Evaluation of a Claims-based Algorithm for the Identification of Transthyretin-mediated Amyloidosis (ATTR) Amyloidosis in Medical Records

Evaluation of a Claims-based Algorithm for the Identification of ATTR Amyloidosis in Medical Records

The primary objective of this study is to evaluate the diagnostic performance of an algorithm in identifying patients with ATTR amyloidosis.

Study Overview

• Status: Not yet recruiting
• Conditions: Transthyretin Amyloidosis
• Intervention / Treatment: Device: Computer algorithm for ATTR

Detailed Description

A screening strategy to identify ATTR in the large background population of patients with one or more common ATTR manifestations, would be of significant clinical value.

In addition, novel ATTR therapies have been recently made available or are currently in development in late-stage clinical trials. As early diagnosis and treatment is expected to achieve better outcomes, this makes the development and validation of an easily implemented, rapid and electronically-enabled diagnostic algorithm especially important.

A medical and pharmacy claims-based algorithm was developed to potentially identify patients at risk of having ATTR. The goal of this study is to evaluate the ability of the algorithm to identify patients with ATTR by performing diagnostic clinical work up in patients that the algorithm identifies in a large dataset of patients at Yale.

The primary objective of this study is to evaluate the diagnostic performance of the algorithm in identifying patients with ATTR amyloidosis.

The secondary objective of this study is to estimate the clinical benefit of the algorithm, as measured by the added diagnostic value, i.e. the proportion or rate of patients who were previously undiagnosed. The total obtained prevalence will be assessed and informally compared to the referral-based prevalence of ATTR amyloidosis patients at Yale.

• Study Type: Interventional
• Enrollment (Estimated): 100
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Cinthia S De Freitas, RN, BSN; Phone Number: (203)785-6315; Email: cinthia.defreitas@yale.edu

Study Locations

• United States
  • Connecticut
    • New Haven, Connecticut, United States, 06520
      • Yale New Haven Hospital
      • Principal Investigator: Edward Miller, MD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Identified by the ATTR diagnostic algorithm and matched by Yale's list of potential subjects defined as:

  1. subjects within the claims dataset that are predicted to be at risk of having ATTR who are also being managed within YNHHS

  2. patients who need to be contacted and offered additional clinical evaluation to determine whether they have a diagnosis of ATTR (non-hereditary or Hereditary ATTR amyloidosis).

     Exclusion Criteria:

• Patients who have opted out of research in the Epic system will be excluded entirely from the study
• Patients who are pregnant or who may become pregnant

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Screening
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Computer algorithm for ATTR; Patients will be evaluated for the identification of ATTR Amyloidosis through a claims-based algorithm	Device: Computer algorithm for ATTR; Patients will be evaluated for the identification of ATTR Amyloidosis through a claims-based algorithm

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Diagnostic performance of algorithm in identifying patients with ATTR amyloidosis	Potential thresholds for defining diagnostic positivity based on the calculated algorithmic scores will be explored and the corresponding positive predictive value (PPV) will serve as indicator for the diagnostic performance. Negative predictive values (NPV) may be explored if the actual distribution of score data will allow for it.	2 years

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Proportion of diagnosed patients	The proportion or rate of patients who were previously undiagnosed of ATTR Amyloidosis	2 years

Collaborators and Investigators

• Sponsor: Yale University
• Collaborators: Alnylam Pharmaceuticals Inc
• Investigators: Principal Investigator: Edward Miller, MD, Yale University

Study record dates

Study Major Dates

• Study Start (Estimated): April 1, 2024
• Primary Completion (Estimated): February 1, 2026
• Study Completion (Estimated): February 1, 2026

Study Registration Dates

• First Submitted: September 24, 2020
• First Submitted That Met QC Criteria: September 24, 2020
• First Posted (Actual): September 30, 2020

Study Record Updates

• Last Update Posted (Actual): February 12, 2024
• Last Update Submitted That Met QC Criteria: February 8, 2024
• Last Verified: February 1, 2024

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Metabolic Diseases; Proteostasis Deficiencies; Amyloidosis
• Other Study ID Numbers: 2000026611; 000 (Other Identifier: 11.8.23)

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No