A Simple Score to Identify Increased Risk of Transthyretin Amyloid Cardiomyopathy in Heart Failure With Preserved Ejection Fraction

Key Points

Question  Which patients with heart failure and preserved ejection fraction (HFpEF) have an increased risk of transthyretin amyloid cardiomyopathy (ATTR-CM) warranting technetium Tc 99m pyrophosphate scintigraphy?

Findings  The study team developed and validated an ATTR-CM score comprising of 3 clinical (age, male sex, hypertension diagnosis) and 3 echocardiographic (ejection fraction, posterior wall thickness, relative wall thickness) variables to predict increased risk of ATTR-CM in HFpEF cohorts with variable ATTR-CM prevalence.

Meaning  Because specific and highly effective therapy for ATTR-CM exists, the ATTR-CM score can provide a simple tool to guide use of technetium Tc 99m pyrophosphate scintigraphy and increase recognition and appropriate therapy of ATTR-CM in patients with HFpEF.

Importance  Transthyretin amyloid cardiomyopathy (ATTR-CM) is a form of heart failure (HF) with preserved ejection fraction (HFpEF). Technetium Tc 99m pyrophosphate scintigraphy (PYP) enables ATTR-CM diagnosis. It is unclear which patients with HFpEF have sufficient risk of ATTR-CM to warrant PYP.

Objective  To derive and validate a simple ATTR-CM score to predict increased risk of ATTR-CM in patients with HFpEF.

Design, Setting, and Participants  Retrospective cohort study of 666 patients with HF (ejection fraction ≥ 40%) and suspected ATTR-CM referred for PYP at Mayo Clinic, Rochester, Minnesota, from May 10, 2013, through August 31, 2020. These data were analyzed September 2020 through December 2020. A logistic regression model predictive of ATTR-CM was derived and converted to a point-based ATTR-CM risk score. The score was further validated in a community ATTR-CM epidemiology study of older patients with HFpEF with increased left ventricular wall thickness ([WT] ≥ 12 mm) and in an external (Northwestern University, Chicago, Illinois) HFpEF cohort referred for PYP. Race was self-reported by the participants. In all cohorts, both case patients and control patients were definitively ascertained by PYP scanning and specialist evaluation.

Main Outcomes and Measures  Performance of the derived ATTR-CM score in all cohorts (referral validation, community validation, and external validation) and prevalence of a high-risk ATTR-CM score in 4 multinational HFpEF clinical trials.

Results  Participant cohorts included were referral derivation (n = 416; 13 participants [3%] were Black and 380 participants [94%] were White; ATTR-CM prevalence = 45%), referral validation (n = 250; 12 participants [5%]were Black and 228 participants [93%] were White; ATTR-CM prevalence = 48% ), community validation (n = 286; 5 participants [2%] were Black and 275 participants [96%] were White; ATTR-CM prevalence = 6% ), and external validation (n = 66; 23 participants [37%] were Black and 36 participants [58%] were White; ATTR-CM prevalence = 39%). Score variables included age, male sex, hypertension diagnosis, relative WT more than 0.57, posterior WT of 12 mm or more, and ejection fraction less than 60% (score range −1 to 10). Discrimination (area under the receiver operating characteristic curve [AUC] 0.89; 95% CI, 0.86-0.92; P < .001) and calibration (Hosmer-Lemeshow; χ² = 4.6; P = .46) were strong. Discrimination (AUC ≥ 0.84; P < .001 for all) and calibration (Hosmer-Lemeshow χ²  = 2.8; P = .84; Hosmer-Lemeshow χ²  = 4.4; P = .35; Hosmer-Lemeshow χ² = 2.5; P = .78 in referral, community, and external validation cohorts, respectively) were maintained in all validation cohorts. Precision-recall curves and predictive value vs prevalence plots indicated clinically useful classification performance for a score of 6 or more (positive predictive value ≥25%) in clinically relevant ATTR-CM prevalence (≥10% of patients with HFpEF) scenarios. In the HFpEF clinical trials, 11% to 35% of male and 0% to 6% of female patients had a high-risk (≥6) ATTR-CM score.

