To hear about similar clinical trials, please enter your email below
Trial Title:
Prospective Validation of an EHR-based Pancreatic Cancer Risk Model
NCT ID:
NCT05973331
Condition:
Pancreatic Adenocarcinoma
Predictive Cancer Model
Study type:
Observational
Overall status:
Active, not recruiting
Study design:
Time perspective:
Prospective
Intervention:
Intervention type:
Other
Intervention name:
Pancreatic Cancer Risk Model (PRISM)
Description:
A neural network model (PrismNN) and a logistic regression model (PrismLR) that use
routinely collected EHR data to stratify individuals from the general population into
PDAC risk groups
Arm group label:
prospective general opulation cohort
Summary:
The goal of this prospective observational cohort study is to validate a previously
developed pancreatic cancer risk prediction algorith (the PRISM model) using electronic
health records from the general population. The main questions it aims to answer are:
- Will a pancreatic cancer risk model, developed on routine EHR data, reliably and
accurately predict pancreatic cancer in real-time?
- What is the average time from model deployment and risk prediction, to the date of
pancreatic cancer development and what is the stage of pancreatic cancer 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.
Detailed description:
To prospectively validate, implement in real-time, and assess performance of an EHR-
based PDAC risk-prediction model. To test the hypothesis that our model will reliably
predict PDAC in a real-time clinical setting, we will conduct a multi-center prospective
cohort study, deploying the PDAC risk model within the TriNetX federated network
database, and will take the following steps:
i) generate a risk prediction score for each individual under the care of 44 health care
organizations (HCOs) in the USA ii) follow all individuals for up to 3 years to assess
the primary end-point of PDAC development.
The following metrics will be used to test the discriminative performance and calibration
of the EHR-based PDAC risk model in predicting incident PDAC, at the end of the 3-year
period:
1. AUROC, sensitivity, specificity, PPV/NPV for assessing discrimination
2. Calibration: for assessing the accuracy of estimates, based on the estimated to
observed number of events
Criteria for eligibility:
Study pop:
The cohort will be selected from 44 eligible HCOs comprised of community hospitals,
outpatient clinics and academic medical centers from across the US.
Sampling method:
Non-Probability Sample
Criteria:
Inclusion Criteria:
- Male and females age >= 40 years from 44 US HCOs from the TriNetX platform
- at least 2 clinical encounters to the HCO, within the last year, before the study
start date
Exclusion Criteria:
- Personal history of PDAC or current PDAC
- Age below 40
Notes on sampling method: no sampling was performed. All eligible individuals are
included in this study.
Gender:
All
Minimum age:
40 Years
Maximum age:
100 Years
Healthy volunteers:
Accepts Healthy Volunteers
Locations:
Facility:
Name:
Beth Israel Deaconess Medical Center
Address:
City:
Boston
Zip:
02115
Country:
United States
Start date:
July 17, 2023
Completion date:
September 2026
Lead sponsor:
Agency:
Beth Israel Deaconess Medical Center
Agency class:
Other
Collaborator:
Agency:
Massachusetts Institute of Technology
Agency class:
Other
Collaborator:
Agency:
TriNetX, LLC
Agency class:
Other
Source:
Beth Israel Deaconess Medical Center
Record processing date:
ClinicalTrials.gov processed this data on November 12, 2024
Source: ClinicalTrials.gov page:
https://clinicaltrials.gov/ct2/show/NCT05973331
