Prospective Validation of Liver Cancer Risk Computation (LIRIC) Models

NCT06140823 | Active Not Recruiting

• 1 other identifier: Nov2023Trial
• Study Type: observational
• Target: 6,000,000
• Locations: 1 country
• Sites: 1

Brief 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.

Conditions

Predictive Cancer Model

Outcome Measures

Primary Outcomes (3)

• Area under the receiver operating characteristic curve (AUROC) of LIRIC for all groups stratified

  To assess the discriminatory performance of LIRIC for prospective identification of high-risk individuals for HCC development. ROCs and AUROC numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location.

  6 months from index date, at 1 year, 2 years and 3 years

• Calibration of LIRIC for all groups stratified

  To assess how well the risk prediction by LIRIC aligns with observed risk without recalibration. Calibration plots will be created for the whole population and groups stratified by age, sex, race, and geographical location.

  6 months from index date, at 1 year, 2 years and 3 years

• Performance metrics for LIRIC model risk quantiles

  To evaluate the sensitivity, specificity, number of individuals/number of HCC cases, PPV, NNS in each predicted risk quantile for multiple risk thresholds

  6 months from index date, at 1 year, 2 years and 3 years

Secondary Outcomes (2)

• Timing of incident HCC occurrence

  6 months from index date, at 1 year, 2 years and 3 years

• Tumor stage at HCC diagnosis

  6 months from index date, at 1 year, 2 years and 3 years

Study Arms (3)

prospective general population cohort

Males and females age \>= 40 years, without a personal history of HCC or current HCC and at least two clinical visits to their HCO, within the last year, before the study start date.

Other: Liver Risk Computation Model (LIRIC)

Prospective cirrhosis population cohort

Males and females age \>= 40 years, with liver cirrhosis and without a personal history of HCC or current HCC, that have at least two clinical visits to their HCO, within the last year, before the study start date.

Other: Liver Risk Computation Model (LIRIC)_cirrhosis

Prospective no_cirrhosis population cohort

Males and females age \>= 40 years, without a personal history of HCC or current HCC and without a diagnosis of liver cirrhosis, that have at least two clinical visits to their HCO, within the last year, before the study start date.

Other: Liver Risk Computation Model (LIRIC)_no_cirrhosis

Interventions

Liver Risk Computation Model (LIRIC) OTHER

A neural network model (LIRIC-NN) and a logistic regression model (LIRIC-LR) that use routinely collected EHR data to stratify individuals into HCC risk groups for the general population

prospective general population cohort

Liver Risk Computation Model (LIRIC)_cirrhosis OTHER

A neural network model (LIRIC-NN) and a logistic regression model (LIRIC-LR) that use routinely collected EHR data to stratify individuals into HCC risk groups for the population with liver cirrhosis

Prospective cirrhosis population cohort

Liver Risk Computation Model (LIRIC)_no_cirrhosis OTHER

neural network model (LIRIC-NN) and a logistic regression model (LIRIC-LR) that use routinely collected EHR data to stratify individuals into HCC risk groups for the population without liver cirrhosis

Prospective no_cirrhosis population cohort

Eligibility Criteria

• Age: 40 Years - 100 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The cohort will be selected from 44 eligible HCOs comprised of community hospitals, outpatient clinics and academic medical centers from across the US.

You may qualify if:

• Male and females age ≥40 years from all US HCOs available on the platform
• at least at least 2 clinical encounters to the HCO, within the last year, before the study start date

You may not qualify if:

• Personal history of HCC or current HCC (ICD-9: 155.0; ICD-10: C22.0)

Sponsors & Collaborators

• Beth Israel Deaconess Medical Center: lead
• Massachusetts Institute of Technology: collaborator
• TriNetX, LLC: collaborator

Study Sites (1)

Beth Israel Deaconess Medical Center

Boston, Massachusetts, 02115, United States

Location

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: November 15, 2023
• First Posted: November 20, 2023
• Study Start: April 1, 2023
• Primary Completion (Estimated): March 31, 2027
• Study Completion (Estimated): March 31, 2027
• Last Updated: April 22, 2026

Record last verified: 2026-04

Locations

US (1)