ArticleEuropean radiology2016
Does size reliably predict malignancy in soft tissue tumours?
Article in European radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 25 citations in OpenAlex.
- Intravoxel incoherent motion combined with conventional MRI for the differentiation of benign, intermediate, and malignant fibrous soft-tissue tumors.Frontiers in oncology · 2026Article
- Key clinical and demographic factors influencing head and neck tumor severity in Lagos.BMC oral health · 2025Article
- Ultrasound performance in pediatric deep soft-tissue tumor characterization.Scientific reports · 2023Article
- Evaluation of Classic and Quantitative Imaging Features in the Differentiation of Benign and Atypical Lipomatous Soft Tissue Tumors Using a Standardized Multiparametric MRI Protocol: A Prospective Single-Centre Study in 45 Patients.Current oncology (Toronto, Ont.) · 2023Article
- Diagnostic Performance of Magnetic Resonance Imaging in Discriminating Benign and Malignant Soft Tissue Tumors.International journal of general medicine · 2023Article
- What morphological MRI features enable differentiation of low-grade from high-grade soft tissue sarcoma?BJR open · 2022Article
- Significance of coagulation and fibrinolysis markers for benign and malignant soft tissue tumors.BMC cancer · 2021Article
- Accuracy of ultrasound in the characterisation of deep soft tissue masses: a prospective study.European radiology · 2020Article
- Differentiation of soft tissue and bone sarcomas from benign lesions utilizingBMC medical imaging · 2020Article
- Small indeterminate superficial soft tissue masses: relationship between depth and histological grade.The British journal of radiology · 2020Article
- High-grade soft-tissue sarcoma: optimizing injection improves MRI evaluation of tumor response.European radiology · 2019Article
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 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeIn this retrospective study we examined whether size is a viable marker of tumour malignancy in soft tissue masses (STM) and if the ratio of width and length (R
methodsMeasurements of maximal lesion size and perpendicular diameter were performed in available MRI and ultrasonography studies of 212 patients (mean age 54.4 ± 17.2 years, male:female 1:1.12) with a histologically verified diagnosis.
resultsOverall, 28.2 % of lesions were malignant, 11.1 % intermediate, and 58.8 % benign. Size alone was a weak predictor of malignancy in STMs (sensitivity 68.8 %, specificity 50.3 %, positive predictive value [PPV] 44.0 %, negative predictive value [NPV] 80.4 %). R
conclusionsSize should not be used alone to estimate an STM's malignancy. R KEY POINTS: •Size does not reliably differentiate between benign, intermediate, and malignant tumours •The R
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.