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

Not Applicable

Recruiting

• Conditions: Transthyretin Amyloidosis
• Interventions: Device: Computer algorithm for ATTR

• Registration Number: NCT04569903
• Lead Sponsor: Yale University

Brief Summary

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

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.

Basic Information
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Recruitment & Eligibility
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Study & Design
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Trial Locations

Study Timeline

• Study First Submitted: 2020-09-24
• Study First Submitted QC: 2020-09-24
• Study First Posted: 2020-09-30
• Status Verified: 2024-08
• Study Start: 2024-08-01
• Last Update Submitted: 2024-08-14
• Last Update Posted: 2024-08-15
• Primary Completion: 2026-02
• Study Completion: 2026-02

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 100

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).

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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

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Study & Design

• Study Type: INTERVENTIONAL
• Study Design: SINGLE_GROUP

Arm && Interventions

Group	Intervention	Description
Computer algorithm for ATTR	Computer algorithm for ATTR	Patients will be evaluated for the identification of ATTR Amyloidosis through a claims-based algorithm

Primary Outcome Measures

Name	Time	Method
Diagnostic performance of algorithm in identifying patients with ATTR amyloidosis	2 years	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.

Secondary Outcome Measures

Name	Time	Method
Proportion of diagnosed patients	2 years	The proportion or rate of patients who were previously undiagnosed of ATTR Amyloidosis

Trial Locations

Locations (1)

Yale New Haven Hospital; 🇺🇸 New Haven, Connecticut, United States