xml: <clinical_study>
    <!-- This xml conforms to an XML Schema at:
      https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
    <required_header>
      <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
      <link_text>Link to the current ClinicalTrials.gov record.</link_text>
      <url>https://clinicaltrials.gov/ct2/show/NCT05973331</url>
    </required_header>
    <id_info>
      <org_study_id>2023Trial</org_study_id>
      <nct_id>NCT05973331</nct_id>
    </id_info>
    <brief_title>Prospective Validation of an EHR-based Pancreatic Cancer Risk Model</brief_title>
    <official_title>Prospective Validation of an EHR-based Model to Predict Pancreatic Cancer Risk Using Multicenter US Data</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>Beth Israel Deaconess Medical Center</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>Massachusetts Institute of Technology</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>TriNetX, LLC</agency>
        <agency_class>Other</agency_class>
      </collaborator>
    </sponsors>
    <source>Beth Israel Deaconess Medical Center</source>
    <oversight_info>
      <has_dmc>No</has_dmc>
      <is_fda_regulated_drug>No</is_fda_regulated_drug>
      <is_fda_regulated_device>No</is_fda_regulated_device>
    </oversight_info>
    <brief_summary>
      <textblock>
        The goal of this prospective observational cohort study is to validate a previously developed&#xD;
        pancreatic cancer risk prediction algorith (the PRISM model) using electronic health records&#xD;
        from the general population. The main questions it aims to answer are:&#xD;
  &#xD;
          -  Will a pancreatic cancer risk model, developed on routine EHR data, reliably and&#xD;
             accurately predict pancreatic cancer in real-time?&#xD;
  &#xD;
          -  What is the average time from model deployment and risk prediction, to the date of&#xD;
             pancreatic cancer development and what is the stage of pancreatic cancer at diagnosis?&#xD;
             The risk model will be deployed on data from individuals eligible for the study. Each&#xD;
             individual will be assigned a risk score and tracked over time to assess the model's&#xD;
             discriminatory performance and calibration.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        To prospectively validate, implement in real-time, and assess performance of an EHR- based&#xD;
        PDAC risk-prediction model. To test the hypothesis that our model will reliably predict PDAC&#xD;
        in a real-time clinical setting, we will conduct a multi-center prospective cohort study,&#xD;
        deploying the PDAC risk model within the TriNetX federated network database, and will take&#xD;
        the following steps:&#xD;
  &#xD;
        i) generate a risk prediction score for each individual under the care of 44 health care&#xD;
        organizations (HCOs) in the USA ii) follow all individuals for up to 3 years to assess the&#xD;
        primary end-point of PDAC development.&#xD;
  &#xD;
        The following metrics will be used to test the discriminative performance and calibration of&#xD;
        the EHR-based PDAC risk model in predicting incident PDAC, at the end of the 3-year period:&#xD;
  &#xD;
          1. AUROC, sensitivity, specificity, PPV/NPV for assessing discrimination&#xD;
  &#xD;
          2. Calibration: for assessing the accuracy of estimates, based on the estimated to observed&#xD;
             number of events&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Active, not recruiting</overall_status>
    <start_date type="Actual">July 17, 2023</start_date>
    <completion_date type="Anticipated">September 2026</completion_date>
    <primary_completion_date type="Anticipated">July 2026</primary_completion_date>
    <study_type>Observational</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <observational_model>Cohort</observational_model>
      <time_perspective>Prospective</time_perspective>
    </study_design_info>
    <primary_outcome>
      <measure>Area under the receiver operating characteristic curve (AUROC) of PRISM for all groups stratified</measure>
      <time_frame>6 months from index date</time_frame>
      <description>To assess the discriminatory performance of PRISM for prospective identification of high-risk individuals for PDAC development. ROCs and AUROC numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Area under the receiver operating characteristic curve (AUROC) of PRISM for all groups stratified</measure>
      <time_frame>at 1 year</time_frame>
      <description>To assess the discriminatory performance of PRISM for prospective identification of high-risk individuals for PDAC development. ROCs and AUROC numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Area under the receiver operating characteristic curve (AUROC) of PRISM for all groups stratified</measure>
      <time_frame>at 2 years</time_frame>
      <description>To assess the discriminatory performance of PRISM for prospective identification of high-risk individuals for PDAC development. ROCs and AUROC numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Area under the receiver operating characteristic curve (AUROC) of PRISM for all groups stratified</measure>
      <time_frame>at 3 years</time_frame>
      <description>To assess the discriminatory performance of PRISM for prospective identification of high-risk individuals for PDAC development. ROCs and AUROC numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Calibration of PRISM for all groups stratified</measure>
      <time_frame>6 months from index date</time_frame>
      <description>To access how well the risk prediction by PRISM 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.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Calibration of PRISM for all groups stratified</measure>
      <time_frame>at 1 year</time_frame>
