhances predictive accuracy over long-axis diameter alone.

Indexed as

CalcinosisGastrointestinal Stromal TumorsStomach NeoplasmsTomography, X-Ray ComputedAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedRetrospective StudiesRisk AssessmentCalcificationEndoscopyGastric gastrointestinal stromal tumorRisk stratificationSmall gastric gastrointestinal stromal tumor

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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.