ArticleJournal of gastrointestinal oncology2017
CT-based assessment of visceral adiposity and outcomes for esophageal adenocarcinoma.
Article in Journal of gastrointestinal oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled 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.
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
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Adiposity and cancer survival: a systematic review and meta-analysis.Cancer causes & control : CCC · 2022Pooled it
- Development and validation of a CT-based comprehensive nomogram for differentiating benign from malignant subcentimeter solid nodules.Journal of thoracic disease · 2025Article
- Establishment of normative biometric data for body composition based on computed tomography in a North American cohort.Clinical nutrition (Edinburgh, Scotland) · 2021Article
- Visceral Obesity, Metabolic Syndrome, and Esophageal Adenocarcinoma.Frontiers in oncology · 2021Review
- Influence of body composition and muscle strength on outcomes after multimodal oesophageal cancer treatment.Journal of cachexia, sarcopenia and muscle · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVarious methods of quantifying and correlating obesity to outcomes for patients with esophageal adenocarcinoma (EA) have been evaluated. Published data suggest that quantification of adiposity may be more accurate than body mass index (BMI) as a prognostic factor. We report our analysis of adiposity as a prognostic factor in a series of patients with EA.
methodsThis single institution retrospective review included patients with EA who underwent esophagectomy from 1994-2008. Patients with BMI <20 were excluded. Using the preoperative CT scan, the visceral (VFA), subcutaneous (SFA), and total abdominal fat (TFA) areas were calculated. Each was contoured on a Siemens Leonardo workstation at the level of the iliac crest (L4/5). The Hounsfield threshold was -30 to -130. Outcomes were analyzed using Kaplan-Meier method and log-rank analysis. Multivariate analysis (MVA) was performed using the Cox proportion hazard regression model.
resultsWe identified 126 patients for the analysis. There were no statistically significant differences in overall survival or disease-free survival between groups above and below the medians for TFA, SFA, or VFA/SFA ratio. However, an increase in VFA was significantly associated with worsened OS and DFS when we further classified patients into quartiles. Patients with VFA ≥182 cm
conclusionsPublished data have demonstrated an association between treatment outcomes and degree of adiposity; our study found a correlation between VFA and OS and DFS in patients with EA. Median TFA, SFA, and VFA/SFA were not prognostic on MVA. While VFA >182 cm
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.