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

Sponsor
Yale University (Other)
Overall Status
Not yet recruiting
CT.gov ID
NCT04569903
Collaborator
Alnylam Pharmaceuticals Inc (Other)
100
1
1
2
49.1

Study Details

Study Description

Brief Summary

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

Condition or Disease Intervention/Treatment Phase
  • Device: Computer algorithm for ATTR
N/A

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 Design

Study Type:
Interventional
Anticipated Enrollment :
100 participants
Allocation:
N/A
Intervention Model:
Single Group Assignment
Masking:
None (Open Label)
Primary Purpose:
Screening
Official Title:
Evaluation of a Claims-based Algorithm for the Identification of ATTR Amyloidosis in Medical Records
Anticipated Study Start Date :
Sep 30, 2022
Anticipated Primary Completion Date :
Oct 1, 2022
Anticipated Study Completion Date :
Dec 1, 2022

Arms and Interventions

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

Outcome Measures

Primary Outcome Measures

  1. 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

  1. Proportion of diagnosed patients [2 years]

    The proportion or rate of patients who were previously undiagnosed of ATTR Amyloidosis

Eligibility Criteria

Criteria

Ages Eligible for Study:
18 Years and Older
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
No
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

Contacts and Locations

Locations

Site City State Country Postal Code
1 Yale New Haven Hospital New Haven Connecticut United States 06520

Sponsors and Collaborators

  • Yale University
  • Alnylam Pharmaceuticals Inc

Investigators

  • Principal Investigator: Edward Miller, MD, Yale University

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
Yale University
ClinicalTrials.gov Identifier:
NCT04569903
Other Study ID Numbers:
  • 2000026611
First Posted:
Sep 30, 2020
Last Update Posted:
Aug 12, 2022
Last Verified:
Aug 1, 2022
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No
Additional relevant MeSH terms:

Study Results

No Results Posted as of Aug 12, 2022