ArticleCancer control : journal of the Moffitt Cancer Center
The Prognostic Value of Body Composition Analysis on Non-Enhanced CT for Risk Stratification in Gastrointestinal Stromal Tumors: A Retrospective Study.
Article in Cancer control : journal of the Moffitt Cancer Center. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- A deep learning-based radiomic nomogram derived from visceral fat for early prediction of gastrointestinal stromal tumor risk grade.Frontiers in medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
IntroductionContrast-enhanced computed tomography (CT) is the primary imaging modality for accurate risk stratification in gastrointestinal stromal tumors (GISTs). However, contrast-enhanced CT may not always be accessible or suitable for all patients undergoing risk assessment of GISTs. Therefore, this study explored the use of non-enhanced CT imaging for assessing body composition in patients with GISTs to preoperatively predict risk stratification.MethodsWe retrospectively analyzed 233 patients with GISTs who met the inclusion criteria. Pretreatment complete abdominal CT images from these patients were processed and analyzed using the Siemens Syngo imaging system. The data were subsequently organized and analyzed using the SPSS software (version 26.0).ResultsThrough two independent samples t-tests, Mann-Whitney U tests, and chi-square tests (including corrected chi-square tests and Fisher's exact tests), the intermediate-high risk group exhibited a lower visceral fat index (VFI) and higher tumor volumes and proportions of necrosis (
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.