Conclusions and Relevance  A simple 6 variable clinical score may be used to guide use of PYP and increase recognition of ATTR-CM among patients with HFpEF in the community. Further validation in larger and more diverse populations is needed.

Heart failure (HF) with preserved ejection fraction (HFpEF) is a common clinical syndrome often affecting older persons with hypertensive heart disease and increased left ventricular (LV) wall thickness (WT) due to hypertrophy.^1,2 Transthyretin amyloid cardiomyopathy (ATTR-CM) is an infiltrative cardiomyopathy that produces LV wall thickening and clinical HF, usually in the setting of relatively preserved ejection fraction and thus is another identifiable etiology of HFpEF.^3,4 Epidemiology studies performing systematic imaging to exclude ATTR-CM in older patients with HFpEF and increased LV wall thickening suggest a prevalence of ATTR-CM between 6%⁵ to 13%⁴ in such patients.

Transthyretin stabilizing therapy improves clinical status and outcomes in patients with ATTR-CM,^6,7 whereas other therapies used in patients with HFpEF may be poorly tolerated in patients with ATTR-CM.⁸ Thus, it is critical to distinguish ATTR-CM from other etiologies of HFpEF. Technetium Tc 99m pyrophosphate single-photon emission-computed tomography (PYP) allows accurate, noninvasive diagnosis of ATTR-CM when PYP false positives are excluded and appropriate evaluations rule out light-chain amyloidosis.⁹ However, PYP imaging for ATTR-CM in unselected patients with HFpEF would be inefficient and costly. A simple clinical tool to better discriminate which patients with HFpEF should be assessed for ATTR-CM is needed.

We sought to derive and validate a simple clinical score that could predict increased risk of ATTR-CM in patients with HFpEF to inform medical decision-making on PYP imaging. Furthermore, given recent concern that unrecognized ATTR-CM in clinical trial cohorts may have affected HFpEF trial outcomes,¹⁰ we quantified the frequency of patients at high risk for ATTR-CM in large, contemporary HFpEF clinical trials.

The study was approved by the Mayo Clinic Institutional Review Board and funded by the Mayo Clinic Department of Cardiovascular Medicine. Only patients who had provided written informed consent for use of their medical records for research were included. Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) reporting guidelines were followed.

All patients with PYP at Mayo Clinic (Rochester, Minnesota) since 2013 who had echocardiography within 1 year of PYP, an ejection fraction (EF) of 40% or more, validated HF diagnosis (eTable 1 in the Supplement), and no history of an EF less than 40% or of HF due to valve disease comprised the PYP-referral cohort (n = 666, eFigure 1 in the Supplement) and were randomly assigned to derivation (n = 416) or validation cohorts (n = 250). Methodology for obtaining PYP, electrocardiogram, and echocardiographic parameters is described in the eMethods in the Supplement.

A separate community HFpEF validation cohort (n = 286, eFigure 1 in the Supplement) was composed of southeastern Minnesota residents who were 60 years of age or older with a validated HF diagnosis, an EF of 40% or more, and LV septal and/or posterior WT of 12 mm or more who were enrolled in a community-based ATTR-CM epidemiology study where all patients underwent PYP.⁵

A genetic variant predisposing to hereditary ATTR-CM (ATTRm-CM) is more common in Black people and evaluation patterns for ATTR-CM may vary by institution. Thus, we validated the ATTR-CM score in a more racially diverse, external HFpEF cohort (EF ≥40%, eFigure 1 in the Supplement) who had undergone PYP at Northwestern University Feinberg School of Medicine (Chicago, Illinois) (external PYP-referral validation cohort, n = 66; approved by the Northwestern University Institutional Review Board). All patients with positive PYP in all cohorts were evaluated by amyloid specialists who assessed accuracy of PYP and excluded light chain-amyloidosis (AL) (eMethods in the Supplement).

Candidate variable selection was based on known ATTR-CM clinical features, uniform availability of variables, and avoidance of collinearity while allowing categorization of variables to be considered in the modeling process (eMethods in the Supplement). Only variables available in the standard evaluation of HFpEF in general clinical practices were considered.

