ArticleEuropean radiology2019
A clinical-radiomics nomogram for the preoperative prediction of lung metastasis in colorectal cancer patients with indeterminate pulmonary nodules.
Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 1 of them a synthesis that pooled it.
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Who cites it
59 citing papers in PubMed, 1 synthesis or guideline pooled it, 99 citations in OpenAlex.
- Pooled it
- Crafting a prognostic nomogram for the overall survival rate of cutaneous verrucous carcinoma using the surveillance, epidemiology, and end results database.Frontiers in endocrinology · 2023Trial
- Trial
- A web-based prediction model for overall survival of elderly patients with early renal cell carcinoma: a population-based study.Journal of translational medicine · 2022Trial
- A Nomogram for Predicting Cancer-Specific Survival of Osteosarcoma and Ewing's Sarcoma in Children: A SEER Database Analysis.Frontiers in public health · 2022Trial
- The Differential Diagnostic Value of Radiomics Signatures Between Single-Nodule Pulmonary Metastases and Second Primary Lung Cancer in Patients with Colorectal Cancer.Technology in cancer research & treatmentTrial
- Differentiating sub-centimeter lung metastases in colorectal cancer by deep learning: a multicenter retrospective study.BMC medical imaging · 2026Article
- Risk factors for exclusive lung metastasis in colorectal cancer: a comprehensive narrative review.Journal of gastrointestinal oncology · 2026Review
- Artificial intelligence and computational prediction models for risk stratification, treatment response, and outcomes in colorectal cancer: a narrative review.Frontiers in oncology · 2026Review
- Prognosis of dedifferentiated liposarcoma based on surveillance, epidemiology, and end results database.European journal of medical research · 2025Article
- Preoperative prediction and localization of synchronous metastases in colon cancer: the role of CECT combined with clinical characteristics.BMC cancer · 2025Article
- Construction of a clinical prediction model for overall survival and cancer-specific survival in malignant phyllode tumor of the breast based on the SEER database.Discover oncology · 2025Article
- New insights into imaging of pulmonary metastases from extra-thoracic neoplasms.La Radiologia medica · 2025Review
- Incidence trends, overall survival, and metastasis prediction using multiple machine learning and deep learning techniques in pediatric and adolescent population with osteosarcoma and Ewing's sarcoma: nomogram and webpage.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Article
- Multi-modal radiomics features to predict overall survival of locally advanced esophageal cancer after definitive chemoradiotherapy.BMC cancer · 2025Article
- Application of Radiomics in Predicting the Prognosis of Medulloblastoma in Children.Children (Basel, Switzerland) · 2025Article
- Complete blood counts as potential risk factors of early dissemination to liver and lungs in resected colorectal cancer: a retrospective cohort study.International journal of colorectal disease · 2025Article
- Diagnostic accuracy of artificial intelligence based on imaging data for predicting distant metastasis of colorectal cancer: a systematic review and meta-analysis.Frontiers in oncology · 2025Article
- Radiomic score for lung nodules as a prognostic biomarker in locally advanced rectal cancer patients: A bi-institutional study.Cancer medicine · 2024Article
- Review
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
objectivesTo develop and validate a clinical-radiomics nomogram for preoperative prediction of lung metastasis for colorectal cancer (CRC) patients with indeterminate pulmonary nodules (IPN).
methods194 CRC patients with lung nodules were enrolled in this study (136 in the training cohort and 58 in the validation cohort). To evaluate the probability of lung metastasis, we developed three models, the clinical model with significant clinical risk factors, the radiomics model with radiomics features constructed by the least absolute shrinkage and selection operator algorithm, and the clinical-radiomics model with significant variables selected by the stepwise logistic regression. The Akaike information criterion (AIC) was used to compare the relative strength of different models, and the area under the curve (AUC) was used to quantify the predictive accuracy. The nomogram was developed based on the most appropriate model. Decision-curve analysis was applied to assess the clinical usefulness.
resultsThe clinical-radiomics model (AIC = 98.893) with the lowest AIC value compared with that of the clinical-only model (AIC = 138.502) or the radiomics-only model (AIC = 116.146) was identified as the best model. The clinical-radiomics nomogram was also successfully developed with favourable discrimination in both training cohort (AUC = 0.929, 95% CI: 0.885-0.974) and validation cohort (AUC = 0.922, 95% CI: 0.857-0.986), and good calibration. Decision-curve analysis confirmed the clinical utility of the clinical-radiomics nomogram.
conclusionsIn CRC patients with IPNs, the clinical-radiomics nomogram created by the radiomics signature and clinical risk factors exhibited favourable discriminatory ability and accuracy for a metastasis prediction. KEY POINTS: • Clinical features can predict lung metastasis of colorectal cancer patients. • Radiomics analysis outperformed clinical features in assessing the risk of pulmonary metastasis. • A clinical-radiomics nomogram can help clinicians predict lung metastasis in colorectal cancer patients.
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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.