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

Study Status: NOT_YET_RECRUITING
Recruit Status: NOT_YET_RECRUITING
Study Type: INTERVENTIONAL

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

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

Detailed Summary:

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.

Sponsor: Yale University

Current Primary Outcome: 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.

Original Primary Outcome: 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.

Current Secondary Outcome:

Original Secondary Outcome:

Information By: Yale University

Dates:
Date Received: September 24, 2020
Date Started: December 01, 2023
Date Completion: December 01, 2023
Last Updated: September 12, 2023
Last Verified: September 01, 2023