      <description>To access how well the risk prediction by PRISM 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.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Calibration of PRISM for all groups stratified</measure>
      <time_frame>at 2 years</time_frame>
      <description>To access how well the risk prediction by PRISM 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.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Calibration of PRISM for all groups stratified</measure>
      <time_frame>at 3 years</time_frame>
      <description>To access how well the risk prediction by PRISM 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.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>PRISM performance metrics of high-risk group for direct screening</measure>
      <time_frame>6 months from index date</time_frame>
      <description>To evaluate sensitivity, specificity, PPV, and SIR for patients identified as high-risk by PRISM. Numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location. Risk threshold determined based on Standardized Incidence Ratio of 5 or greater. The absolute one-year risk thresholds are 0.1834% for PrismNN and 0.2048% risk for PrismLR. SIR 5 or greater was chosen because it is comparable to the current screening inclusion threshold for individuals with an inherited predisposition.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>PRISM performance metrics of high-risk group for direct screening</measure>
      <time_frame>at 1 year</time_frame>
      <description>To evaluate sensitivity, specificity, PPV, and SIR for patients identified as high-risk by PRISM. Numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location. Risk threshold determined based on Standardized Incidence Ratio of 5 or greater. The absolute one-year risk thresholds are 0.1834% for PrismNN and 0.2048% risk for PrismLR. SIR 5 or greater was chosen because it is comparable to the current screening inclusion threshold for individuals with an inherited predisposition.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>PRISM performance metrics of high-risk group for direct screening</measure>
      <time_frame>at 2 years</time_frame>
      <description>To evaluate sensitivity, specificity, PPV, and SIR for patients identified as high-risk by PRISM. Numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location. Risk threshold determined based on Standardized Incidence Ratio of 5 or greater. The absolute one-year risk thresholds are 0.1834% for PrismNN and 0.2048% risk for PrismLR. SIR 5 or greater was chosen because it is comparable to the current screening inclusion threshold for individuals with an inherited predisposition.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>PRISM performance metrics of high-risk group for direct screening</measure>
      <time_frame>at 3 years</time_frame>
      <description>To evaluate sensitivity, specificity, PPV, and SIR for patients identified as high-risk by PRISM. Numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location. Risk threshold determined based on Standardized Incidence Ratio of 5 or greater. The absolute one-year risk thresholds are 0.1834% for PrismNN and 0.2048% risk for PrismLR. SIR 5 or greater was chosen because it is comparable to the current screening inclusion threshold for individuals with an inherited predisposition.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>PRISM performance metrics of medium-risk group for biomarker testing</measure>
      <time_frame>6 months from index date</time_frame>
      <description>To evaluate sensitivity, specificity, PPV, and SIR for patients identified as medium-risk by PRISM. Numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location. Risk threshold determined by specificity 85%, with sensitivity around 46%. The absolute one-year risk thresholds are 0.0574% for PrismNN and 0.0564% for PrismLR. Prism operates as a tiered system for identifying individuals in need of screening with this lower risk threshold.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>PRISM performance metrics of medium-risk group for biomarker testing</measure>
      <time_frame>at 1 year</time_frame>
      <description>To evaluate sensitivity, specificity, PPV, and SIR for patients identified as medium-risk by PRISM. Numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location. Risk threshold determined by specificity 85%, with sensitivity around 46%. The absolute one-year risk thresholds are 0.0574% for PrismNN and 0.0564% for PrismLR. Prism operates as a tiered system for identifying individuals in need of screening with this lower risk threshold.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>PRISM performance metrics of medium-risk group for biomarker testing</measure>
      <time_frame>at 2 years</time_frame>
      <description>To evaluate sensitivity, specificity, PPV, and SIR for patients identified as medium-risk by PRISM. Numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location. Risk threshold determined by specificity 85%, with sensitivity around 46%. The absolute one-year risk thresholds are 0.0574% for PrismNN and 0.0564% for PrismLR. Prism operates as a tiered system for identifying individuals in need of screening with this lower risk threshold.</description>
    </primary_outcome>
    <primary_outcome>
      <measure>PRISM performance metrics of medium-risk group for biomarker testing</measure>
      <time_frame>at 3 years</time_frame>
      <description>To evaluate sensitivity, specificity, PPV, and SIR for patients identified as medium-risk by PRISM. Numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location. Risk threshold determined by specificity 85%, with sensitivity around 46%. The absolute one-year risk thresholds are 0.0574% for PrismNN and 0.0564% for PrismLR. Prism operates as a tiered system for identifying individuals in need of screening with this lower risk threshold.</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>Timing of incident PDAC occurrence</measure>
