Clinical Trials Logo

Clinical Trial Summary

The goal of this prospective observational cohort study is to validate previously developed Hepatocellular Carcinoma (HCC) risk prediction algorithms, the Liver Risk Computation (LIRIC) models, which are based on electronic health records. The main questions it aims to answer are: - Will our retrospectively developed general population LIRIC models, developed on routine EHR data, perform similarly when prospectively validated, and reliably and accurately predict HCC in real-time? - What is the average time from model deployment and risk prediction, to the date of HCC development and what is the stage of HCC at diagnosis? The risk model will be deployed on data from individuals eligible for the study. Each individual will be assigned a risk score and tracked over time to assess the model's discriminatory performance and calibration.


Clinical Trial Description

The investigators will conduct a prospective observational cohort study, separately deploying three separate LIRIC models (the general population, cirrhosis, and no_cirrhosis models) on retrospective de-identified EHR data of 44 HCOs in the USA, using the TriNetX federated network platform. LIRIC will generate a risk score for each individual. All risk-stratified individuals will be prospectively, electronically followed for up to 3-years to assess the primary end-point of HCC development. At the end of this period, model discrimination will be assessed, using the following metrics: AUROC, sensitivity, specificity, PPV/NPV. Risk scores generated by the model will be divided into quantiles. For each quantile, the investigators will evaluate the following: number of individuals in each quantile, number of HCC cases, PPV, NNS, SIR. Model calibration will be used for assessing the accuracy of estimates, based on the estimated to observed number of events. The model will dynamically re-evaluate all individual data every 6 months, re-classifying individuals (as needed). ;


Study Design


Related Conditions & MeSH terms


NCT number NCT06140823
Study type Observational
Source Beth Israel Deaconess Medical Center
Contact
Status Active, not recruiting
Phase
Start date April 1, 2023
Completion date March 31, 2027

See also
  Status Clinical Trial Phase
Recruiting NCT06023966 - A Clinical Prospective Study to Validate a Risk Scoring Model for the HMGC After Curative Surgery
Recruiting NCT04535466 - Diagnosis Predictive Modle for Dense Density Breast Tissue Based on Radiomics
Recruiting NCT03280134 - A Prospective Validation Cohort Study of a Prediction System on nSLN Metastasis in Early Breast Cancer N/A
Recruiting NCT03253107 - Predicting Biomarker of Gastric Cancer Chemotherapy Response
Recruiting NCT06364371 - Dynamic Multi-omics Integration Model to Predict Neoadjuvant Therapy Response in Locally Advanced Rectal Cancer
Recruiting NCT05997147 - A Preoperative Model to Predict the Lymphovascular Invasion in Pancreatic Ductal Adenocarcinoma
Recruiting NCT05929365 - Innovative Approach to Detect Recurrent Colorectal Lesions With Surveillance Via Mutation Analysis & Clinical Phenotype
Active, not recruiting NCT05973331 - Prospective Validation of an EHR-based Pancreatic Cancer Risk Model
Recruiting NCT05338073 - KM3D Multicenter Cancer Consortium: Predicting Patient Response Using 3D Cell Culture Models
Recruiting NCT06391892 - Liquid Biopsy (ctDNA) Guided Treatment in Localized Pancreatic Cancer: Neoadjuvant CTX vs. Upfront Surgery Phase 3
Recruiting NCT06202404 - Predicting Tumor Metastasis by Employing a Target Organ/Primary Lesion Fusion Radiomics Model
Completed NCT06411015 - Prognostic Evaluation Prediction Model Survival Spinal Epidural Metastases
Completed NCT04079283 - Radiomics of Immunotherapeutics Response Evaluation and Prediction
Completed NCT06092918 - Generation and Validation of Predictive Models for Localized Prostate Cancer Treated With External Radiotherapy.
Recruiting NCT06339307 - A Prospective Clinical Study to Validate a Preoperative Risk Scoring Model for LNM in GC Patients
Recruiting NCT04185779 - COLO-COHORT (Colorectal Cancer Cohort) Study
Active, not recruiting NCT06074029 - Exploratory Study on the Therapeutic Effect Prediction Model of Advanced BTC Immunotherapy Phase 1/Phase 2
Recruiting NCT05741944 - The Value of a Risk Prediction Tool (PERSARC) for Effective Treatment Decisions of Soft-tissue Sarcomas Patients N/A
Recruiting NCT04452058 - CT-based Radiomic Algorithm for Assisting Surgery Decision and Predicting Immunotherapy Response of NSCLC
Recruiting NCT04511481 - Deep Learning Magnetic Resonance Imaging Radiomic Predict Platinum-sensitive in Patients With Epithelial Ovarian Cancer