ArticleMolecular imaging and biology2021
Contrast-Enhanced CT-based Textural Parameters as Potential Prognostic Factors of Survival for Colorectal Cancer Patients Receiving Targeted Therapy.
Article in Molecular imaging and biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses 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
8 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Diagnostic sensitivity and specificity of enhanced computed tomography in colorectal tumors: a meta-analysis and systematic review.Diagnostic and interventional radiology (Ankara, Turkey) · 2026Pooled it
- Radiomics in precision medicine for colorectal cancer: a bibliometric analysis (2013-2023).Frontiers in oncology · 2024Pooled it
- Role of radiomics in the diagnosis and treatment of gastrointestinal cancer.World journal of gastroenterology · 2022Review
- Development and validation of a radiomics-based nomogram for the preoperative prediction of microsatellite instability in colorectal cancer.BMC cancer · 2022Article
- Radiomics-based nomogram as predictive model for prognosis of hepatocellular carcinoma with portal vein tumor thrombosis receiving radiotherapy.Frontiers in oncology · 2022Article
- CT-Based Radiomics Can Predict the Efficacy of Anlotinib in Advanced Non-Small-Cell Lung Cancer.Journal of oncology · 2022Article
- Comparative analysis of the efficacy and accuracy of magnetic resonance imaging (MRI) and contrast-enhanced CT for residual and new lesions after transcatheter arterial chemoembolization (TACE) in patients with primary liver cancer.Translational cancer research · 2021Article
- Integrative Analysis of Histopathological Images and Genomic Data in Colon Adenocarcinoma.Frontiers in oncology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study was designed to estimate the clinical significance of the contrast-enhanced computed tomography (CT) textural features for prediction of survival in colorectal cancer (CRC) patients receiving targeted therapy (bevacizumab and cetuximab). PROCEDURES: The LifeX software was used to extract the textural parameters of the tumor lesions in the contrast-enhanced CT. We used the least absolute shrinkage and selection operator (LASSO) Cox regression and random forest method to screen the non-redundant radiomic features and constructed the CT imaging score. Univariate and multivariate analyses through the Cox proportional hazards model were performed to assess the prognostic clinical factor. Based on the result of multivariate analysis and CT imaging score, combined nomogram model was constructed to predict the overall survival (OS) of patients. Decision curves analysis was employed to evaluate the performance of the combined model and clinical model.
resultsAfter comparative analysis of the area under curve of the receiver operating characteristic (ROC) curve, we chose the result of random forest model as CT imaging score. Considering the clinical practice and the result of analysis, age, surgery, and lactate dehydrogenase (LDH) level have been introduced into clinical model. Based on the result of analysis and the CT imaging score, we constructed the nomogram combined model. C-index and calibration curve verified the goodness of fit and discrimination of the combined model. Decision curve analysis (DCA) demonstrated that the combined model showed the better net benefit for a 3-year OS than clinical model.
conclusionsIn conclusion, the study provides preliminary evidences that several radiomic parameters of tumor lesions derived from CT images were prognostic factors and predictive markers for CRC patients who are candidates for targeted therapy (bevacizumab and cetuximab).
Indexed as
Identifiers
33108800What 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.