Clinical data were ascertained by International Classification of Diseases, Ninth Revision (ICD-9) and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes in the PYP-referral cohort. Laboratory, echocardiographic, and electrocardiographic data (within 1 year of index PYP) were abstracted. While medial e′ velocity, tricuspid lateral annular plane systolic excursion, and global longitudinal strain are known to be associated with ATTR-CM,⁸ they were missing in 9%, 41%, and 26% of patients, respectively, and were not included as candidate variables. While electrocardiographic variables are associated with ATTR-CM, electrocardiograms were missing in 5% or showed abnormalities precluding assessment of low-voltage or pseudo-infarct pattern (missing, ventricular pacing, or left bundle branch block) in 22% of patients and showed atrial fibrillation (precluding assessment of PR interval) in 31% of patients. Thus, electrocardiographic variables were not included as candidate variables. High-sensitivity cardiac troponin T (hscTnT) was missing in 48% of patients and N-terminal pro-brain natriuretic peptide (NTproBNP) was missing in 4% of patients and were not included but their incremental value to the final score was assessed in sensitivity analyses. In the community cohort, comorbidities were collected by patient interview and manual chart review.⁵

The analytic plan was to derive a multivariable logistic regression model that could be summarized with a simple point-based additive score (eMethods in the Supplement). Thus, continuous variables were transformed to categorical variables using cutoffs that represented the medians in the PYP-referral derivation set or previously established partition values. Candidate variables were analyzed with univariate logistic regression to determine association with ATTR-CM. Those with a P value less than .05 were then entered into the multivariable logistic model. Sequential backward elimination was used to determine variables independently associated with ATTR-CM. Variables that were statistically significant in the final model that resulted in only minor improvements (AUC < .005) in the area under the receiver-operating characteristic (ROC) curve (AUC) were excluded to provide a parsimonious model. Using variable β estimates, a weighted ATTR-CM risk prediction score was then constructed.¹¹ The optimal score cutoff was identified by the balance of sensitivity and specificity in the derivation cohort. The final score was then evaluated in the 3 validation cohorts.

To explore the potential burden of ATTR-CM in contemporary HFpEF clinical trials, we evaluated the prevalence of a high-risk ATTR-CM score in participants with available data for all score variables. Accordingly, analysis was restricted to trial participants enrolled in echocardiography substudies. Data from the Irbesartan in Heart Failure With Preserved Ejection Fraction (I-PRESERVE; n = 525), Prospective Comparison of ARNI With ARB on Management of Heart Failure With Preserved Ejection Fraction (PARAMOUNT; n = 272), Prospective Comparison of ARNI With ARB Global Outcomes in Heart Failure With Preserved Ejection Fraction (PARAGON-HF; n = 1019), and Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist (TOPCAT [Americas subset]; n = 645) trials were available.

Group comparisons used 2-sample t tests, Wilcoxon rank-sum test, the Pearson χ² test, or Fisher exact test, as appropriate based on distributional assumptions. Standardized differences (SD) in the distribution of variables between PYP-referral and each of the community-HFpEF and the external PYP-referral validation cohorts were assessed. Univariate logistic regression was used to identify variables that were associated with ATTR-CM diagnosis and ultimately a multivariable logistic regression model was used to construct the weighted score.

Discrimination performance was assessed using the AUC. Calibration was assessed with the Hosmer-Lemeshow goodness-of-fit test where a P greater than .05 indicates consistent calibration with the model. In the community-HFpEF cohort, precision-recall curves were generated¹² with positive predictive value ([PPV], precision) on the y-axis and sensitivity (recall) on the x-axis to better characterize model performance in the lower-prevalence situations most relevant to widespread clinical use. In precision-recall plots, the line of no information is the prevalence of ATTR-CM in the cohort. Plots of PPV and negative predictive value (NPV) across lower ATTR-CM prevalence (0%-10%) were constructed using the predictive characteristics (sensitivity and specificity) of the score observed in the community-HFpEF cohort.

For group comparisons, 2-sided P less than or equal to .05 were considered statistically significant. SDs less than 0.2 were considered to be small differences while those more than 0.8 were considered to be large differences.¹³ Analyses were performed using SAS, version 9.4 (SAS Institute).

