ArticleCancer management and research2021
The Potential of Visceral Adipose Tissue in Distinguishing Clear Cell Renal Cell Carcinoma from Renal Angiomyolipoma with Minimal Fat.
Article in Cancer management and research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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, 5 citations in OpenAlex.
- The relationship between renal cell carcinoma pathological types and perirenal fat area.BMC cancer · 2025Article
- Nutritional status as a predictive factor for paediatric tuberous sclerosis complex-associated kidney angiomyolipomas: a retrospective analysis.European journal of pediatrics · 2024Article
- Comparison of perinephric fat measurements between malignant and benign renal tumours.The Journal of international medical research · 2022Article
- Stress Reactivity, Susceptibility to Hypertension, and Differential Expression of Genes in Hypertensive Compared to Normotensive Patients.International journal of molecular sciences · 2022Article
- Spectrum of Presentations and Management Strategies in Renal Angiomyolipoma.Journal of kidney cancer and VHL · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo overcome the challenge of preoperative differentiation between clear cell renal cell carcinoma (ccRCC) and renal angiomyolipoma with minimal fat (RMFAML), we evaluated the potential of visceral adipose tissue (VAT) in distinguishing RMFAML from ccRCC. PATIENTS AND
methodsPatients (191) were divided into ccRCC and RMFAML groups according to postoperative pathology. Umbilical horizontal computed tomography (CT) images were used for visceral fat area (VFA), subcutaneous fat area (SFA) and total fat area (TFA) measurements. Logistic regression was used to identify risk factors for ccRCC. Areas under the receiver operating characteristic (ROC) curve (AUCs) were compared to identify the most valuable indicator for identifying ccRCC and RMFAML.
resultsIn total, 166 patients had ccRCC, and 25 had RMFAML. ccRCC and RMFAML patients showed significant differences in age (P<0.001), sex (P<0.001), hypertension (P=0.027), BMI (P<0.001), SFA (P=0.046), VFA (P<0.001) and TFA (P<0.001). According to multiple logistic regression analysis, male sex [4.311 (1.469~12.653), p=0.008]; older age [1.047 (1.008~1.088), p=0.017]; and higher BMI [1.305 (1.088~1.566), p=0.004], SFA [1.013 (1.003~1.023), p=0.008], VFA [1.026 (1.012~1.041), p<0.001] and TFA [1.011 (1.005~1.017), p=0.001] were associated with ccRCC. The AUCs of sex (male), age, BMI, TFA, VFA, and SFA were 0.726, 0.687, 0.783, 0.769, 0.840, and 0.645, respectively. The VFA cut-off value was 69.99 cm
conclusionIn differentiating ccRCC from RMFAML, male sex, older age, and higher BMI, TFA, SFA, and VFA are risk factors for ccRCC. VFA is the most effective indicator for identifying ccRCC.
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.