ReviewCancers2024
Clinical Prediction Models for Prognosis of Colorectal Liver Metastases: A Comprehensive Review of Regression-Based and Machine Learning Models.
Review in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
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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
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Methodological and applicability pitfalls of clinical prediction models for asthma diagnosis: a systematic review and critical appraisal of evidence.BMC medical research methodology · 2025Pooled it
- A SEER based SHAP interpretable prognostic nomogram for overall survival in surgically treated patients with colorectal cancer and synchronous liver metastasis.Translational cancer research · 2026Article
- The Prognostic Impact of the Number of Colorectal Liver Metastases At the Time of Presentation Among Patients Undergoing Surgery.Journal of gastrointestinal cancer · 2026Article
- Risk factors and predictive models for perioperative acute kidney injury in children: a narrative review.Translational pediatrics · 2026Review
- Two Decades of Multimodal Management of Colorectal Liver Metastases With Long-Term Outcomes.ANZ journal of surgery · 2026Article
- Associating liver partition and portal vein ligation for staged hepatectomy (ALPPS)Hepatobiliary surgery and nutrition · 2026Article
- Impact of an AI prognostic tool on clinician performance in colorectal liver metastases.NPJ digital medicine · 2026Article
- Predicting histopathological growth patterns and prognosis of colorectal liver metastases using MRI.European radiology · 2026Article
- How to Integrate Surgery into the Multidisciplinary Treatment of Liver-Only Metastatic Colorectal Cancer.Cancers · 2026Review
- Improving Survival Models in Health Care by Balancing Imbalanced Cohorts: A Novel Approach.JCO clinical cancer informatics · 2026Article
- Clinical characteristics and risk factors in patients with colon cancer liver metastases.Frontiers in oncology · 2026Article
- Exploratory analysis of tumor budding density in resected synchronous and metachronous colorectal liver metastases.Frontiers in oncology · 2026Article
- Explainable AI-based prognostication of patients with resectable colorectal liver metastases using preoperative clinical parameters: is it comparable to traditional clinical scoring systems?Frontiers in oncology · 2026Article
- Integrative Predictive Nomograms for Treatment Decision-Making in Resectable Synchronous Colorectal Liver Metastases.Journal of Cancer · 2025Article
- Improving survival models in healthcare: a novel matching approach.Research square · 2024Article
- CASCADE: Context-Aware Data-Driven AI for Streamlined Multidisciplinary Tumor Board Recommendations in Oncology.Cancers · 2024Article
- Integrative Genomic and Clinical Profiling of Colorectal Cancer Liver Metastases to Guide Personalized Surgery and Liver Transplantation.Cancer genomics & proteomicsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Colorectal liver metastasis (CRLM) is a disease entity that warrants special attention due to its high frequency and potential curability. Identification of "high-risk" patients is increasingly popular for risk stratification and personalization of the management pathway. Traditional regression-based methods have been used to derive prediction models for these patients, and lately, focus has shifted to artificial intelligence-based models, with employment of variable supervised and unsupervised techniques. Multiple endpoints, like overall survival (OS), disease-free survival (DFS) and development or recurrence of postoperative complications have all been used as outcomes in these studies. This review provides an extensive overview of available clinical prediction models focusing on the prognosis of CRLM and highlights the different predictor types incorporated in each model. An overview of the modelling strategies and the outcomes chosen is provided. Specific patient and treatment characteristics included in the models are discussed in detail. Model development and validation methods are presented and critically appraised, and model performance is assessed within a proposed framework.
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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.