In the derivation cohort, 189 of 416 (45%) had ATTR-CM and 16 of 189 (8%) had ATTRm-CM. The median age was 76 years, 333 (80%) were male and 380 (94%) were White (Table 1). By ICD codes, 49 patients (12%) had spinal stenosis and 43 patients (10%) had carpal tunnel syndrome. Median EF was 56% (IQR, 50%-63%). WTs were above normal values and echocardiographic variables were suggestive of impaired myocardial relaxation, elevated LV filling pressures, and right ventricular dysfunction. In the derivation cohort (eTable 2 in the Supplement) and in the 3 validation cohorts (eTables 3, 4, and 6 in the Supplement) age, sex, comorbidities, and electrocardiographic and echocardiographic variables varied by presence or absence of ATTR-CM. The PYP-referral validation cohort (Table 1 and eTable 3 in the Supplement) had similar ATTR-CM prevalence (48%; 11% ATTRm-CM) and clinical characteristics as the derivation cohort.

The community-HFpEF validation cohort was predominantly White (96%) with age, sex, and comorbidity profiles, electrocardiographic findings, and echocardiographic features that were more typical of HFpEF and different from the PYP-referral derivation and validation cohorts (most SD > 0.20; Table 1). This was also reflected in the distribution of H₂FpEF scores whereby the community validation cohort had higher scores compared with the PYP-referral derivation and the PYP-referral validation cohorts (median H2FpEF score 6.0 vs 4.5 and vs 4.0, respectively; P < .001 for both). Despite the lower prevalence of ATTR-CM, the frequency of spinal stenosis and carpal tunnel syndrome were much higher than in the PYP-referral cohorts, likely reflecting differences in comorbidity ascertainment methods.

In the external PYP-referral validation cohort (n = 66), 39% had ATTR-CM (19% ATTRm-CM). Compared with the Mayo PYP-referral cohort, patients were less likely to be male, were more likely to be Black (37%), and had somewhat smaller left ventricles and greater relative WT (eTable 5 in the Supplement).

Of candidate variables assessed in univariate analysis, those that were predictive for ATTR-CM in the referral derivation cohort and entered the multivariable logistic model are presented in Table 2. After sequential backward elimination and exclusion of variables with minimal effect on discriminatory ability, the final model included age, male sex, hypertension diagnosis, EF less than 60%, posterior WT of 12 mm or more, and relative WT more than 0.57 (Table 2) with an AUC (95% CI) of 0.89 (0.86-0.92). The weighted ATTR-CM score constructed with the β estimates of the 6 score variables had a range of −1 to 10 with similar discrimination (AUC 0.88; 95% CI, 0.85-0.91) (Figures 1, and 2A). Model-based probabilities closely matched the observed prevalence for each given score value (goodness-of-fit χ² = 4.6; P = .46), indicating robust calibration (Figure 2B). Using 6 as a high-risk cutoff had a sensitivity of 93% and a specificity 62% (eTable 7 in the Supplement). In sensitivity analyses, in patients with biomarker data, neither NTproBNP nor high-sensitive troponin T were additive to the final multivariable model (median cutoff, OR, 0.7; 95% CI, 0.4-1.2; P = .19 and OR, 1.7; 95% CI, 0.8-3.5; P = .18, respectively).

In the PYP-referral validation cohort, the ATTR-CM score had similar predictive characteristics with strong discrimination (AUC, 0.84; 95% CI, 0.79-0.89) (Figure 2C) and calibration (goodness-of-fit χ² = 2.8; P = .84; Figure 2D). A score of 6 or more had a sensitivity of 89% and a specificity of 56% (eTable 7 in the Supplement).

In the community-HFpEF validation cohort, the ATTR-CM score showed strong discrimination (AUC, 0.84; 95% CI, 0.75-0.94; Figure 2E) and calibration (goodness-of-fit χ² = 4.4; P = .35; Figure 2F) properties. A score of 6 or more had a sensitivity and specificity of 83% and 72%, respectively (eTable 7 in the Supplement). The precision-recall curve (Figure 3A) from the community cohort indicated clinically meaningful reclassification with score of 6 or more having a PPV of 17% vs the line of no information (ATTR-CM prevalence = 6%). Using the sensitivity and specificity of a score of 6 or more in the community cohort, the PPV and NPV at likely prevalence of ATTR-CM among general HFpEF cohorts (≤10%) were calculated and indicated clinically meaningful reclassification with a PPV of 25% at a ATTR-CM prevalence of 10% (Figures 3B and 3C).

