ArticleBMC cancer2022
Development and validation of a gradient boosting machine to predict prognosis after liver resection for intrahepatic cholangiocarcinoma.
Article in BMC cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.
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Who cites it
27 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The Use of Machine Learning for Analyzing Real-World Data in Disease Prediction and Management: Systematic Review.JMIR medical informatics · 2025Pooled it
- Laparoscopic versus open liver resection for intrahepatic cholangiocarcinoma: a systematic review of propensity score-matched studies.Updates in surgery · 2023Pooled it
- Multiple prognostic prediction models for subglottic laryngeal cancer based on machine learning.Translational cancer research · 2026Article
- Machine Learning-Based Model to Predict Survival in Resectable Intrahepatic Cholangiocarcinoma.Cancer management and research · 2026Article
- Construction and validation of a nomogram based on the log odds of positive lymph nodes to predict the prognosis of T1 gastric cancer.Scientific reports · 2025Article
- Machine learning-driven simplification of the hypomania checklist-32 for adolescent: a feature selection approach.International journal of bipolar disorders · 2024Article
- Artificial intelligence methods available for cancer research.Frontiers of medicine · 2024Review
- Article
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- A personalized prognostic model for long-term survival in patients with intrahepatic cholangiocarcinoma: a retrospective cohort study.Annals of surgical treatment and research · 2024Article
- Development of machine learning models for patients in the high intrahepatic cholangiocarcinoma incidence age group.BMC geriatrics · 2024Article
- Creation of a machine learning-based prognostic prediction model for various subtypes of laryngeal cancer.Scientific reports · 2024Article
- Cancer-Associated Fibroblasts Together with a Decline in CD8+ T Cells Predict a Worse Prognosis for Breast Cancer Patients.Annals of surgical oncology · 2024Article
- Development of prognostic models for advanced multiple hepatocellular carcinoma based on Cox regression, deep learning and machine learning algorithms.Frontiers in medicine · 2024Article
- Factors influencing recurrence and model development for recurrence of minimally invasive percutaneous transhepatic lithotripsy: a single-center retrospective study.American journal of translational research · 2024Article
- Downregulation of JAM3 occurs in cholangiocarcinoma by hypermethylation: A potential molecular marker for diagnosis and prognosis.Journal of cellular and molecular medicine · 2024Article
- Application of AI on cholangiocarcinoma.Frontiers in oncology · 2024Review
- Predicting the microvascular invasion and tumor grading of intrahepatic mass-forming cholangiocarcinoma based on magnetic resonance imaging radiomics and morphological features.Quantitative imaging in medicine and surgery · 2023Article
- Machine learning for predicting the survival in osteosarcoma patients: Analysis based on American and Hebei Province cohort.Biomolecules & biomedicine · 2023Article
- Systemic lupus erythematosus with high disease activity identification based on machine learning.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2023Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAccurate prognosis assessment is essential for surgically resected intrahepatic cholangiocarcinoma (ICC) while published prognostic tools are limited by modest performance. We therefore aimed to establish a novel model to predict survival in resected ICC based on readily-available clinical parameters using machine learning technique.
methodsA gradient boosting machine (GBM) was trained and validated to predict the likelihood of cancer-specific survival (CSS) on data from a Chinese hospital-based database using nested cross-validation, and then tested on the Surveillance, Epidemiology, and End Results (SEER) database. The performance of GBM model was compared with that of proposed prognostic score and staging system.
resultsA total of 1050 ICC patients (401 from China and 649 from SEER) treated with resection were included. Seven covariates were identified and entered into the GBM model: age, tumor size, tumor number, vascular invasion, number of regional lymph node metastasis, histological grade, and type of surgery. The GBM model predicted CSS with C-Statistics ≥ 0.72 and outperformed proposed prognostic score or system across study cohorts, even in sub-cohort with missing data. Calibration plots of predicted probabilities against observed survival rates indicated excellent concordance. Decision curve analysis demonstrated that the model had high clinical utility. The GBM model was able to stratify 5-year CSS ranging from over 54% in low-risk subset to 0% in high-risk subset.
conclusionsWe trained and validated a GBM model that allows a more accurate estimation of patient survival after resection compared with other prognostic indices. Such a model is readily integrated into a decision-support electronic health record system, and may improve therapeutic strategies for patients with resected ICC.
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