Diagnostic Trends and Geographic Health Care Disparities Among Patients With Transthyretin Amyloid Cardiomyopathy.

Nonstandard Abbreviations and Acronyms

transthyretin amyloid cardiomyopathy

variant transthyretin amyloid cardiomyopathy

wild‐type transthyretin amyloid cardiomyopathy

rural–urban commuting area

Clinical Perspective What Is New? These results show that the diagnosed prevalence of transthyretin amyloid cardiomyopathy increased ≈4‐fold from 2017 to 2023, including a comparable 4‐fold increase in the Black population. Pronounced geographic disparities were evident, with large areas of the country experiencing considerably lower diagnostic rates and limited access to specialized care. What Are the Clinical Implications? Identifying these regional disparities may inform targeted strategies to improve diagnosis and reduce the substantial population of undiagnosed patients beyond the immediate reach of amyloid centers.

Transthyretin amyloid cardiomyopathy (ATTR‐CM) is a rare, underdiagnosed, life‐threatening systemic disease that presents as a restrictive cardiomyopathy with cardiac symptoms, neurologic symptoms, or both. 1 ATTR‐CM includes both wild‐type (ATTRwt‐CM) and pathogenic variant (ATTRv‐CM) forms of the disease. 1 , 2 The true incidence and prevalence of ATTR‐CM is unknown. ATTR‐CM has historically been considered a rare disease, though identification has become more common with recent advances in noninvasive cardiac imaging, genetic testing, and diagnostics. 2

Timely and accurate diagnosis of ATTR‐CM remains a challenge due to disease heterogeneity, limited awareness, and a clinical presentation that overlaps with more common conditions. 2 Common symptoms of ATTR‐CM include fatigue, heart failure, dyspnea on exertion, and pulmonary congestion. 2 ATTR‐CM is frequently misdiagnosed as hypertensive heart disease, hypertrophic cardiomyopathy, or aortic stenosis. 2 Patients with delays in diagnosis may be more likely to experience detrimental effects on cardiac function, including worsening clinical status, higher rates of heart failure, and increased risk for arrhythmias. 3 , 4 Diagnostic delays, misdiagnoses, or both may also exacerbate the impact of ATTR‐CM on health‐related quality of life and may increase the use of costly health care resources, such as emergency department visits, hospitalization, diagnostics, and medications. 4 , 5 , 6 This may potentially have a disproportionate effect on Black patients and those with lower socioeconomic status who have a greater risk for underdiagnosis and more adverse outcomes. 7

Access to cardiology providers and specialized amyloid centers may play a role in the diagnosis of ATTR‐CM. However, the relationship between proximity to these services and ATTR‐CM diagnosis is not well understood. A recent study of county‐level estimations of practicing cardiologists in the United States using data from HealthLink Dimensions demonstrated that 46.3% of counties overall and 86.2% of rural counties had no cardiologists. 8 A prior analysis of Medicare fee‐for‐service claims data from 2000 to 2012 found diagnosis of cardiac amyloidosis (both amyloid light chain and ATTR‐CM) clustered in the Northeast and Midwest around conventional amyloid centers at the time. 9 The current study sought to assess the diagnostic trends and the geographic distribution of amyloid centers and cardiology providers, with the goal of elucidating ongoing diagnostic disparities of ATTR‐CM in the contemporary era of disease‐modifying treatment.

Methods

Data Availability and Access

The data that support the findings of this study were used under license from Komodo Health and derived from the Komodo Healthcare Map. Due to data use agreements and their proprietary nature, restrictions apply on the availability of the data. Further information is available from the sponsor of the study, BridgeBio Pharma, Inc. (San Francisco, CA). All authors had full access to the data in the study and take responsibility for its integrity and the data analysis.

Study Design

This was a cross‐sectional geospatial analysis of amyloid centers and cardiology providers in the United States and a retrospective cohort analysis of patients with ATTR‐CM in the United States from the Komodo Healthcare Map. The study period was from January 1, 2016, to June 30, 2024, and the patient identification period was from July 1, 2016, to June 30, 2024. The Komodo Healthcare Map is composed of medical and prescription claims data from several sources. It is characterized by proprietary partnership with >150 key national payers and consortiums, representing >150 million payer complete lives. The database is representative of the US commercial‐, Medicare‐, and Medicaid‐insured populations. The Komodo Healthcare database complies with the Health Insurance Portability and Accountability Act. Given the anonymized, deidentified nature of the data, patient consent was not possible or required, and institutional review board approval to conduct this study was not necessary. Only aggregate cohort‐level results were reported, without identification of any health care providers or health care facilities.