      <time_frame>6 months from index date</time_frame>
      <description>To evaluate how long in advance before PDAC occurrence should be expected for PRISM models to make high-risk predictions. Distribution plots of the date of PDAC incidence for high/medium-risk groups (defined in Outcome 3 and Outcome 4) will be created.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Timing of incident PDAC occurrence</measure>
      <time_frame>at 1 year</time_frame>
      <description>To evaluate how long in advance before PDAC occurrence should be expected for PRISM models to make high-risk predictions. Distribution plots of the date of PDAC incidence for high/medium-risk groups (defined in Outcome 3 and Outcome 4) will be created.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Timing of incident PDAC occurrence</measure>
      <time_frame>at 2 years</time_frame>
      <description>To evaluate how long in advance before PDAC occurrence should be expected for PRISM models to make high-risk predictions. Distribution plots of the date of PDAC incidence for high/medium-risk groups (defined in Outcome 3 and Outcome 4) will be created.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Timing of incident PDAC occurrence</measure>
      <time_frame>at 3 years</time_frame>
      <description>To evaluate how long in advance before PDAC occurrence should be expected for PRISM models to make high-risk predictions. Distribution plots of the date of PDAC incidence for high/medium-risk groups (defined in Outcome 3 and Outcome 4) will be created.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Tumor stage at PDAC diagnosis</measure>
      <time_frame>6 months from index date</time_frame>
      <description>stage at diagnosis per tumor registry/pathology report</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Tumor stage at PDAC diagnosis</measure>
      <time_frame>at 1 year</time_frame>
      <description>stage at diagnosis per tumor registry/pathology report</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Tumor stage at PDAC diagnosis</measure>
      <time_frame>at 2 years</time_frame>
      <description>stage at diagnosis per tumor registry/pathology report</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Tumor stage at PDAC diagnosis</measure>
      <time_frame>at 3 years</time_frame>
      <description>stage at diagnosis per tumor registry/pathology report</description>
    </secondary_outcome>
    <number_of_groups>1</number_of_groups>
    <enrollment type="Actual">6134060</enrollment>
    <condition>Pancreatic Adenocarcinoma</condition>
    <condition>Predictive Cancer Model</condition>
    <arm_group>
      <arm_group_label>prospective general opulation cohort</arm_group_label>
      <description>Males and females age &gt;= 40 years, without a personal history of PDAC or current PDAC, with at least 2 clinical encounters to the HCO within the year prior to the study start date.</description>
    </arm_group>
    <intervention>
      <intervention_type>Other</intervention_type>
      <intervention_name>Pancreatic Cancer Risk Model (PRISM)</intervention_name>
      <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</description>
      <arm_group_label>prospective general opulation cohort</arm_group_label>
    </intervention>
    <eligibility>
      <study_pop>
        <textblock>
          The cohort will be selected from 44 eligible HCOs comprised of community hospitals,&#xD;
          outpatient clinics and academic medical centers from across the US.&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Non-Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Male and females age &gt;= 40 years from 44 US HCOs from the TriNetX platform&#xD;
  &#xD;
            -  at least 2 clinical encounters to the HCO, within the last year, before the study&#xD;
               start date&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  Personal history of PDAC or current PDAC&#xD;
  &#xD;
            -  Age below 40&#xD;
  &#xD;
          Notes on sampling method: no sampling was performed. All eligible individuals are included&#xD;
          in this study.&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>40 Years</minimum_age>
      <maximum_age>100 Years</maximum_age>
      <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Limor Appelbaum, MD</last_name>
      <role>Principal Investigator</role>
      <affiliation>Beth Israel Deaconess Medical Center</affiliation>
    </overall_official>
    <location>
      <facility>
        <name>Beth Israel Deaconess Medical Center</name>
        <address>
          <city>Boston</city>
          <state>Massachusetts</state>
          <zip>02115</zip>
          <country>United States</country>
        </address>
      </facility>
    </location>
    <location_countries>
      <country>United States</country>
    </location_countries>
    <verification_date>August 2023</verification_date>
    <study_first_submitted>July 17, 2023</study_first_submitted>
    <study_first_submitted_qc>August 1, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 2, 2023</study_first_posted>
    <last_update_submitted>August 1, 2023</last_update_submitted>
    <last_update_submitted_qc>August 1, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 2, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Principal Investigator</responsible_party_type>
      <investigator_affiliation>Beth Israel Deaconess Medical Center</investigator_affiliation>
      <investigator_full_name>Limor Appelbaum</investigator_full_name>
      <investigator_title>Staff Scientist</investigator_title>
    </responsible_party>
    <patient_data>
      <sharing_ipd>No</sharing_ipd>
    </patient_data>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: download date: ClinicalTrials.gov processed this data on September 20, 2023
  link text: Link to the current ClinicalTrials.gov record.