In the external PYP-referral validation cohort, the ATTR-CM score showed strong discrimination (AUC, 0.84; 95% CI, 0.75-0.94; Figure 2G) and calibration (goodness-of-fit χ² = 2.5; P = .78; Figure 2H). A score of 6 or more had a sensitivity and specificity of 85% and 58%, respectively (eTable 7 in the Supplement).

In the PYP-referral and community-HFpEF cohorts, most patients with ATTR-CM had early intermediate ATTR-CM disease stage (≥82% Mayo Clinic stage I-II/III). Compared with HFpEF, patients with ATTR-CM tended to have higher H₂FpEF scores, although this did not consistently reach statistical significance (eTables 2-4 in the Supplement). This supports the discriminatory power of the ATTR-CM score for differentiating ATTR-CM (across Mayo Clinic stages) from HFpEF in patients who otherwise have similar or potentially higher H₂FpEF scores.

Demographics of clinical trial participants studied are summarized in eTable 8 in the Supplement. The proportion of patients with a high-risk ATTR-CM score (≥6) in HFpEF clinical trials varied from 11% to 35% in male patients and from 0% to 6% in female patients across trials (eFigure 2 in the Supplement).

In a tertiary medical center cohort of patients with HFpEF referred for PYP, we developed and validated a simple score to predict increased risk of ATTR-CM. We further validated the score in a community cohort of older patients with HFpEF who underwent systematic PYP as part of an epidemiology study and an external, more racially diverse cohort of patients with HFpEF referred for PYP. The ATTR-CM score has a range of −1 to 10, is based on 6 widely available clinical variables (age, sex, hypertension diagnosis, EF, posterior WT, and relative WT), and has strong discrimination and calibration across the derivation and each of the validation cohorts. An ATTR-CM score of 6 or more provides good sensitivity and negative predictive value across a range of ATTR-CM prevalence in 3 different validation cohorts and indicates increased risk for ATTR-CM sufficient to warrant further testing. Precision-recall curves and predictive value vs prevalence plots indicate clinically relevant classification performance, even in cohorts with ATTR-CM prevalence of 10% or less, supporting the value of the ATTR-CM score in the community where the prevalence of ATTR-CM is much lower than tertiary cohorts referred for suspected ATTR-CM. Application of the score in contemporary HFpEF clinical trial cohorts, which often include LV wall thickening in entry criteria, indicate a substantial proportion of participants have a heightened risk of ATTR-CM.

Increased ventricular WT occurs in approximately 50% of patients with HFpEF¹⁴ and is used to support a HFpEF diagnosis.¹⁵ The need for methods to discriminate between HFpEF and ATTR-CM in patients with HF, a preserved EF, and increased WT has not been addressed until recently. Two studies have established the prevalence of ATTR-CM in older persons (≥60 years) with HF, increased WT (≥12 mm), and a normal EF.^4,5A prospective epidemiology study in a largely White population enrolled such patients and found an ATTR-CM prevalence of 6.3% (95% CI, 3.8%-9.8%).⁵ A case series from a Spanish referral hospital enrolled such patients who were hospitalized and found an ATTR-CM prevalence of 13.3% (95% CI, 7.2%-19.5%).⁴

The presence of ATTR-CM has profound therapeutic implications, but it is not clear what collection of ATTR-CM risk factors warrant routine active ascertainment. In our community study,⁵ few patients (1%) were diagnosed clinically despite older age, increased WT, and ready access to PYP scanning. While routine PYP increased diagnosis by 6-fold, scanning all older patients with HF, normal EF, and increased WT would be costly and carry a low positivity rate (6%). The ATTR-CM score offers clinicians a simple tool that can be readily applied at the bedside to predict which patients with clinical HF and normal EF have sufficient risk of ATTR-CM to warrant systematic PYP. As above, available epidemiology studies indicate a prevalence of ATTR-CM in older patients with increased WT of approximately 10% and in this scenario, an ATTR-CM score of 6 or more has a PPV of 25%.