Patients

Patients were included if they were aged ≥50 years on the index date and had ≥2 claims with an amyloidosis diagnosis code (E85.0, E85.1, E85.2, E85.4, E85.82) occurring on separate days and ≥2 claims for a cardiac‐related International Classification of Diseases , Tenth Revision , Clinical Modification ( ICD‐10‐CM ) code; or ≥1 claim for tafamidis based on National Drug Codes. Patients were excluded if they had >1 ICD‐10‐CM diagnosis code of light chain amyloidosis (E85.81) on different dates during the study period, or had >1 claim (on separate days) for multiple myeloma or received hematopoietic stem cell transplantation at any time during the study period (Table S1 ). All patients were required to have ≥6 months (182 days) of continuous enrollment in a closed claims source before the index date, defined as the first occurrence of an ATTR‐CM diagnosis code or tafamidis claim, and live in the 50 US states. Comorbidities were measured during the 6 months before the index date on the basis of ICD‐10‐CM diagnostic codes (Table S1 ).

The type of ATTR‐CM was determined on the basis of the ATTR‐CM diagnosis codes on claims occurring during the identification period. To be considered ATTRv‐CM, a patient was required to have ≥2 heredofamilial amyloidosis codes (on separate days) during the identification period. If a patient had ATTRwt‐CM codes and 0 to 1 heredofamilial amyloidosis codes during the identification period, the patient was considered ATTRwt‐CM. Patients were labeled as “unknown” if they had 1 heredofamilial amyloidosis code and no ATTRwt‐CM codes (with tafamidis claim) or if they only had a tafamidis claim and no relevant ATTR‐CM codes during the identification period.

Outcome Measures

The primary objective of the study was to descriptively evaluate temporal trends and potential geographic and racial differences in the prevalence and demographics of ATTR‐CM over time in the modern treatment era. We sought to assess the relation of ATTR‐CM prevalence by region and in relation to the availability of cardiologists and of amyloid specialists.

Geographic regions were separated into Northeast, Midwest, West, and South on the basis of divisions recommended by the US census 10 and by rural–urban commuting area (RUCA) group, where rural was defined as a RUCA code of 4 to 9, and frontier was defined as a RUCA code of 10. 11 While there is no definitive count for all amyloid centers in the United States, amyloid centers were classified on the basis of information provided by the International Society of Amyloidosis, Amyloidosis Foundation, and Amyloid Research Consortium (Table S2 ). 12 , 13 , 14 Cardiologists were identified using the specialization variables in the Komodo Healthcare Map. 15 We assessed the geospatial distribution of amyloid centers in the United States; a map of cardiologist deserts in the United States, defined as areas that completely lack cardiologists; the prevalence of ATTR‐CM overall and over time, using the Komodo Healthcare database as the denominator; and expected distance to amyloid centers based on census data, stratified by urban versus rural. Patient location was calculated using proxy variables. The Komodo Healthcare Map is limited to a 3‐digit zip code for patients. As a proxy for patient location, a 5‐digit zip code was imputed from either the patient's outpatient primary care provider claims or pharmacy (mail‐order pharmacies excluded). Distance was calculated from patient location proxy to the nearest amyloid center and cardiologist zip code.

Statistical Analysis

Categorical variables (eg, sex and race) were summarized by frequency and percentage. Continuous variables (eg, age) were summarized by mean±SD, median, quartiles, minimum, and maximum. Demographics were stratified by region, ATTR‐CM type, year of diagnosis, and RUCA group; prevalence was stratified by region and race. Statistical analyses were descriptive in nature; R statistical software (R version 4.2.1; R Foundation for Statistical Computing, Vienna, Austria) was used for analytics. 16

To calculate annual prevalence (2017–2023), the number of patients with an ATTR‐CM diagnosis within each year of interest (in addition to previously diagnosed patients who had not yet died) was divided by the total population at risk. More specifically, if previously diagnosed patients were alive or enrolled for ≥1 day in the given year, they were included in the numerator. All patients with ≥1 day of enrollment for that year of interest within the Komodo Healthcare database were included in the denominator (“population at risk”). For mapping prevalence at the zip code level, the denominator used the US population estimates for zip codes based on the American Community Survey.

Results

Baseline Demographics and Patient Characteristics

Overall, 75 000 patients were diagnosed with ATTR‐CM during the identification period; 14 980 patients met the eligibility criteria, and 53 113 were excluded due to <6 months of continuous enrollment in a closed claims source before the index date, likely driven by a large increase in recent diagnoses (Figure S1 ). Mean age was 74.8±9.7 years, 62.3% of patients were men, 54.1% were White individuals, and 28.8% were Black individuals (Tables 1 and 2 ). The diagnosis of ATTRwt‐CM was the most common (88.6%), followed by ATTRv‐CM (10.0%) and ATTR‐CM of unknown type (1.5%). Regional representation was highest from the Northeast (n=5893 [39.3%]), followed by the Midwest (n=3571 [23.8%]), the South (n=3493 [23.3%]), and the West (n=2023 [13.5%]). The majority of patients (90.8%) lived in an urban area (Table 1 ). Comparatively, 80% of the general US population lives in an urban area. 17 When stratified by year, there was an increase in mean age over time (from 73.0 years in 2016–2018 to 75.8 years in 2022–2024) and a decrease in the proportion of patients with ATTRv‐CM (from 17.0% in 2016–2018 to 6.7% in 2022–2024). The proportion of patients with comorbidities was generally consistent over time, with some increasing over time (chronic kidney disease, systolic and diastolic heart failure, obesity) and others decreasing over time (stroke) (Table 2 ).

A total of 80 amyloid centers were identified, 17 each in the Northeast and Midwest, 20 in the West, and 26 in the South (Table 3 ). The majority of amyloid centers were located in urban areas, with only 1 amyloid center located in a rural area and none located in a frontier area. California was the state with the highest number of amyloid centers (n=8), followed by New York (n=6), and Illinois and North Carolina (n=5 each) (Figure S2 ). The mean number of amyloid centers per capita was 0.24 per 1 000 000 and was highest in the Northeast (0.30) and lowest in the South (0.21) (Table 3 ).

Assuming homogeneous distribution of amyloid within the population, the expected weighted distance to an amyloid center in the contiguous United States was 67.7 miles, being shortest in the Northeast (35.9 miles) and longest in the South (83.1 miles) (Table 3 ). Comparatively, the mean distance of patients with ATTR‐CM in the study to a cardiology provider was 4.3±10.4 miles and to an amyloid center was 48.5±59.5 miles (Table 3 ), suggesting geographic clustering. Distance to a cardiology provider was shortest in the Northeast (mean, 2.8±6.2 miles) and longest in the Midwest (mean, 7.1±15.0 miles). Distance to an amyloid center was shortest in the Northeast (mean, 32.3±39.3 miles) and longest in the South (mean, 75.0±71.5 miles) (Table 3 ).

ATTR ‐ CM Geographic Prevalence and Trends Over Time

The diagnosed prevalence of ATTR‐CM during the time of the study was 35.68 per 100 000 people and was highest among Black patients (102.17), followed by patients of other races (55.77) (Table 4 ). ATTR‐CM prevalence in White patients was 33.54 per 100 000 people. Prevalence was highest in the Northeast (52.63) and lowest in the West (26.97) and South (27.24). In the Northeast, 59.8% of patients were White individuals and 24.9% were Black individuals; in the South, 41.2% of patients were White individuals and 40.4% were Black individuals (Table 1 ). The prevalence of ATTR‐CM increased steadily over time, from 10.52 per 100 000 people in 2017 to 42.51 in 2023, and varied by race (Figure 1A ). The largest increase in prevalence over time was seen in Black patients. The prevalence of ATTR‐CM also increased over time by region, with the largest increase seen in the Northeast (Figure 1B ).

Geographically, the prevalence of ATTR‐CM was highest in the Northeast (Maine, 69.74 per 100 000 people; Massachusetts, 64.28; New York, 58.89; District of Columbia, 48.03; New Jersey, 47.18; Pennsylvania, 45.47; Connecticut, 44.06) but was lower in the Midwest (Iowa, 11.71; South Dakota, 14.12; Indiana, 19.41; Missouri, 19.94; Nebraska, 20.57), which generally correlated with the relative distribution of amyloid centers in those areas (Figure 2A ). Large areas of the country were identified, particularly in the Midwest, where there were cardiologist deserts with limited cardiology providers and amyloid centers. The analysis also identified clusters of White patients with ATTR‐CM (eg, in Montana, Nebraska, New Mexico, North Dakota, South Dakota, and Wyoming) who were being diagnosed despite further distance from an amyloid center (Figure 2B ). In Black patients with ATTR‐CM, similar clusters inside cardiologist deserts were not observed, with prevalence being limited to areas with amyloid centers (Figure 2C ).

Discussion

In this report, we assessed diagnostic trends and geographic disparities of ATTR‐CM in a large, nationwide, contemporary cohort of 14 980 patients in the United States. With the advent of Food and Drug Administration–approved ATTR‐CM therapy in 2019, the diagnosed prevalence of ATTR‐CM increased ≈4‐fold from 2017 to 2023 (from 11 to 43 cases per 100 000 people). This increase in prevalence likely reflects both improved disease awareness, leading to more new diagnoses, as well as patients living longer with the disease due to improved treatment options. Prevalence was highest among Black patients, with 118 cases per 100 000 people in 2023 (3‐fold higher than White patients driven by a higher proportion of individuals with ATTRv‐CM) and a 4‐fold increase over the study period. Geographically, prevalence was highest in the Northeast and lowest in the West and South, with evidence of clustering around amyloid centers that were predominantly located in urban areas. Geospatial analysis of amyloid centers found that large areas of the country, such as in the Midwest, had a limited number of cardiology providers and amyloid centers. These cardiology deserts, which were observed regardless of race, are likely to result in fewer patients with ATTR‐CM being diagnosed than would be expected if more cardiology providers and amyloid centers were available.

While geographic and racial differences in the diagnosis of ATTR‐CM and mortality rates of ATTR‐CM have been demonstrated by other epidemiologic studies, this is the first large‐cohort study to show that these geographic disparities persist in the contemporary treatment era. In a prior analysis of patients aged >65 years in the Medicare database from 2000 to 2012, patients with cardiac amyloidosis (combining both light‐chain amyloidosis and ATTR‐CM) were also found to cluster around historic amyloid centers at the time in New York, Boston, and Rochester. 9 Since then, the number of amyloid centers has grown considerably, as well as the diagnostic rate of ATTR‐CM, as evidenced by our study. However, there remain large areas of the country with persistently poor access to amyloid specialists, even cardiologists in many cases.

Prior studies have shown that reduced access to cardiologists in the general population is associated with poor outcomes. County‐level estimates of cardiologists in the United States using data from HealthLink Dimensions demonstrated that 46.3% of counties had no cardiologists, and 86.2% of rural counties had no cardiologists. 8 The average round‐trip distance to the nearest cardiologist was 16.3 miles in counties with cardiologists, but was 87.1 miles in counties without cardiologists. 8 Counties without cardiologists had higher age‐adjusted cardiovascular mortality rates compared with counties that had cardiologists. 8 In the current study, mean distance to an amyloid center was 48.5 miles, resulting in an average round‐trip distance of 97 miles, similar to counties without cardiologists in the prior study. While the prolonged distance brings up concerns with access to care, it conversely suggests geographic clustering. On the basis of census data, the expected weighted distance from an amyloid center was 68 miles, or 136 miles round trip. This would imply that patients are more likely to be diagnosed closer to amyloid centers, with patients further from amyloid centers remaining undiagnosed, consistent with the geographic deserts shown on the population density maps. Additional geographic variation was shown with our regional analysis, with distance to a cardiology provider being shortest in the Northeast and longest in the Midwest, and distance to an amyloid center was shortest in the Northeast and longest in the South. This correlated with the mean number of amyloid centers per capita, which was greater in the Northeast and lowest in the South.

Other studies have evaluated geographic and racial variation in amyloid diagnoses on the basis of mortality rates. While ATTR‐CM can affect all individuals, Black patients are disproportionately affected due to increased prevalence of the p.Val142Ile (p.V122I) variant. 18 In an analysis of amyloidosis‐related death from 2018 to 2022 using death certificate data from the Centers for Disease Control and Prevention's Wide‐Ranging Online Data for Epidemiologic Research database, mortality rates were more than twice as high for Black men compared with White men. 19 Higher mortality rates were observed in the Northeast, while lower mortality rates were seen in the South, and counties with the highest mortality rates were concentrated around amyloid centers. 19 This aligns with an earlier study by Alexander et al 20 that demonstrated similar higher age‐adjusted mortality rates in Black men versus White men from 1999 to 2015 using the Centers for Disease Control and Prevention's Wide‐Ranging Online Data for Epidemiologic Research database, with lower mortality rates observed in the South, even though these states had the highest proportions of Black individuals compared with other regions. The geographic variation observed in these studies likely represents increased disease recognition in regions with better access to amyloid centers and cardiology providers rather than increased disease lethality. 19 , 20

Diagnostic delay is a common feature of ATTR‐CM, and patients may see ≥3 physicians before confirming a diagnosis. 21 This is in part because the initial signs and symptoms of ATTR‐CM may be nonspecific and attributed to more common conditions, such as diabetes, hypertension, and chronic kidney disease. 18 Regional differences in practice patterns and access to amyloid centers can be a significant barrier to timely diagnosis of ATTR‐CM. 18 For example, bone scintigraphy is a less invasive, highly specific, and moderately sensitive method for ATTR‐CM diagnosis, allowing for a biopsy‐free diagnosis in the absence of a monoclonal protein after appropriate evaluation (eg, free light chains, serum/urine immunofixation). 22 , 23 However, 1 study observed that patients in the South had fewer claims for bone scintigraphy compared with patients in the Northeast, 23 which aligns with the higher concentration of amyloid centers in the Northeast compared with the South.

A number of strategies for improving the regional differences in ATTR‐CM diagnosis have been suggested. Providing reliable transportation services can significantly enhance health care access for patients in underserved and rural areas. 18 Efforts to promote the development and growth of cardiology providers and amyloid centers in underserved areas is equally important to reduce geographic barriers to treatment. 18 Pairing amyloid centers with smaller practices to streamline the diagnostic and management process may also help underserved populations. Leveraging and expanding telemedicine and telehealth services should also be considered. 8 , 18 Another option is to systematically leverage electronic health records with integrated social determinants of health data to identify at‐risk populations, which could enable health care teams to prioritize resource allocation. 18 Finally, there is a need for education to primary care physicians who care for patients in regions where there are cardiology deserts.

This study was associated with some limitations. First, the prevalence of ATTR‐CM was calculated using an unvalidated ICD‐10‐CM coding algorithm, which may result in misclassification of ATTR‐CM, including misclassification of ATTRv‐CM versus ATTRwt‐CM, as cases were not adjudicated; however, in the absence of a published validated ATTR‐CM coding algorithm, the current algorithm was informed by available literature. 24 , 25 , 26 , 27 Second, because systematic screening was not performed for ATTR‐CM, the true prevalence is likely underestimated. Third, because only 6 months were required for the baseline period to evaluate for comorbidities before amyloid diagnosis, earlier manifestations of the disease, such as carpal tunnel syndrome, are expected to be underestimated by the study design. Fourth, only the first 3 digits of patients' zip codes were available, requiring proxy calculations to be used to determine their location. Fifth, this study did not evaluate geographic disparities in the methods used for ATTR‐CM diagnosis, such as differences in the use of biopsies or tissue typing. A prior retrospective observational cohort study demonstrated that the proportion of patients receiving technetium‐99m pyrophosphate scans varied by geographic region, indicating that there may be regional differences that could be influenced by local availability of testing modalities. 28 Sixth, the list of amyloid centers used in this analysis was a best approximation based on information available at the time of the study from the International Society of Amyloidosis, Amyloidosis Foundation, and Amyloid Research Consortium, and our conclusions may be impacted by our definition of what constitutes an “amyloid center.” Finally, available data were limited in some regions of the West (eg, Alaska and California) due to lack of Komodo Healthcare Map data captured in closed health care systems.

In conclusion, our study demonstrated that the diagnosed prevalence of ATTR‐CM increased ≈4‐fold from 2017 to 2023, including a 4‐fold increase in the Black population, in the setting of increased awareness, advances in noninvasive diagnostic algorithms, and effective therapeutic options. However, there remain geographic disparities in ATTR‐CM prevalence. The majority of patients diagnosed with amyloidosis were located near an amyloid center, but there are still large areas of the country with substantially reduced diagnostic rates and limited access to care. Strategies to address these regional disparities need to be identified, as there likely remains a substantial population of undiagnosed patients outside the immediate radius of amyloid centers.

Sources of Funding

The study was funded by BridgeBio Pharma, Inc. (San Francisco, CA).

Disclosures

J.D.M. is a researcher for Abbott Laboratories and Myocardial Solutions; consultant, advisor, and/or speaker for Alnylam Pharmaceuticals, AstraZeneca, BridgeBio Pharma, Inc., and Pfizer. K.M.A. is a consultant, advisor, and speaker for Alexion Pharmaceuticals, Alnylam Pharmaceuticals, Arbor Biotechnologies, Bayer, BridgeBio Pharm, Inc., Novo Nordisk, and Pfizer. H.D.D., E.N., and N.L. are employees of Genesis Research Group, which received financial compensation from BridgeBio Pharma, Inc., for preparing the research reported in the manuscript. M.U. is an employee and stockholder of BridgeBio Pharma, Inc. and stockholder of Pfizer, Inc. R.K.C. has no disclosures to report.

Supporting information

Figures S1–S2

Tables S1–S2

Data S1: STROBE Statement

Acknowledgments

Under the guidance of the authors, additional medical writing and editorial assistance were provided by Anne Jacobson, MPharm, CMPP, of The Lockwood Group (Stamford, CT) and funded by BridgeBio Pharma, Inc. Editorial support was provided by Erin Mathern, MBA, CMPP, of BridgeBio Pharma, Inc. All of the authors participated in the conception and design of the study and in the analysis and interpretation of data. All of the authors participated in the preparation and final approval of the manuscript.

References

1 Ruberg FL , Grogan M , Hanna M , Kelly JW , Maurer MS . Transthyretin amyloid cardiomyopathy: JACC state‐of‐the‐art review . J Am Coll Cardiol . 2019 ; 73 : 2872 – 2891 . doi: 10.1016/j.jacc.2019.04.003 31171094 PMC6724183

2 Brito D , Albrecht FC , de Arenaza DP , Bart N , Better N , Carvajal‐Juarez I , Conceição I , Damy T , Dorbala S , Fidalgo JC , et al. World Heart Federation consensus on transthyretin amyloidosis cardiomyopathy (ATTR‐CM) . Glob Heart . 2023 ; 18 : 59 . doi: 10.5334/gh.1262 37901600 PMC10607607

3 Bishop E , Brown EE , Fajardo J , Barouch LA , Judge DP , Halushka MK . Seven factors predict a delayed diagnosis of cardiac amyloidosis . Amyloid . 2018 ; 25 : 174 – 179 . doi: 10.1080/13506129.2018.1498782 30169971

4 Nativi‐Nicolau J , Fine NM , Ortiz‐Pérez JT , Brown D , Vera‐Llonch M , Reddy SR , Chang E , Tarbox MH . Clinical manifestations and healthcare utilization before diagnosis of transthyretin amyloidosis . J Comp Eff Res . 2022 ; 11 : 1031 – 1044 . doi: 10.2217/cer-2022-0074 35993313

5 Lane T , Fontana M , Martinez‐Naharro A , Quarta CC , Whelan CJ , Petrie A , Rowczenio DM , Gilbertson JA , Hutt DF , Rezk T , et al. Natural history, quality of life, and outcome in cardiac transthyretin amyloidosis . Circulation . 2019 ; 140 : 16 – 26 . doi: 10.1161/circulationaha.118.038169 31109193

6 Formiga F , García‐Pavía P , Martín Sánchez FJ , Navarro‐Ruiz A , Rubio‐Terrés C , Peral C , Tarilonte P , López‐Ibáñez de Aldecoa A , Rubio‐Rodríguez D . Health and economic impact of the correct diagnosis of transthyretin cardiac amyloidosis in Spain . Expert Rev Pharmacoecon Outcomes Res . 2021 ; 21 : 1127 – 1133 . doi: 10.1080/14737167.2021.1933948 34047214

7 Shankar B , Yanek L , Jefferson A , Jani V , Brown E , Tsottles D , Barranco J , Zampino S , Ranek M , Sharma K , et al. Race and socioeconomic status impact diagnosis and clinical outcomes in transthyretin cardiac amyloidosis . JACC CardioOncol . 2024 ; 6 : 454 – 463 . doi: 10.1016/j.jaccao.2024.05.001 38983379 PMC11229544

8 Kim JH , Cisneros T , Nguyen A , van Meijgaard J , Warraich HJ . Geographic disparities in access to cardiologists in the United States . J Am Coll Cardiol . 2024 ; 84 : 315 – 316 . doi: 10.1016/j.jacc.2024.04.054 38986673

9 Gilstrap LG , Dominici F , Wang Y , El‐Sady MS , Singh A , Di Carli MF , Falk RH , Dorbala S . Epidemiology of cardiac amyloidosis‐associated heart failure hospitalizations among fee‐for‐service Medicare beneficiaries in the United States . Circ Heart Fail . 2019 ; 12 : e005407 . doi: 10.1161/CIRCHEARTFAILURE.118.005407 31170802 PMC6557425

10 U.S. Census Bureau . Census Regions and Divisions of the United States . Accessed October 3, 2025. https://www2.census.gov/geo/pdfs/maps‐data/maps/reference/us_regdiv.pdf .

11 U.S. Department of Agriculture, Economic Research Service . 2020 Rural–Urban Commuting Area (RUCA) Codes . Accessed October 16, 2025. https://www.ers.usda.gov/data‐products/rural‐urban‐commuting‐area‐codes .

12 International Society of Amyloidosis . Amyloidosis Centers by Region . Accessed February 3, 2025. https://www.isaamyloidosis.org/resources .

13 The Amyloidosis Foundation . Patient Resources: US Treatment Centers . Accessed February 3, 2025. https://www.amyloidosis.org/resources#treatment‐centers .

14 Amyloidosis Research Consortium . Treatment Centers & Clinical Trials . Accessed February 3, 2025. https://arci.org/patients‐and‐caregivers/treatment‐centers‐clinical‐trials/ .

15 Motairek I , Chen Z , Makhlouf MHE , Deo S , Salerno P , Mentias A , Nasir K , Rajagopalan S , Al‐Kindi SG . Mapping geographic proximity to cardiologists across the United States . Circ Cardiovasc Qual Outcomes . 2023 ; 16 : e010133 . doi: 10.1161/CIRCOUTCOMES.123.010133 37698011 PMC10592115

16 R Development Core Team . R: A Language and Environment for Statistical Computing . Vienna, Austria : R Foundation for Statistical Computing ; 2010 . ISBN 3‐900051‐07‐0. http://www.R‐project.org

17 U.S. Census Bureau . 2020 Census Urban Areas Facts . Accessed October 3, 2025. https://www.census.gov/programs‐surveys/geography/guidance/geo‐areas/urban‐rural/2020‐ua‐facts.html

18 Fahed G , Collins BN , Cai N , Jimenez JI , Kitakata H , Pino Moreno JE , Alexander KM . Race, genetics, and social determinants of health in transthyretin cardiac amyloidosis: a literature review and call to action . Curr Cardiol Rep . 2025 ; 27 : 66 . doi: 10.1007/s11886-025-02220-z 40042763

19 Fahed G , Jimenez JI , Cai N , Wu X , Edmonds A , Shah K , Kitakata H , Haddad F , Witteles RM , Alexander KM . Socioeconomic and geographic disparities in the reported U.S. amyloidosis mortality from 2018–2022: a persistent underdetection? JACC Heart Fail . 2025 ; 13 : 533 – 535 . doi: 10.1016/j.jchf.2024.11.021 40044390

20 Alexander KM , Orav J , Singh A , Jacob SA , Menon A , Padera RF , Kijewski MF , Liao R , Di Carli MF , Laubach JP , et al. Geographic disparities in reported US amyloidosis mortality from 1979 to 2015: potential underdetection of cardiac amyloidosis . JAMA Cardiol . 2018 ; 3 : 865 – 870 . doi: 10.1001/jamacardio.2018.2093 30046835 PMC6233639

21 Rozenbaum MH , Large S , Bhambri R , Stewart M , Whelan J , van Doornewaard A , Dasgupta N , Masri A , Nativi‐Nicolau J . Impact of delayed diagnosis and misdiagnosis for patients with transthyretin amyloid cardiomyopathy (ATTR‐CM): a targeted literature review . Cardiol Ther . 2021 ; 10 : 141 – 159 . doi: 10.1007/s40119-021-00219-5 33877591 PMC8126532

22 Kittleson MM , Ruberg FL , Ambardekar AV , Brannagan TH , Cheng RK , Clarke JO , Dember LM , Frantz JG , Hershberger RE , Maurer MS , et al. 2023 ACC expert consensus decision pathway on comprehensive multidisciplinary care for the patient with cardiac amyloidosis: a report of the American College of Cardiology Solution Set Oversight Committee . J Am Coll Cardiol . 2023 ; 81 : 1076 – 1126 . doi: 10.1016/j.jacc.2022.11.022 36697326

23 Bourque JM , Schepart A , Bhambri R , Castaño A , O'Brien A , Chen Y , Prasad S , Roy A , Grodin JL . Temporal trends in diagnostic testing patterns for wild‐type transthyretin amyloid cardiomyopathy in the Medicare fee‐for‐service population . Am J Cardiol . 2022 ; 167 : 98 – 103 . doi: 10.1016/j.amjcard.2021.11.048 35022130

24 Witteles RM , Chung H , Dai F , Gutierrez C , Rava A , Swarup S , Ebrahim A , Pankratova C . Trends in diagnostic testing in Medicare patients with wild‐type transthyretin amyloid cardiomyopathy . Front Cardiovasc Med . 2025 ; 12 : 1638380 . doi: 10.3389/fcvm.2025.1638380 41235331 PMC12606490

25 Jaiswal V , Hanif M , Mashkoor Y , Jaiswal A , Prasad T , Rajak K , Khan MS , Mentz RJ , Fonarow GC . Sodium‐glucose cotransporter 2 inhibitor use and outcomes in transthyretin amyloid cardiomyopathy . JACC Adv . 2024 ; 3 : 101405 . doi: 10.1016/j.jacadv.2024.101405 39817087 PMC11734025

26 Damy T , Bourel G , Slama M , Algalarrondo V , Lairez O , Fournier P , Costa J , Pelcot F , Farrugia A , Zaleski ID , et al. Incidence and survival of transthyretin amyloid cardiomyopathy from a French nationwide study of in‐ and out‐patient databases . Orphanet J Rare Dis . 2023 ; 18 : 345 . doi: 10.1186/s13023-023-02933-w 37926810 PMC10626733

27 Huda A , Castaño A , Niyogi A , Schumacher J , Stewart M , Bruno M , Hu M , Ahmad FS , Deo RC , Shah SJ . A machine learning model for identifying patients at risk for wild‐type transthyretin amyloid cardiomyopathy . Nat Commun . 2021 ; 12 : 2725 . doi: 10.1038/s41467-021-22876-9 33976166 PMC8113237

28 Witteles RM , Done N , Sperry BW , Soman P , Alexander KM , Pfefferkorn J , Li T , Udall M , Rosen A , Johnson PT , et al. Technetium‐99m pyrophosphate (PYP) scans among patients in the US: a retrospective real‐world study of demographics, comorbidity profiles, and subsequent transthyretin amyloid cardiomyopathy (ATTR‐CM) diagnosis using a claims database . J Nucl Cardiol . 2025 ; 50 : 102359 . doi: 10.1016/j.nuclcard.2025.102359