ArticleFrontiers in oncology2021
Radiomics Analysis of Contrast-Enhanced CT Predicts Survival in Clear Cell Renal Cell Carcinoma.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Clinical application of radiomics for the prediction of treatment outcome and survival in patients with renal cell carcinoma: a systematic review.World journal of urology · 2024Pooled it
- A CT-based intratumoral and peritumoral radiomics nomogram for postoperative recurrence risk stratification in localized clear cell renal cell carcinoma.BMC medical imaging · 2025Trial
- Article
- From Radiomics to Radiogenomics: Decoding Renal Cell Carcinoma Biology for Precision Medicine-a narrative review.Insights into imaging · 2025Review
- Impact of contrast enhancement phase on CT-based radiomics analysis for predicting post-surgical recurrence in renal cell carcinoma.Japanese journal of radiology · 2025Article
- Optimization of response surface methodology for the extraction of isoliquiritigenin fromFrontiers in pharmacology · 2025Article
- Predicting first-line VEGFR-TKI resistance and survival in metastatic clear cell renal cell carcinoma using a clinical-radiomic nomogram.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- A CT-based deep learning radiomics nomogram outperforms the existing prognostic models for outcome prediction in clear cell renal cell carcinoma: a multicenter study.European radiology · 2023Article
- Prognostic value of computed tomography radiomics features in patients with gastric neuroendocrine neoplasm.Frontiers in oncology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo develop and validate the radiomics nomogram that combines clinical factors and radiomics features to estimate overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC), and assess the incremental value of radiomics for OS estimation. MATERIALS AND
methodsOne hundred ninety-four ccRCC cases were included in the training cohort and 188 ccRCC patients from another hospital as the test cohort. Three-dimensional region-of-interest segmentation was manually segmented on multiphasic contrast-enhanced abdominal CT images. Radiomics score (Rad-score) was calculated from a formula generated
resultsRad-score, calculated using a linear combination of the 11 screened features multiplied by their respective LASSO Cox coefficients, was significantly associated with OS. Calibration curves showed good agreement between the OS predicted by the nomograms and observed outcomes. The radiomics nomogram presented higher discrimination capability compared to clinical nomogram in the training (C-index: 0.884; 95% CI: 0.808-0.940
conclusionsThe radiomics nomogram may be used for predicting OS in patients with ccRCC, and radiomics is useful to assist quantitative and personalized treatment.
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.