  url: https://clinicaltrials.gov/ct2/show/NCT05973331
  org study id: 2023Trial
  nct id: NCT05973331
  lead sponsor: 
  collaborator: 
  collaborator: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  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.
  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
  observational model: Cohort
  time perspective: Prospective
  measure: Area under the receiver operating characteristic curve (AUROC) of PRISM for all groups stratified
  time frame: 6 months from index date
  description: To assess the discriminatory performance of PRISM for prospective identification of high-risk individuals for PDAC development. ROCs and AUROC numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location.
  measure: Area under the receiver operating characteristic curve (AUROC) of PRISM for all groups stratified
  time frame: at 1 year
  description: To assess the discriminatory performance of PRISM for prospective identification of high-risk individuals for PDAC development. ROCs and AUROC numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location.
  measure: Area under the receiver operating characteristic curve (AUROC) of PRISM for all groups stratified
  time frame: at 2 years
  description: To assess the discriminatory performance of PRISM for prospective identification of high-risk individuals for PDAC development. ROCs and AUROC numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location.
  measure: Area under the receiver operating characteristic curve (AUROC) of PRISM for all groups stratified
  time frame: at 3 years
  description: To assess the discriminatory performance of PRISM for prospective identification of high-risk individuals for PDAC development. ROCs and AUROC numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location.
  measure: Calibration of PRISM for all groups stratified
  time frame: 6 months from index date
  description: To access how well the risk prediction by PRISM 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.
  measure: Calibration of PRISM for all groups stratified
  time frame: at 1 year
  description: To access how well the risk prediction by PRISM 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.
  measure: Calibration of PRISM for all groups stratified
  time frame: at 2 years
  description: To access how well the risk prediction by PRISM 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.
  measure: Calibration of PRISM for all groups stratified
  time frame: at 3 years
  description: To access how well the risk prediction by PRISM 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.
  measure: PRISM performance metrics of high-risk group for direct screening
  time frame: 6 months from index date
  description: To evaluate sensitivity, specificity, PPV, and SIR for patients identified as high-risk by PRISM. Numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location. Risk threshold determined based on Standardized Incidence Ratio of 5 or greater. The absolute one-year risk thresholds are 0.1834% for PrismNN and 0.2048% risk for PrismLR. SIR 5 or greater was chosen because it is comparable to the current screening inclusion threshold for individuals with an inherited predisposition.
  measure: PRISM performance metrics of high-risk group for direct screening
  time frame: at 1 year
  description: To evaluate sensitivity, specificity, PPV, and SIR for patients identified as high-risk by PRISM. Numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location. Risk threshold determined based on Standardized Incidence Ratio of 5 or greater. The absolute one-year risk thresholds are 0.1834% for PrismNN and 0.2048% risk for PrismLR. SIR 5 or greater was chosen because it is comparable to the current screening inclusion threshold for individuals with an inherited predisposition.
  measure: PRISM performance metrics of high-risk group for direct screening
  time frame: at 2 years
  description: To evaluate sensitivity, specificity, PPV, and SIR for patients identified as high-risk by PRISM. Numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location. Risk threshold determined based on Standardized Incidence Ratio of 5 or greater. The absolute one-year risk thresholds are 0.1834% for PrismNN and 0.2048% risk for PrismLR. SIR 5 or greater was chosen because it is comparable to the current screening inclusion threshold for individuals with an inherited predisposition.
  measure: PRISM performance metrics of high-risk group for direct screening
  time frame: at 3 years
  description: To evaluate sensitivity, specificity, PPV, and SIR for patients identified as high-risk by PRISM. Numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location. Risk threshold determined based on Standardized Incidence Ratio of 5 or greater. The absolute one-year risk thresholds are 0.1834% for PrismNN and 0.2048% risk for PrismLR. SIR 5 or greater was chosen because it is comparable to the current screening inclusion threshold for individuals with an inherited predisposition.