Expert consensus provides a list of clinical features that should alert the clinician to the possibility of ATTR-CM, but their predictive characteristics have not been defined.¹⁶ Echocardiography-based scores predictive of any amyloid cardiomyopathy (AL or ATTR) in a high-prevalence (57%) referral cohort have been described¹⁷ but they were neither ATTR-CM–specific nor externally validated and required sophisticated imaging techniques that undermine universal adoption. In contrast, we rigorously validated a simple ATTR-CM-specific score in well-characterized cohorts of varying ATTR-CM prevalence and used precision-recall curves and predictive value vs prevalence plots to determine score performance even in lower prevalence cohorts. We found that the score worked well in these settings. Furthermore, our analytic plan restricted candidate variables to those that are widely available, easily extractable from clinical records, and familiar to most clinicians. While certain echocardiographic variables like tricuspid lateral annular plane systolic excursion and global longitudinal strain are associated with ATTR-CM,⁸ they may not be familiar to noncardiologists and, even at academic centers included here, were missing in a substantial proportion of patients. Similarly, despite their reported association with ATTR-CM, variables, such as carpal tunnel syndrome and spinal stenosis, are plagued by ascertainment biases that may significantly limit their diagnostic utility (below).

Predictive artificial intelligence algorithms based on ICD diagnosis codes,¹⁸ electrocardiogram^19,20 and/or echocardiogram image analysis²⁰ have been described. However, these were not validated in low-prevalence cohorts,¹⁹ did not distinguish between AL- and ATTR-CM,^19,20 or were reliant on ICD diagnostic codes for case, control, or ATTR-CM risk score ascertainment.^18,20 Our previous epidemiology study⁵ showed that prevalence estimates based on a clinical diagnosis of ATTR-CM vastly underestimate the prevalence of ATTR-CM and thus could affect performance of ICD code–based models. Accordingly, in all our cohorts, we ensured that both cases and controls were definitively characterized, all having undergone PYP, with appropriate clinical evaluation by amyloid experts in patients with a positive PYP to verify or exclude the diagnosis. While use of electronic health record diagnosis codes would lend itself to use of large data sets,²⁰ scores developed without the rigorous case and control ascertainment used here may not perform as well. Furthermore, our score could be applied to large electronic health record databases given the simplicity of the score variables and the ability to use natural language processing on echocardiography reports to extract the echocardiographic variables required for the score.

A substantial proportion of contemporary HFpEF clinical trial participants were found to have a high-risk ATTR-CM score, with a significant subset likely having ATTR-CM as an etiology of their HFpEF, particularly male patients. This finding supports systematic ATTR-CM risk assessment among high-risk ATTR-CM participants in HFpEF trials to exclude patients with undiagnosed ATTR-CM who may not respond to HFpEF therapies.¹⁰

Our study has several strengths, including the use of a community-based cohort and a more racially diverse external PYP-referral validation cohort with a wide range of ATTR-CM prevalence, our robust case and control ascertainment, and rigorous statistical methods. Variable missingness limited use of some reasonable candidate variables but ensured a clinically feasible model applicable to all care settings. The ATTR-CM score was derived in patients with suspected ATTR-CM already referred for PYP imaging and thus may not perform similarly if applied to patients with HFpEF more broadly. The high prevalence of White participants in the PYP-referral cohort does not reflect demographics of the larger US population. Although our validation of the ATTR-CM score in the more racially diverse external PYP-referral cohort tempers this limitation, future prospective validation studies in larger cohorts with higher prevalence of ATTRm-CM and women, as well as with more racial diversity, are needed.

A simple, 6-variable clinical score may identify patients with suspected HFpEF who are at increased risk of ATTR-CM and should undergo additional clinical evaluation to identify or exclude ATTR-CM, a form of HFpEF with a specific etiology that is underrecognized and has specific and highly effective therapy. Further validation of this score is needed.

Accepted for Publication: May 9, 2022.

Published Online: September 7, 2022. doi:10.1001/jamacardio.2022.1781

Corresponding Author: Omar F. AbouEzzeddine, MDCM, MS, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (abouezzeddine.omar@mayo.edu).

