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Genetic Analysis of Hereditary Transthyretin Ala97Ser Related Amyloidosis
Published on: June 9, 2018
Development of a Predictive Tool in Patients With High Pretest Probability for Transthyretin Amyloid Cardiomyopathy
Jocelyn Chai1, Andrew Starovoytov1, Daniel Worsley2
1Division of Cardiology, University of British Columbia, British Columbia, Canada.
Insights
This study developed screening criteria and a predictive tool for transthyretin amyloid cardiomyopathy (ATTR-CM), identifying new diagnoses in 23% of high-risk patients. The tool aids clinicians in refining diagnosis and pretest probability for ATTR-CM.
Area of Science:
- Cardiology
- Medical Diagnostics
- Clinical Research
Background:
- Transthyretin amyloid cardiomyopathy (ATTR-CM) is a frequently underdiagnosed condition contributing to heart failure, arrhythmias, and valvular disease.
- Early identification of ATTR-CM is crucial for timely intervention and improved patient outcomes.
Purpose of the Study:
- To establish screening criteria for identifying patients at high risk of developing ATTR-CM.
- To develop a predictive diagnostic tool for ATTR-CM.
Main Methods:
- A prospective observational registry study conducted between 2019-2022 at two Vancouver academic sites.
- Screening of patients over 60 years old presenting to heart failure, atrial fibrillation, and transcatheter valve clinics.
- Utilizing univariable and multivariable logistic regression to identify predictors of ATTR-CM in patients undergoing technetium-99m-pyrophosphate scintigraphy.
Main Results:
- Out of 2,500 screened patients, 200 were enrolled; 46 (23.0%) were diagnosed with ATTR-CM.
- ATTR-CM patients were older, more frequently male, and exhibited higher NT-proBNP levels, increased posterior wall thickness, low QRS voltages, more atrioventricular block, and higher Doppler E/e' ratios compared to non-ATTR-CM patients.
- A 5-item predictive tool demonstrated high diagnostic accuracy with 89.1% sensitivity and 85.1% specificity (AUC 0.931).
Conclusions:
- Broad screening in high-risk populations identified new ATTR-CM cases in 23% of patients.
- The developed predictive tool can assist clinicians in refining pretest probability and optimizing ATTR-CM diagnosis.
- External validation of the predictive tool in diverse patient populations is recommended.
Background:
Transthyretin amyloid cardiomyopathy (ATTR-CM) is an underdiagnosed cause of heart failure, arrhythmias, and valvular disease.
Objectives:
The objectives of the study were to develop: 1) screening criteria to identify high-risk patients for ATTR-CM; and 2) a predictive tool for ATTR-CM diagnosis.
Methods:
This prospective observational registry (2019-2022) at 2 Vancouver academic sites screened patients aged >60 years presenting to heart failure, atrial fibrillation, transcatheter valve clinics, and cardiologists' offices. Patients meeting high-risk criteria who underwent technetium-99m-pyrophosphate were included. Predictors of ATTR-CM were identified using univariable and multivariable logistic regression.
Results:
Of 2,500 patients screened, 200 were enrolled (mean age 78.4 ± 8.3 years; 64.5% male) with a mean follow-up of 3 years. ATTR-CM was diagnosed in 46 (23.0%), and 7 (3.5%) had immunoglobulin light-chain amyloidosis amyloidosis. Compared to non-ATTR-CM, those with ATTR-CM were older (82.6 ± 7.1 years vs 77.2 ± 8.1 years; P < 0.001), male (80.4% vs 59.7%, P = 0.013), and had higher NT-proBNP (3,633 vs 2018; P = 0.027). ATTR-CM patients had greater posterior wall thickness (14.5 ± 3.2 vs 11.2 ± 1.8; P < 0.001), low QRS voltages (37.0% vs 3.9%; P < 0.001), more atrioventricular block (38.5% vs 19.2%; P = 0.018), and higher Doppler E/e' (18.7 ± 7.6 vs 14.4 ± 6.2, P = 0.001). A 5-item predictive tool (score ≥7) identified patients who had positive ATTR-CM diagnoses (sensitivity 89.1% [95% CI: 80.1%-98.1%], specificity 85.1% [95% CI: 70.4%-90.7%], area under receiver operating characteristic curve 0.931 [95% CI: 0.884-0.978]).
Conclusions:
Broad screening criteria of high-risk populations referred for technetium-99m-pyrophosphate yielded new ATTR-CM diagnoses in 23% of patients. Our predictive tool may guide clinicians in refining pretest probability and optimizing diagnosis for ATTR-CM. External validation in broader populations is warranted.
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