  measure: PRISM performance metrics of medium-risk group for biomarker testing
  time frame: 6 months from index date
  description: To evaluate sensitivity, specificity, PPV, and SIR for patients identified as medium-risk by PRISM. Numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location. Risk threshold determined by specificity 85%, with sensitivity around 46%. The absolute one-year risk thresholds are 0.0574% for PrismNN and 0.0564% for PrismLR. Prism operates as a tiered system for identifying individuals in need of screening with this lower risk threshold.
  measure: PRISM performance metrics of medium-risk group for biomarker testing
  time frame: at 1 year
  description: To evaluate sensitivity, specificity, PPV, and SIR for patients identified as medium-risk by PRISM. Numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location. Risk threshold determined by specificity 85%, with sensitivity around 46%. The absolute one-year risk thresholds are 0.0574% for PrismNN and 0.0564% for PrismLR. Prism operates as a tiered system for identifying individuals in need of screening with this lower risk threshold.
  measure: PRISM performance metrics of medium-risk group for biomarker testing
  time frame: at 2 years
  description: To evaluate sensitivity, specificity, PPV, and SIR for patients identified as medium-risk by PRISM. Numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location. Risk threshold determined by specificity 85%, with sensitivity around 46%. The absolute one-year risk thresholds are 0.0574% for PrismNN and 0.0564% for PrismLR. Prism operates as a tiered system for identifying individuals in need of screening with this lower risk threshold.
  measure: PRISM performance metrics of medium-risk group for biomarker testing
  time frame: at 3 years
  description: To evaluate sensitivity, specificity, PPV, and SIR for patients identified as medium-risk by PRISM. Numbers will be calculated for the whole population and groups stratified by age, sex, race, and geographical location. Risk threshold determined by specificity 85%, with sensitivity around 46%. The absolute one-year risk thresholds are 0.0574% for PrismNN and 0.0564% for PrismLR. Prism operates as a tiered system for identifying individuals in need of screening with this lower risk threshold.
  measure: Timing of incident PDAC occurrence
  time frame: 6 months from index date
  description: To evaluate how long in advance before PDAC occurrence should be expected for PRISM models to make high-risk predictions. Distribution plots of the date of PDAC incidence for high/medium-risk groups (defined in Outcome 3 and Outcome 4) will be created.
  measure: Timing of incident PDAC occurrence
  time frame: at 1 year
  description: To evaluate how long in advance before PDAC occurrence should be expected for PRISM models to make high-risk predictions. Distribution plots of the date of PDAC incidence for high/medium-risk groups (defined in Outcome 3 and Outcome 4) will be created.
  measure: Timing of incident PDAC occurrence
  time frame: at 2 years
  description: To evaluate how long in advance before PDAC occurrence should be expected for PRISM models to make high-risk predictions. Distribution plots of the date of PDAC incidence for high/medium-risk groups (defined in Outcome 3 and Outcome 4) will be created.
  measure: Timing of incident PDAC occurrence
  time frame: at 3 years
  description: To evaluate how long in advance before PDAC occurrence should be expected for PRISM models to make high-risk predictions. Distribution plots of the date of PDAC incidence for high/medium-risk groups (defined in Outcome 3 and Outcome 4) will be created.
  measure: Tumor stage at PDAC diagnosis
  time frame: 6 months from index date
  description: stage at diagnosis per tumor registry/pathology report
  measure: Tumor stage at PDAC diagnosis
  time frame: at 1 year
  description: stage at diagnosis per tumor registry/pathology report
  measure: Tumor stage at PDAC diagnosis
  time frame: at 2 years
  description: stage at diagnosis per tumor registry/pathology report
  measure: Tumor stage at PDAC diagnosis
  time frame: at 3 years
  description: stage at diagnosis per tumor registry/pathology report
  arm group label: prospective general opulation cohort
  description: Males and females age >= 40 years, without a personal history of PDAC or current PDAC, with at least 2 clinical encounters to the HCO within the year prior to the study start date.
  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
  study pop: 
  sampling method: Non-Probability Sample
  criteria: 
  gender: All
  minimum age: 40 Years
  maximum age: 100 Years
  healthy volunteers: Accepts Healthy Volunteers
  last name: Limor Appelbaum, MD
  role: Principal Investigator
  affiliation: Beth Israel Deaconess Medical Center
  facility: 
  country: United States
  responsible party type: Principal Investigator
  investigator affiliation: Beth Israel Deaconess Medical Center
  investigator full name: Limor Appelbaum
  investigator title: Staff Scientist
  sharing ipd: No