Author Contributions: Authors Davies and AbouEzzeddine had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Davies, Redfield, Grogan, Chareonthaitawee, Solomon, Borlaug, AbouEzzeddine.

Acquisition, analysis, or interpretation of data: Davies, Redfield, Scott, Grogan, Dispenzieri, A. Shah, S. Shah, Wehbe, Solomon, Reddy, Borlaug, AbouEzzeddine.

Drafting of the manuscript: Davies, Chareonthaitawee, Reddy, AbouEzzeddine.

Critical revision of the manuscript for important intellectual content: Redfield, Scott, Grogan, Dispenzieri, Chareonthaitawee, A. Shah, S. Shah, Wehbe, Solomon, Borlaug, AbouEzzeddine.

Statistical analysis: Davies, Scott, S. Shah.

Administrative, technical, or material support: Dispenzieri, Chareonthaitawee, S. Shah, Wehbe, Borlaug, AbouEzzeddine.

Supervision: Redfield, Grogan, Dispenzieri, Chareonthaitawee, S. Shah, Solomon, Borlaug, AbouEzzeddine.

Conflict of Interest Disclosures: Dr Grogan reported receiving clinical trial support funds to Mayo Clinic from Akcea, Alnylam, Eidos, Pfizer, and Prothena. Dr Dispenzieri reported being on an advisory board and independent review committee for Janssen; a data monitoring safety committee on oncopeptides for Sorrento; and research grants from Alynlam, Pfizer, Takeda, and Bristol Myers Squibb outside the submitted work. Dr Chareonthaitawee reported consulting for General Electric Healthcare, Medtrace, and BioClinica, and receiving royalties from UpToDate outside the submitted work. Dr A. Shah reported research support not related to this study from Novartis and Philips Ultrasound and consulting fees from Philips Ultrasound. Dr S. Shah reported research grants from Actelion, AstraZeneca, Corvia, Novartis, and Pfizer and has received consulting fees from Abbott, Actelion, AstraZeneca, Amgen, Aria CV, Axon Therapies, Bayer, Boehringer Ingelheim, Boston Scientific, Bristol Myers Squibb, Cardiora, CVRx, Cytokinetics, Edwards Lifesciences, Eidos, Eisai, Imara, Impulse Dynamics, Intellia, Ionis, Ironwood, Lilly, Merck, MyoKardia, Novartis, Novo Nordisk, Pfizer, Prothena, Regeneron, Rivus, Sanofi, Shifamed, Tenax, Tenaya, and United Therapeutics. Dr Wehbe reported receiving research support from the American Society of Nuclear Cardiology and Pfizer outside the submitted work. Dr Solomon reported research grants from Actelion, Alnylam, Amgen, AstraZeneca, Bellerophon, Bayer, Bristol Myers Squibb, Celladon, Cytokinetics, Eidos, Gilead, GSK, Ionis, Lilly, Mesoblast, MyoKardia, National Institutes of Health/National Heart, Lung, and Blood Institute, Neurotronik, Novartis, Novo Nordisk, Respicardia, Sanofi Pasteur, Theracos, and US2.AI and has consulted for Abbott, Action, Akros, Alnylam, Amgen, Arena, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Cardior, Cardurion, Corvia, Cytokinetics, Daiichi Sankyo, GlaxoSmithKline, Lilly, Merck, Myokardia, Novartis, Roche, Theracos, Quantum Genomics, Cardurion, Janssen, Cardiac Dimensions, Tenaya, Sanofi Pasteur, Dinaqor, Tremeau, CellProThera, Moderna, American Regent, Sarepta, Lexicon, Anacardio, Akros, and PureHealth. Dr Borlaug reported receiving grants from the National Heart, Lung, and Blood Institute; research funding from Axon, AstraZeneca, Corvia, Medtronic, GlaxoSmithKline, Mesoblast, Novartis, and Tenax Therapeutics; and consulting fees from Actelion, Amgen, Aria, Boehringer Ingelheim, Edwards Lifesciences, Eli Lilly, Imbria, Janssen, Merck, Novo Nordisk, NGMBio, ShouTi, and VADovations outside the submitted work. Dr AbouEzzeddine reported receiving grants from Pfizer during the conduct of the study outside the submitted work. No other disclosures were reported.