Predictive Modeling to Assess Pretest Probability of Transthyretin Gene Variants Based on Demographic Information | oneAMYLOIDOSISvoice
×
Or register here
Global Search

Trusted Resources: Education

Scientific literature and patient education texts

Back to Education / Scientific Articles

Predictive Modeling to Assess Pretest Probability of Transthyretin Gene Variants Based on Demographic Information

key information

source: Circulation: Heart Failure

year: 2023

authors: Joshua Saef, Trejeeve Martyn, Lauren Ives, Lori R. Roth, Justin L. Grodin, Mathew S. Maurer, Mazen Hanna, W.H. Wilson Tang

summary/abstract:

Background:
Transthyretin amyloid cardiomyopathy (ATTR-CM) is a morbid condition, though recent advances in diagnosis and therapy stand to change its natural history. Patients’ TTR genotype may guide family screening as more treatments and preventive strategies become available. An efficient, intuitive means of determining pretest genetic risk may better inform patients/clinicians when pursuing genetic testing.

Methods:
This is a cohort study of 767 consecutive patients diagnosed with ATTR-CM who underwent genetic testing. Classification and regression trees (CART) analysis created a decision tree assessing likelihood of carrying a pathologic TTR gene variant. Age, sex, and race were used as independent variables. Logistic regression was also performed to model probability of pathologic TTR genotype. The primary outcome was the decision tree’s accuracy in 2 separate institutions’ ATTR-CM registry.

Results:
In our study cohort, 208 patients (27.1%) had ATTRv. Race has served most efficiently as the root node followed by age and sex in a CART algorithm, and showed 88.2% accuracy (75.3% sensitivity, 93.9% specificity) in the validation cohort. The odds of having a TTR gene variant were greater in Black patients compared with non-Black patients (OR, 34.6 [95% CI, 20.5–58.3]; P<0.001). Non-Black patients with ATTR-CM aged 69 years and older had <4% risk of having a predisposing mutation.

Conclusions:
This CART algorithm incorporating age, sex, and race was able to determine which patients with ATTR-CM have pathogenic TTR mutations with high specificity. Non-Black patients diagnosed at age 69 years or older with ATTR-CM have a low likelihood to have ATTRv.

organization: Heart Vascular and Thoracic Institute, Cleveland Clinic Foundation, USA; Penn Medicine and Children's Hospital of Philadelphia, University of Pennsylvania, USA; University of Texas Southwestern Medical Center, USA; Columbia University College of Physicians and Surgeons, USA

DOI: 10.1161/CIRCHEARTFAILURE.122.009908

read more

Related Content

To improve your experience on this site, we use cookies. This includes cookies essential for the basic functioning of our website, cookies for analytics purposes, and cookies enabling us to personalize site content. By clicking on 'Accept' or any content on this site, you agree that cookies can be placed. You may adjust your browser's cookie settings to suit your preferences.
More information

The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.

Close

Community Key Collaborator

Support for this landing page is provided by an independent education grant from

Translation of this platform made possible through an independent education grant from

© 2024 rareLife solutions Inc.

To improve your experience on this site, we use cookies. This includes cookies essential for the basic functioning of our website, cookies for analytics purposes, and cookies enabling us to personalize site content. By clicking on 'Accept' or any content on this site, you agree that cookies can be placed. You may adjust your browser's cookie settings to suit your preferences.
More information

The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.

Close