Clinical trial NCT05973331: Prospective Validation of an EHR-based Pancreatic Cancer Risk Model
Official title: Prospective Validation of an EHR-based Model to Predict Pancreatic Cancer Risk Using Multicenter US Data
Study type: OBSERVATIONAL
Overall status: ACTIVE_NOT_RECRUITING
Conditions: Pancreatic Adenocarcinoma
Predictive Cancer Model
Lead sponsor: Beth Israel Deaconess Medical Center
Sponsor class: OTHER
Collaborators: name: Massachusetts Institute of Technology
name: TriNetX, LLC
First posted: 2023-08-02
Enrollment: 6134060
Sex: ALL
Minimum age (years): 40
Maximum age (years): 100
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
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.

Brief 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

Eligibility 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.

Primary outcomes:
measure: Area under the receiver operating characteristic curve (AUROC) of PRISM for all groups stratified
timeFrame: 6 months from index date
measure: Area under the receiver operating characteristic curve (AUROC) of PRISM for all groups stratified
timeFrame: at 1 year
measure: Area under the receiver operating characteristic curve (AUROC) of PRISM for all groups stratified
timeFrame: at 2 years
measure: Area under the receiver operating characteristic curve (AUROC) of PRISM for all groups stratified
timeFrame: at 3 years
measure: Calibration of PRISM for all groups stratified
timeFrame: 6 months from index date
measure: Calibration of PRISM for all groups stratified
timeFrame: at 1 year
measure: Calibration of PRISM for all groups stratified
timeFrame: at 2 years
measure: Calibration of PRISM for all groups stratified
timeFrame: at 3 years
measure: PRISM performance metrics of high-risk group for direct screening
timeFrame: 6 months from index date
measure: PRISM performance metrics of high-risk group for direct screening
timeFrame: at 1 year
measure: PRISM performance metrics of high-risk group for direct screening
timeFrame: at 2 years
measure: PRISM performance metrics of high-risk group for direct screening
timeFrame: at 3 years
measure: PRISM performance metrics of medium-risk group for biomarker testing
timeFrame: 6 months from index date
measure: PRISM performance metrics of medium-risk group for biomarker testing
timeFrame: at 1 year
measure: PRISM performance metrics of medium-risk group for biomarker testing
timeFrame: at 2 years
measure: PRISM performance metrics of medium-risk group for biomarker testing
timeFrame: at 3 years
Secondary outcomes:
measure: Timing of incident PDAC occurrence
timeFrame: 6 months from index date
measure: Timing of incident PDAC occurrence
timeFrame: at 1 year
measure: Timing of incident PDAC occurrence
timeFrame: at 2 years
measure: Timing of incident PDAC occurrence
timeFrame: at 3 years
measure: Tumor stage at PDAC diagnosis
timeFrame: 6 months from index date
measure: Tumor stage at PDAC diagnosis
timeFrame: at 1 year
measure: Tumor stage at PDAC diagnosis
timeFrame: at 2 years
measure: Tumor stage at PDAC diagnosis
timeFrame: at 3 years
Other outcomes:
Locations:
city: Boston
country: United States
facility: Beth Israel Deaconess Medical Center
state: Massachusetts
Study officials:
affiliation: Beth Israel Deaconess Medical Center
name: Limor Appelbaum, MD
role: PRINCIPAL_INVESTIGATOR
References: