Abstract
Introduction
Timely diagnosis and treatment are essential for improving outcomes and quality of life in patients with transthyretin (ATTR) amyloidosis. Early multisystem manifestations are often unrecognized, leading to diagnostic delays and misdiagnosis. Large-scale, multicountry, observational studies are needed to better characterize the real-world trajectory of these patients.
Methods
OverTTuRe, an ANTHOLOGY study, is a retrospective, observational, descriptive, longitudinal, multicountry study using secondary data from claims databases, electronic health records, and healthcare registries. The primary aim of this analysis was to characterize baseline characteristics, early clinical manifestations, and outcomes in patients with hereditary transthyretin (ATTRv) amyloidosis from the United States (US), United Kingdom (UK), Japan, Denmark, and Sweden.
Results
Of 1502 patients identified, the predominant phenotype across countries was ATTRv amyloidosis with polyneuropathy (ATTRv-PN 51.3–63.7%); however, many patients had ATTRv with mixed phenotype (ATTRv mixed 36.3–48.8%). Compared to patients with ATTRv mixed, patients with ATTRv-PN were younger, and a higher proportion were female (36.6–64.1% vs. 19.3–56.4%). Median (interquartile range) time from any initial cardiac or noncardiac manifestation to diagnosis varied across countries; time from any noncardiac manifestation to diagnosis was longest for both phenotypes in the US (ATTRv-PN 2.9 [1.0–4.0] years; ATTRv mixed 2.4 [0.8–3.7] years). Following diagnosis, treatment was not available for most patients. Mortality (ATTRv-PN 14.6–36.2%; ATTRv mixed 21.0–73.0%) and hospitalization (ATTRv-PN 23.5–66.2%; ATTRv mixed 20.8–70.5%) risk varied across countries in the 5 years following diagnosis. Pre- and post-diagnosis healthcare resource utilization was high for both phenotypes.
Conclusions
These findings highlight the heterogeneity of clinical manifestations and outcomes of ATTRv amyloidosis across phenotypes and countries. Patients frequently experience diagnostic delays and numerous healthcare interactions. Elevated clinical suspicion to facilitate earlier diagnosis, together with a multidisciplinary care approach and timely access to targeted therapies, is needed to improve outcomes.
Trial Registration
ClinicalTrials.gov identifier NCT06355934.
Supplementary Information
The online version contains supplementary material available at 10.1007/s40119-026-00450-y.
Keywords: Hereditary ATTR amyloidosis, Observational, Real-world evidence
Plain Language Summary
The goal of this research was to better understand the real-world care of patients with hereditary transthyretin (ATTRv) amyloidosis. Diagnosing this disease can be challenging due to its diverse symptoms, which often lead to delays and misdiagnosis. By studying patients across different countries, researchers aimed to evaluate patterns that could improve early diagnosis and treatment. Researchers identified patients across the US, the UK, Japan, Denmark, and Sweden from 2014 to 2023. Data sources included electronic health records, claims databases, and healthcare registries. Researchers categorized patients into ATTRv with polyneuropathy (ATTRv-PN) and mixed phenotype groups. The study analyzed patient demographics, symptoms, healthcare visits, and treatments. Significant variation in symptoms and outcomes among patients with ATTRv amyloidosis was found. Many patients experienced diagnostic delays of up to 3.5 years, especially those with mixed phenotypes. Healthcare use was high, with frequent outpatient visits and hospital stays. Survival rates varied across countries and phenotypes. Despite available treatment options, many patients did not receive them, especially in the US and UK. These findings highlight the need for increased awareness and better diagnostic practices for ATTRv amyloidosis, including adapting to the diverse disease presentations. Early diagnosis and treatment can improve patient outcomes, reduce healthcare use, and enhance quality of life.
Graphical Abstract
Supplementary Information
The online version contains supplementary material available at 10.1007/s40119-026-00450-y.
Key Summary Points
| Why carry out this study? |
| Limited real-world data are available on the characteristics of patients with transthyretin (ATTR) amyloidosis across different countries, healthcare systems, and phenotypes. |
| OverTTuRe is a retrospective, multicountry, real-world study. This contemporary analysis aimed to characterize baseline characteristics, early clinical manifestations, outcomes, and healthcare resource utilization (HCRU) in patients with hereditary ATTR amyloidosis from the United States, United Kingdom, Japan, Denmark, and Sweden. |
| What was learned from this study? |
| Patients experienced diverse symptoms, and diagnostic delays of up to 3.5 years. |
| Following diagnosis, varying survival and hospitalization rates were observed across countries, and most patients did not receive specific disease-modifying treatment. |
| HCRU was elevated both before and after diagnosis, with high rates of outpatient visits and varying lengths of hospital stays observed across countries. |
Digital Features
There is a graphical abstract available for this article [10.6084/m9.figshare.32083815]
Introduction
Transthyretin (ATTR) amyloidosis is a clinically heterogeneous, progressive, and potentially fatal disease caused by the accumulation of misfolded and aggregated transthyretin (TTR) proteins as amyloid deposits in multiple organ systems. In most cases, cardiomyopathy (CM) and/or peripheral polyneuropathy (PN) are the predominant symptomatic manifestations of the disease [1].
ATTR amyloidosis can either be hereditary (ATTRv) or acquired (ATTR wildtype [ATTRwt]) [1, 2]. ATTRv amyloidosis is an autosomal dominant disorder, and more than 140 disease-causing TTR variants have been described [2–4], including those depicted in Fig. 1. While ATTRv amyloidosis is a global disease, endemic regions exist for certain genetic variants [5].
Fig. 1.
Genotype–phenotype correlation in ATTR amyloidosis. Adapted with modifications from Poli L et al. 2023 under CC, BY 4.0 [6]. ATTR amyloid transthyretin, ATTR mixed ATTR amyloidosis with mixed phenotype, ATTR-CM ATTR amyloidosis with cardiomyopathy, ATTR-PN ATTR amyloidosis with polyneuropathy, ATTRwt wild-type ATTR amyloidosis, TTR transthyretin
Phenotypic variability exists in which certain variants are predominantly associated with neurological manifestations (ATTR-PN), and others with cardiac manifestations (ATTR-CM). In patients with a mixed phenotype, a continuum of possible clinical presentations exists whereby both neurological and cardiac manifestations are observed irrespective of genotype (Fig. 1) [6]. Neurological manifestations associated with ATTR-PN include progressive neuropathic pain, altered sensation, loss of motor function, autonomic dysregulation, e.g., neurogenic orthostatic hypotension, urinary incontinence, and gastrointestinal (GI) and erectile dysfunction [1, 6–8]. Furthermore, glaucoma, renal involvement, and adrenal insufficiency have been described. Average life expectancy from disease onset in patients with ATTRv is approximately 6–12 years [9].
Progressive heart failure is the main cardiac manifestation of ATTR-CM. However, heart failure symptoms are frequently preceded by other cardiac conditions, including atrial fibrillation (AF) or atrial flutter (AFL), bradyarrhythmia (sinoatrial dysfunction and atrioventricular [AV] blocks), troponin-positive chest pain with unobstructed coronary arteries, and aortic valve stenosis [1]. Mean life expectancy for patients with untreated ATTRv amyloidosis with cardiomyopathy (ATTRv-CM) is 2.2–3.5 years [10, 11]
Despite the availability of disease-modifying therapies, patients with ATTR amyloidosis typically experience substantial diagnostic delays, often waiting several years for a correct diagnosis [12]. Approximately 32% of ATTR amyloidosis patients are initially misdiagnosed [13], partially owing to its diverse clinical presentation, which often resembles other conditions, including hypertensive cardiomyopathy [14] and chronic inflammatory demyelinating polyneuropathy [15], and its prominent associated manifestations such as carpal tunnel syndrome and lumbar spinal stenosis [16–21]. Misdiagnoses and delays have been associated with inappropriate treatments and worse clinical outcomes [1, 17].
Real-world studies have advanced the understanding of the epidemiology of ATTR amyloidosis [22, 23]. The Transthyretin Amyloidosis Outcomes Survey (THAOS) was a global, longitudinal, observational study conducted from 2008 to 2023 in 5500 patients diagnosed with ATTR amyloidosis and also asymptomatic carriers of TTR variants [23, 24]; substantial phenotypic and genotypic variability was observed [23–25]. A retrospective cohort study using national population-based registers from four Nordic countries identified 1831 patients with ATTR-CM revealed that patients had multiple healthcare visits pre-diagnosis [22].
Current evidence highlights the heterogeneous presentation of ATTR amyloidosis and its burden on patients and healthcare systems. This emphasizes the need for heightened clinical suspicion, recognition of the constellation of possible symptoms, and early diagnosis and treatment initiation. However, few real-world studies have described patients with ATTR-PN and mixed phenotypes [25, 26] and their clinical outcomes [13, 27, 28]. Studies have most commonly been conducted in Europe and North America, leaving evidence gaps from other world regions [26, 29]. As such, there is a critical need for data from large longitudinal studies including patients with all ATTR amyloidosis phenotypes across disparate countries and healthcare settings.
ANTHOLOGY is a global ATTR amyloidosis evidence generation program, and quality improvement opportunity comprising the OverTTuRe and MaesTTRo multicountry real-world studies that utilize bespoke analyses and leverage collaborations between healthcare professionals and centers of excellence. Program rationale and design have been previously published [30].
The primary aim of this analysis was to describe baseline characteristics, early clinical manifestations, and outcomes in patients with ATTRv amyloidosis identified in secondary healthcare databases from five countries across North America, Europe, and East Asia.
Methods
Study Design
OverTTuRe (NCT06355934) is a retrospective, observational, longitudinal, multicountry study, which utilizes secondary data from electronic health records (EHRs), insurance claims databases, healthcare registries, chart reviews, and disease registries [30, 31].
This analysis was conducted using Optum’s de-identified Clinformatics® Data Mart Database (Optum® CDM) in patients diagnosed with ATTR amyloidosis between January 1, 2017, and December 31, 2023 (United States [US] cohort); January 1, 2014, and December 31, 2022, from Clinical Practice Research Datalink (CPRD) Aurum linked to Hospital Episode Statistics (HES [Copyright © 2025, re-used with the permission of The Health & Social Care Information Centre. All rights reserved]; United Kingdom [UK] cohort); and January 1, 2014, and December 31, 2023, from the Medical Data Vision (MDV) database (Japanese cohort), CROSS-TRACKS [32] (Danish cohort), and CELOSIA study (Swedish cohort). Patients were followed up until database end, loss to follow-up, or death.
Data Sources
This study used secondary data from claims databases, EHRs, and healthcare registries. Different coding systems are used across databases. Code lists were developed specifically for each database. Further information about the specific databases and coding systems for individual countries is provided in Supplementary Material Appendix 1.
Study Population
A diagnostic coding-based algorithm was developed in consultation with the authors and other external experts to identify patients with a diagnosis of ATTR amyloidosis (Supplementary Material Fig. S1). The algorithm has been iteratively refined, including the use of proxy measures, to optimize specificity. Local adaptations were made to the algorithm, where applicable, to account for country-specific coding practices.
Patients aged ≥ 18 years with a first diagnosis code for amyloidosis occurring during the study period with ≥ 1 year of baseline data available before the index date were included. The index date was defined as the date on which the first diagnosis code for amyloidosis was recorded. The reasons for patient exclusion are provided in Supplementary Material Appendix 1. The overall ATTR amyloidosis cohort was segmented by genotype and phenotype based on diagnosis subcodes and/or codes for conditions related to a specific phenotype recorded on, or within 5 years before, the index date. Diagnosis codes recorded on the index date were first used to assign patients to hereditary (International Classification of Diseases, Tenth Revision [ICD-10] E85.0–2, or equivalent) or wild-type (ICD-10 E85.4, E85.8, E85.9, or equivalent) subgroups (Supplementary Material Fig. S2). Patients identified with a diagnosis of ATTRwt amyloidosis were excluded from the current analysis.
Patients were further stratified according to phenotype. Patients were included in the ATTR-PN group if they only had a diagnosis code for ATTRv-PN (i.e., ICD-10 E85.1, or equivalent), or the below stated neurological conditions recorded on, or within 5 years before, the index date, and did not meet the following criteria for ATTR-CM: heart failure, cardiomyopathy, sinoatrial dysfunction, AV block, AF or AFL, or aortic valve stenosis. Patients were included in the ATTR-CM group if they only had a diagnosis code for ATTR-CM (only applies to CPRD and MDV databases), or the above stated cardiac conditions recorded on, or within 5 years before, the index date, and did not meet the following criteria for ATTR-PN: neuropathy (includes mono-, poly-, and other neuropathy, and autonomic neuropathy), and manifestations of autonomic dysfunction. Patients with mixed phenotype met criteria for both ATTR-PN and ATTR-CM. Patients who met neither criterion were considered to have an unknown phenotype and were excluded from further analysis.
Demographics
Patient demographics were assessed on the index date and included age, sex, and index year. The Quan Weighted Charlson Comorbidity Score was used to determine comorbidity status on, or within 1 year before, the index date [33].
Outcomes
Early Clinical Manifestations
Cardiac manifestations described previously were defined using diagnosis codes. Noncardiac manifestations included neuropathy, GI dysfunction, erectile dysfunction, carpal tunnel syndrome (CTS), CTS surgery, and spinal stenosis.
HCRU
HCRU was defined as primary or secondary care outpatient visits, emergency visits, all-cause hospitalizations (ACHs), and heart failure–related hospitalizations (HFHs). Outpatient visits included encounters in an office, home, hospital outpatient clinic, or via telehealth. Of note, in Japan, MDV only captured primary care outpatient visits provided at an MDV hospital, and in Sweden, CELOSIA did not capture any primary care outpatient visits. In addition, in Denmark, primary care outpatient data from CROSS-TRACKS were not included in this analysis. Emergency visits captured those occurring in the emergency department or urgent care facility. ACHs were hospitalizations for any cause with a length of stay (LOS) ≥ 1 day, and HFHs included a diagnosis code for heart failure.
Treatment Patterns
ATTR amyloidosis treatments available during the study period included TTR protein stabilizers (diflunisal, tafamidis) and TTR gene silencers (vutrisiran, patisiran, inotersen). For each country, treatment approval or reimbursement dates were described by phenotype (Supplementary Material Table S1). This allowed identification of patient subgroups based on time of approval or reimbursement relative to the date of diagnosis and their eligibility for each treatment.
All-Cause Mortality (ACM)
Mortality from any cause was defined differently across databases. ACM was ascertained using death information from administrative claims, member disenrollment status marked as deceased, and links to external sources, e.g., the Social Security Death Index in Optum® CDM. For UK data, ACM was determined from recorded death dates in CPRD records, supplemented by links to official death registrations and hospital discharge status from HES. In MDV, ACM was identified using discharge status records and specific death coding within hospital claims data and was limited to in-hospital deaths only. ACM was determined from death information in the Danish Civil Registration System and the National Cause of Death Register for CROSS-TRACKS and the CELOSIA study, respectively.
Statistical Analyses
Patient characteristics and HCRU measures reported in fewer than five patients were suppressed, while clinical manifestations occurring in fewer than five patients for individual countries and groups were excluded. This was to comply with regulations to protect patient privacy.
Analyses were stratified by phenotype: ATTRv-PN, ATTRv-CM, or ATTRv amyloidosis with mixed phenotype (ATTRv mixed). The study was descriptive without inferential hypothesis testing. Baseline patient characteristics were assessed descriptively. Categorical variables were described by frequencies and percentages and mean ± standard deviation (SD) or median and interquartile range (IQR) were used for continuous variables.
Data describing events in the pre-diagnosis period were limited to patients with 5 years of lookback data. The frequency and median (IQR) time between the first recorded diagnosis of cardiac or noncardiac clinical manifestations related to ATTR amyloidosis and the index date were calculated. The number of patients with at least one HCRU encounter and the mean and median number of visits per patient in the 5 years before the index date, were described.
ACM and HCRU outcomes in the post-diagnosis period were assessed from the day after the index date up to 5 years. ACM was assessed by Kaplan–Meier survival analysis. HCRU outcomes were assessed by Aalen–Johansen cumulative incidence methods, with competing risk of death. Incidence rates per person-year (PPY) were described to determine the number of HCRU events in the post-diagnosis period while accounting for variable follow-up time.
Ethical Approval
OverTTuRe was performed in adherence to ethical principles that are consistent with the 1964 Declaration of Helsinki and its later amendments, Good Clinical Practice (GCP) guidelines of the International Conference on Harmonization (ICH), Guidelines for Good Pharmacoepidemiology Practices (GPP), and applicable legislation on non-interventional and/or observational studies. The investigators performed their duties in adherence with local regulations and guidelines governing medical practice and ethics. Ethical approvals were obtained for the use of CELOSIA data from the Swedish Ethical Review Authority, and CRPD and HES data from CRPD’s Research Data Governance. Data from the MDV and Optum® CDM were anonymized or de-identified, so ethical approval was not required. In Denmark, register-based studies require no ethical approval.
Results
Baseline Characteristics
In total, 1502 patients with ATTRv amyloidosis (ATTRv-PN, n = 845; ATTRv mixed, n = 657) were identified from the US (n = 978), the UK (n = 110), Japan (n = 80), Denmark (n = 6), and Sweden (n = 328). Patient disposition by country is shown in Supplementary Material Table S2. Data were not reportable for patients with ATTRv mixed in Denmark due to a small patient sample (n < 5). While the predominant phenotype identified in all countries was ATTRv-PN (51.3–63.7%), a considerable proportion of patients presented with the ATTRv mixed phenotype (36.3–48.8%). A total of 90 patients from the US, 19 from the UK, five from Japan, 19 from Sweden, and five from Denmark were identified as having ATTRv-CM. To comply with patient privacy regulations, patient characteristics and outcomes occurring in fewer than five patients were suppressed. As a result, most measures for patients with ATTRv-CM were not reported due to numerically insufficient sample sizes, and this patient subgroup was excluded from this analysis.
The time trend for ATTRv amyloidosis diagnosis generally increased during the study period in the US and Sweden. In countries with smaller sample sizes such as Japan, this pattern was less clear, and no obvious trend was observed in the UK (Table 1).
Table 1.
Baseline characteristics in patients with ATTRv-PN and ATTRv mixed
| United States | United Kingdom | Japan | Denmark | Sweden | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| ATTRv-PN | ATTRv mixed | ATTRv-PN | ATTRv mixed | ATTRv-PN | ATTRv mixed | ATTRv-PN | ATTRv mixed | ATTRv-PN | ATTRv mixed | |
| Patients, n | 529 | 449 | 60 | 50 | 41 | 39 | 6 | < 5 | 209 | 119 |
| Age at the index datea, years, median (Q1–Q3) | 68.0 (53.0–76.0) | 78.0 (70.0–84.0) | 62.0 (39.0–73.0) | 75.5 (65.0–82.0) | 69.0 (52.0–76.0) | 75.0 (71.0–82.0) | 48.5 (40.8–57.0) | NR | 66.0 (52.0–72.0) | 75.0 (69.0–81.0) |
| Age categories, n (%) | ||||||||||
| < 65 years | 215 (40.6) | 57 (12.7) | 33 (55.0) | 12 (24.0) | 18 (43.9) | 5 (12.8) | 5 (83.3) | NR | 102 (48.8) | 15 (12.6) |
| 65–74 years | 165 (31.2) | 116 (25.8) | 16 (26.7) | 12 (24.0) | 9 (22.0) | 13 (33.3) | NR | NR | 69 (33.0) | 41 (34.5) |
| 75–84 years | 120 (22.7) | 167 (37.2) | 7 (11.7) | 20 (40.0) | 11 (26.8) | 17 (43.6) | NR | NR | 36 (17.2) | 51 (42.9) |
| ≥ 85 years | 29 (5.5) | 109 (24.3) | < 5 | 6 (12.0) | < 5 | < 5 | NR | NR | < 5 | 12 (10.1) |
| Sex, n (%) | ||||||||||
| Male | 190 (35.9) | 203 (45.2) | 32 (53.3) | 27 (54.0) | 26 (63.4) | 17 (43.6) | NR | NR | 123 (58.9) | 96 (80.7) |
| Female | 339 (64.1) | 246 (54.8) | 28 (46.7) | 23 (46.0) | 15 (36.6) | 22 (56.4) | NR | NR | 86 (41.1) | 23 (19.3) |
| Index yeara, n (%) | ||||||||||
| 2014–2016 | NAb | NAb | 22 (36.7) | 17 (34.0) | 9 (22.0) | 9 (23.1) | < 5 | NR | 61 (29.2) | 22 (18.5) |
| 2017–2019 | 231 (43.7) | 147 (32.7) | 29 (48.3) | 20 (40.0) | 14 (34.1) | 13 (33.3) | < 5 | NR | 65 (31.1) | 32 (26.9) |
| 2020–2023 | 298 (56.3) | 302 (67.3) | 9 (15.0)c | 13 (26.0)c | 18 (43.9) | 17 (43.6) | < 5 | NR | 83 (39.7) | 65 (54.6) |
| Charlson Comorbidity Index Score (Quan-weighted) | ||||||||||
| Median (Q1–Q3) | 1.0 (0.0–2.0) | 4.0 (2.0–5.0) | 1.0 (0.0–1.0) | 3.0 (2.0–4.0) | 0.0 (0.0–2.0) | 4.0 (1.0–8.0) | 0.5 (0.0–4.8) | NR | 0.0 (0.0–0.0) | 2.0 (1.0–2.0) |
| Comorbidities, n (%) | ||||||||||
| Hypertension | 337 (63.7) | 409 (91.1) | 22 (36.7) | 27 (54.0) | < 5 | 16 (41.0) | 0 (0.0) | NR | 31 (14.8) | 52 (43.7) |
| Myocardial infarction | 15 (2.8) | 73 (16.3) | < 5 | 8 (16.0) | < 5 | 9 (23.1) | 0 (0.0) | NR | < 5 | 11 (9.2) |
| Type 2 diabetes | 69 (13.0) | 109 (24.3) | 11 (18.3) | 13 (26.0) | < 5 | 5 (12.8) | < 5 | NR | 9 (4.3) | 10 (8.4) |
| Chronic kidney disease (stages 3–5) | 60 (11.3) | 130 (29.0) | < 5 | 8 (16.0) | 0 (0.0) | < 5 | 0 (0.0) | NR | < 5 | 5 (4.2) |
| Cancer | 96 (18.1) | 108 (24.1) | 5 (8.3) | 9 (18.0) | 8 (19.5) | 19 (48.7) | 0 (0.0) | NR | 7 (3.3) | 9 (7.6) |
Baseline characteristics as recorded on the index date or within 1 year before the index date. Data from groups of < 5 patients are suppressed (this includes all patients with ATTRv mixed phenotype from Denmark)
ATTR amyloid transthyretin, ATTRv mixed hereditary ATTR amyloidosis with mixed phenotype, ATTRv-PN hereditary ATTR amyloidosis with polyneuropathy, NA not available, NR not reportable, SD standard deviation
aThe index date is the earliest confirmed International Classification of Diseases, Tenth Revision, E85 diagnosis code, or equivalent
bData for the US cohort (Optum® CDM) captures the period between January 1, 2017 and December 31, 2023
cData for the UK cohort (CPRD Aurum linked to HES) captures the period between January 1, 2014, and December 31, 2022
Compared to patients with ATTRv mixed, patients with ATTRv-PN were generally younger, and a higher proportion were female (36.6–64.1% vs. 19.3–56.4%). Patients with ATTRv-PN had a lower burden of comorbidity than patients with ATTRv mixed (Table 1).
Early Clinical Manifestations Before Diagnosis of ATTRv Amyloidosis
Cardiac Manifestations
Cardiac manifestations frequently preceded a recorded diagnosis of ATTRv amyloidosis in patients with ATTRv mixed. Among patients with ATTRv mixed with 5 years of available lookback data, the most frequent initial cardiac manifestation recorded at or before diagnosis was heart failure, ranging from 40.4% (n = 84) in the US to 68.2% (n = 15) in Japan. AF or AFL were also frequent initial cardiac manifestations in all countries (26.9–47.6%), as was cardiomyopathy in Sweden (47.9%; n = 57) (Fig. 2). A considerable proportion of patients experienced two or more cardiac manifestations within 5 years before diagnosis, with 27.3–47.1% of patients affected across the different countries studied (Supplementary Material Table S3). Data were not reportable for Denmark due to a small patient sample.
Fig. 2.
Frequency of early cardiac clinical manifestations and elapsed time to diagnosis in patients with ATTRv mixed and 5 years of lookback data. Bubble size and percentage represent the proportion of patients with the manifestation on, or within 5 years before, the index date. Any cardiac manifestation includes heart failure, cardiomyopathy, atrial fibrillation or flutter, AV block, and aortic valve stenosis. Patients with ATTRv mixed from Denmark were excluded due to small patient numbers (< 5 patients; Supplementary Table 3). Includes only patients with 5 years of available lookback data. Cardiac manifestations reported in patients with ATTRv mixed only. Groups with specific cardiac manifestations that were reported in < 5 patients have been excluded. AF atrial fibrillation, AFL atrial flutter, ATTR amyloid transthyretin, ATTRv mixed hereditary ATTR amyloidosis with mixed phenotype, AV atrioventricular
Median time from initial recording of any cardiac manifestation to ATTRv amyloidosis diagnosis was 0.4–1.6 years in patients with ATTRv mixed. Initial cardiac manifestations with the longest median (IQR) times to diagnosis included AF or AFL and cardiomyopathy in the US (2.2 [0.6–3.6] years; n = 56 and 2.4 [1.0–3.9] years; n = 31, respectively), AV block in the UK (2.0 [0.5–3.2] years; n = 6), and aortic valve stenosis in Sweden (3.5 [2.5–4.0] years; n = 12) (Fig. 2).
Noncardiac Manifestations
Noncardiac manifestations observed across countries in patients with ATTRv-PN or ATTRv mixed are presented in Fig. 3 and Supplementary Material Table S4. Neuropathy was reported in 15.6–89.5% of patients with ATTRv-PN (Fig. 3a). Although less frequently reported, neuropathy remained a common initial manifestation among patients with ATTRv mixed (Fig. 3b); GI dysfunction was frequently reported as an initial manifestation in patients with ATTRv mixed, particularly in Japan (40.9%; n = 9) and the UK (45.2%; n = 19).
Fig. 3.
Frequency of early noncardiac clinical manifestations and elapsed time to diagnosis in patients with ATTRv amyloidosis and 5 years of lookback data, categorized according to phenotype: a polyneuropathy and b mixed. Bubble size and percentage represent the proportion of patients with the manifestation on, or within 5 years before, the index date. Any noncardiac manifestation includes neuropathy, GI dysfunction, erectile dysfunction, CTS, CTS surgery, and spinal stenosis. Data for patients with ATTRv-PN in Denmark were not captured in Fig. 3 due to the small patient sample (n = 5; patients with any noncardiac manifestations, Supplementary Table S4). Patients with ATTRv mixed from Denmark were excluded due to small patient numbers (< 5 patients). Groups with specific noncardiac manifestations that were reported in < 5 patients have been excluded. aIncludes mono-, poly, and other neuropathy, and autonomic neuropathy. ATTR amyloid transthyretin, ATTRv mixed hereditary ATTR amyloidosis with mixed phenotype, ATTRv-PN hereditary ATTR amyloidosis with polyneuropathy, CTS carpal tunnel syndrome, GI gastrointestinal
Median times were most prolonged from initial recording of any noncardiac manifestation to diagnosis for both phenotypes in the US (ATTRv-PN: 2.9 [1.0–4.0] years; ATTRv mixed: 2.4 [0.8–3.7] years). For specific noncardiac manifestations, diagnostic delays were longest in patients ultimately identified with ATTRv-PN for spinal stenosis and GI dysfunction in the US, and in patients with ATTRv mixed for CTS and spinal stenosis in Sweden, and GI dysfunction and spinal stenosis in the US. Data for patients with ATTRv-PN in Denmark were not reportable due to a small patient sample (Fig. 3).
HCRU Before Diagnosis of ATTRv Amyloidosis
Patients with ATTRv-PN and ATTRv mixed experienced substantial HCRU burden in the 5 years preceding diagnosis (Table 2). Outpatient visits were the most frequent healthcare encounter in both phenotypes across all countries. A considerable proportion of patients experienced an ACH during the 5 years preceding diagnosis (38.6–88.9%) with a median LOS ranging across countries from 3.0 to 5.0 days in patients with ATTRv-PN, and 4.0 to 7.0 days in patients with ATTRv mixed. Approximately 10% of patients with ATTRv mixed in Sweden and the US had a HFH (Table 2).
Table 2.
HCRU before diagnosis in patients with ATTRv-PN or ATTRv mixed and 5 years of lookback data
| United States | United Kingdom | Japan | Denmark | Sweden | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| ATTRv-PN | ATTRv mixed | ATTRv-PN | ATTRv mixed | ATTRv-PN | ATTRv mixed | ATTRv-PN | ATTRv mixed | ATTRv-PN | ATTRv mixed | |
| Patients, n | 184 | 208 | 45 | 42 | 19 | 22 | 6 | < 5 | 209 | 119 |
| Emergency visits | ||||||||||
| Patients with ≥ 1 emergency visit, n (%) | 106 (57.6) | 172 (82.7) | 38 (84.4) | 34 (81.0) | < 5 | 7 (31.8) | < 5 | NR | 88 (42.1) | 84 (70.6) |
| Number of emergency visits per patient | ||||||||||
| Median (Q1–Q3) | 1.0 (0.0–4.0) | 3.0 (1.0–7.0) | 3.0 (1.0–6.0) | 3.0 (1.0–5.0) | NR | 0.0 (0.0–1.0) | NR | NR | 2.0 (1.0–3.0) | 2.0 (1.0–3.0) |
| Mean ± SD | 3.4 ± 8.1 | 7.0 ± 18.9 | 5.6 ± 7.7 | 5.0 ± 7.0 | NR | 0.4 ± 0.6 | NR | NR | 3.3 ± 4.4 | 3.6 ± 5.3 |
| Outpatient visits | ||||||||||
| Patients with ≥ 1 outpatient visit, n (%) | 182 (98.9)a | 207 (99.5)a | 45 (100.0)a | 41 (97.6)a | 18 (94.7)b | 22 (100)b | 6 (100.0)c | NRc | 205 (98.1)d | 117 (98.3)d |
| Number of outpatient visits per patient | ||||||||||
| Median (Q1–Q3) | 35.0 (19.0–53.0) | 49.0 (30.0–75.0) | 64.0 (35.0–98.0) | 58.5 (25.0–97.0) | 14.0 (9.0–40.0) | 32.5 (16.0–50.0) | 11.5 (7.2–15.8) | NR | 7.0 (3.0–13.0) | 9.0 (5.0–16.0) |
| Mean ± SD | 40.1 ± 29.9 | 58.3 ± 42.7 | 73.8 ± 56.9 | 65.4 ± 48.7 | 23.2 ± 22.2 | 35.7 ± 24.1 | 12.2 ± 7.1 | NR | 11.1 ± 16.5 | 11.5 ± 10.0 |
| ACH | ||||||||||
| Patients with ≥ 1 ACH | 71 (38.6) | 157 (75.5) | 40 (88.9) | 35 (83.3) | < 5 | 13 (59.1) | < 5 | NR | 85 (40.7) | 75 (63.0) |
| Number of ACH per patient | ||||||||||
| Median (Q1–Q3) | 0.0 (0.0–1.0) | 1.0 (1.0–3.0) | 2.0 (1.0–4.0) | 3.0 (1.0–5.0) | NR | 1.0 (0.0–2.0) | NR | NR | 2.0 (1.0–2.0) | 2.0 (1.0–3.0) |
| Mean ± SD | 0.8 ± 1.4 | 2.3 ± 2.6 | 4.9 ± 7.7 | 4.4 ± 6.6 | NR | 1.2 ± 1.6 | NR | NR | 2.8 ± 5.9 | 2.8 ± 2.6 |
| Hospital LOS (days) | ||||||||||
| Median (Q1–Q3) | 3.0 (2.0–5.0) | 4.0 (2.0–7.0) | 5.0 (2.0–10.0) | 7.0 (2.0–14.0) | NR | 7.0 (3.0–22.5) | NR | NR | 3.0 (1.0–2.0) | 4.0 (2.0–8.0) |
| Mean ± SD | 5.0 ± 6.9 | 5.8 ± 6.2 | 10.2 ± 21.4 | 12.7 ± 18.1 | NR | 14.1 ± 16.0 | NR | NR | 5.1 ± 6.7 | 6.3 ± 7.5 |
| HFH | ||||||||||
| Patients with ≥ 1 HFH, n (%) | NA | 26 (12.5) | NA | < 5 | NA | < 5 | NA | NR | NA | 13 (10.9) |
| Number of HFH per patient | ||||||||||
| Median (Q1–Q3) | NA | 0.0 (0.0–0.0) | NA | NR | NA | NR | NA | NR | NA | 1.0 (1.0–2.0) |
| Mean ± SD | NA | 0.2 ± 0.4 | NA | NR | NA | NR | NA | NR | NA | 1.6 ± 1.0 |
| Hospital LOS, days | ||||||||||
| Median (Q1–Q3) | NA | 3.0 (2.0–4.0) | NA | NR | NA | NR | NA | NR | NA | 4.0 (2.0–8.0) |
| Mean ± SD | NA | 3.3 ± 2.4 | NA | NR | NA | NR | NA | NR | NA | 4.9 ± 3.0 |
The coding algorithm for ATTRv-PN did not allow for a history of cardiac manifestations. HFH data are not available for patients with ATTRv-PN. HCRU analyses were restricted to patients with 5 years of lookback data. Data from groups of < 5 patients are suppressed (this includes all patients with ATTRv mixed phenotype from Denmark)
ATTR amyloid transthyretin, ATTRv mixed hereditary ATTR amyloidosis with mixed phenotype, ATTRv-PN hereditary ATTR amyloidosis with polyneuropathy, HCRU healthcare resource utilization, HFH heart failure–related hospitalization, IQR interquartile range, LOS length of stay, NA not available, NR not reportable, SD standard deviation
aIncludes primary care and specialist visits
bMDV only captures primary care provided at an MDV hospital
cPrimary care data were not included in the analysis for the cohort of patients from Denmark
dThe CELOSIA study database does not include primary care data
Treatment After Diagnosis of ATTRv Amyloidosis
Most patients in all countries except Sweden did not receive any ATTR amyloidosis treatments. Where data were reportable, 97.2% of patients with ATTRv-PN in the US and 64.1% of those with ATTRv mixed in Japan did not receive treatment. Data were not reportable for Denmark due to a small patient sample. Tafamidis is not approved for use in patients with ATTRv-PN in the US and was not reimbursed during the study period in this patient subgroup in the UK, and TTR gene silencers were approved late in the study period in all countries. While TTR gene silencers were approved or reimbursed in all countries, international variability exists in the implementation of national access pathways, thus impacting the time from treatment approval to initiation in patients (Supplementary Material Table S1).
Post-diagnosis treatment patterns in each country are presented in Supplementary Material Table S5. In Japan, 30.8% (n = 12) and 21.7% (n = 5) of patients with ATTRv mixed received TTR protein stabilizer and TTR gene silencer treatment, respectively; fewer patients with ATTRv-PN were treated with either class. Approximately half of patients with ATTRv-PN in Sweden were prescribed ATTR amyloidosis treatments consisting solely of TTR protein stabilizers; slightly more patients with ATTRv mixed than ATTRv-PN were treated (58.8%; n = 70 vs. 51.7%; n = 108). Vutrisiran was approved late in the study period in Sweden, and data on patisiran and inotersen use were not captured in the CELOSIA study database.
Outcomes After Diagnosis of ATTRv Amyloidosis
ACM
Five-year ATTRv-PN mortality ranged from 14.6% in Sweden to 36.2% in the UK and for ATTRv mixed from 21.0% in Japan to 73.0% in the UK (Fig. 4). Data were insufficient for analysis for either phenotype in Denmark or for patients with ATTRv-PN in Japan.
Fig. 4.
ACM: Kaplan–Meier plots for a the United States, b the United Kingdom, c Japan, and d Sweden in patients with ATTRv-PN and ATTRv mixed. Data for patients with both phenotypes from Denmark and patients with ATTRv-PN from Japan were not presented due to small patient numbers. Where the number of patients at risk was < 5, data have been suppressed. ACM all-cause mortality, ATTR amyloid transthyretin, ATTRv mixed hereditary ATTR amyloidosis with mixed phenotype, ATTRv-PN hereditary ATTR amyloidosis with polyneuropathy
While mortality risk steadily increased over the 5-year follow-up period in both phenotypes in Sweden and the US, and patients with ATTRv-PN in the UK, risk was more pronounced during first year post-diagnosis in patients with ATTRv mixed in the UK (Fig. 4).
Hospitalizations
Initial ACH probability was greatest during the first-year post-diagnosis in patients with ATTRv mixed in the US, and in both phenotypes in Japan and Sweden. At 5 years post-diagnosis, first ACH probability increased from a range of 23.5% in the UK (95% CI 12.7–36.2%) to 66.2% in Sweden (95% CI 58.6–74.8%) in patients with ATTRv-PN, and 20.8% in the UK (95% CI 10.5–33.4%) to 70.5% in Sweden (95% CI 60.3–82.3%) in patients with ATTRv mixed (Fig. 5). The probability of a first HFH gradually increased over the post-diagnosis period in patients with ATTRv mixed (Fig. 6). ACH data were inadequate to conduct analysis in Denmark as were HFH data for patients with ATTRv mixed in the UK and Denmark.
Fig. 5.
ACH: cumulative incidence function curves accounting for competing risk of all-cause death in a the United States, b the United Kingdom, c Japan, and d Sweden in patients with ATTRv-PN and ATTRv mixed. Data for patients with both phenotypes from Denmark were not presented due to small patient numbers. Where the number of patients at risk was < 5, data have been suppressed. ACH all-cause hospitalizations, ATTR amyloid transthyretin, ATTRv mixed hereditary ATTR amyloidosis with mixed phenotype, ATTRv-PN hereditary ATTR amyloidosis with polyneuropathy
Fig. 6.
HFH: cumulative incidence function curves accounting for competing risk of all-cause death in a the United States, b Japan, and c Sweden in patients with ATTRv mixed. Data for patients with both phenotypes from Denmark and the United Kingdom were not presented due to small patient numbers. HFH was not reported in patients with ATTRv-PN. Where the number of patients at risk was < 5, data have been suppressed. ATTR amyloid transthyretin, ATTRv mixed hereditary ATTR amyloidosis with mixed phenotype, HFH heart failure–related hospitalization
HCRU After Diagnosis of ATTRv Amyloidosis
Consistent with the pre-diagnosis period, post-diagnosis HCRU was elevated in all patients across most of the countries, and outpatient visits were the most frequent healthcare encounter (Table 3). When primary care data were captured as part of outpatient visits (US, UK, and Japan), rates in patients with ATTRv mixed ranged from 10.9 in Japan to 13.6 visits PPY in the UK. Similar patterns, although slightly less marked, were observed in patients with ATTRv-PN (Table 3). In countries lacking primary care data (Sweden and Denmark), outpatient visit rates for patients with ATTRv-PN were 4.7 and 8.2 PPY in Sweden and Denmark, respectively; only Sweden had available data for patients with ATTRv mixed (3.9 outpatient visits PPY).
Table 3.
HCRU after diagnosis in patients with ATTRv-PN and ATTRv mixed
| United States | United Kingdom | Japan | Denmark | Sweden | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| ATTRv-PN | ATTRv mixed | ATTRv-PN | ATTRv mixed | ATTRv-PN | ATTRv mixed | ATTRv-PN | ATTRv mixed | ATTRv-PN | ATTRv mixed | |
| Patients, n | 529 | 449 | 60 | 50 | 41 | 39 | 6 | < 5 | 209 | 119 |
| Follow-up time, years, median (Q1–Q3) | 1.7 (0.7–3.2) | 0.9 (0.4–2.1) | 3.6 (0.4–5.2) | 0.6 (0.0–2.8) | 2.0 (0.9–4.0) | 1.5 (0.6–4.0) | 4.2 (3.5–4.9) | NR | 4.2 (1.8–6.8) | 2.2 (0.8–4.5) |
| Emergency visits | ||||||||||
| Visit rate PPY | 1.0 | 1.7 | 0.5 | 2.2 | 0.1 | 0.2 | 0.6 | NR | 0.8 | 1.1 |
| Outpatient visits | ||||||||||
| Visit rate PPY | 10.4a | 12.5a | 11.5a | 13.6a | 8.0b | 10.9b | 8.2c | NRc | 4.7d | 3.9d |
| ACH | ||||||||||
| Visit rate PPY | 0.2 | 0.8 | 0.7 | 2.1 | 0.4 | 0.5 | 1.2 | NR | 0.5 | 0.8 |
| Hospital LOS, days | ||||||||||
| Median (Q1–Q3) | 4.0 (2.0–6.8) | 4.0 (3.0–7.0) | 3.0 (2.0–7.0) | 3.0 (2.0–8.8) | 10.0 (5.0–21.5) | 11.0 (4.0–31.5) | 11.5 (6.5–17.8) | NR | 4.0 (2.0–8.0) | 5.0 (2.0–9.0) |
| Mean ± SD | 5.7 ± 6.6 | 6.5 ± 8.3 | 6.4 ± 11.9 | 7.6 ± 11.3 | 15.2 ± 14.6 | 23.4 ± 29.0 | 12.8 ± 8.3 | NR | 7.5 ± 11.6 | 6.7 ± 6.9 |
| HFH | ||||||||||
| Visit rate PPY | NA | 0.1 | NA | 0.1 | NA | 0.1 | NA | NR | NA | 0.1 |
| Hospital LOS, days | ||||||||||
| Median (Q1–Q3) | NA | 3.0 (1.0–5.0) | NA | 10.0 (8.5–25.5) | NA | 12 (9.0–27.8) | NA | NR | NA | 5.0 (2.0–8.0) |
| Mean ± SD | NA | 3.4 ± 2.5 | NA | 18.2 ± 16.7 | NA | 19.8 ± 19.4 | NA | NR | NA | 6.5 ± 6.1 |
The coding algorithm for ATTRv-PN did not allow for a history of cardiac manifestations. HFH data are not available for patients with ATTRv-PN. Data from groups of < 5 patients are suppressed (this includes all patients with ATTRv mixed phenotype from Denmark)
ACH all-cause hospitalization, ATTR amyloid transthyretin, ATTRv mixed hereditary ATTR amyloidosis with mixed phenotype, ATTRv-PN hereditary ATTR amyloidosis with polyneuropathy, HFH heart failure–related hospitalization, HCRU healthcare resource utilization, IQR interquartile range, LOS length of stay, NA not available, PPY per person-year, SD standard deviation
aIncludes primary care and specialist visits
bMDV only captures primary care provided at an MDV hospital
cPrimary care data were not included in the analysis for the cohort of patients from Denmark
dThe CELOSIA study database does not include primary care data
Median (IQR) ACH LOS was similar across phenotypes, and in most countries ranged from 3.0 to 5.0 days, except for Denmark and Japan, where hospital stays were considerably longer: 11.5 (6.5–17.8) days among patients with ATTRv-PN in Denmark and 10.0 (5.0–21.5) days and 11.0 (4.0–31.5) days in patients with ATTRv-PN and ATTRv mixed in Japan, respectively. Median (IQR) LOS for HFH in patients with ATTRv mixed varied from 3.0 (1.0–5.0) days in the US to 12.0 (9.0–27.8) days in Japan (Table 3).
Discussion
The OverTTuRe study identified a diverse population of patients with ATTRv amyloidosis from five large, nationally representative data sources in three world regions.
While ATTRv-PN was the predominant phenotype observed across all countries, the mixed phenotype accounted for a considerable and growing proportion of patients in the US and Sweden. The mixed phenotype group experienced a particularly high burden of both cardiac and noncardiac manifestations, a potential factor contributing to diagnostic delays. Patients with ATTRv mixed were older at diagnosis than those with ATTRv-PN, and therefore multiple comorbid conditions were more prevalent, potentially contributing to diagnostic delay. The heterogeneous, non-specific, and systemic nature of ATTR amyloidosis has been shown to be a determinant of delayed diagnosis [34, 35]. In the current analysis, diagnostic delays after initial presentation of any noncardiac manifestation were frequently reported, with time to diagnosis varying across countries. Delays varied from 0 and 0.7 years in Japan, to 2.9 years and 2.4 years in the US for patients with ATTRv-PN and mixed phenotypes, respectively. A shorter, but still notable, delay occurred after initial presentation of any cardiac manifestation in patients with ATTRv mixed. These delays also differed across countries, ranging from 0.4 years in the UK to 1.6 years in both the US and Japan.
While these delays may reflect the heterogeneity of clinical manifestations in ATTR amyloidosis, differences across databases must be considered. While the lag time between manifestation occurrence and claims reporting has not been explored in this analysis, it may have also influenced the differences in diagnostic delays across manifestations and countries.
Diagnoses of ATTR amyloidosis are increasing worldwide, predominated by ATTR-CM and mixed phenotype presentations [26, 36, 37], likely arising from greater clinician awareness and phenotype recognition, driven by the availability of novel targeted treatments and increasing access to advanced cardiac imaging methods. A similar time trend of more patients diagnosed with ATTR amyloidosis in OverTTuRe corroborates global data from other sources. Findings from this and other real-world evidence studies reveal the broad continuum of cardiac, neurological, and musculoskeletal manifestations in patients with ATTRv mixed phenotype; such manifestations can persist for many years before a diagnosis is made [38]. These findings emphasize the need for earlier symptom recognition and patient identification via efforts to raise awareness of the constellation of clinical manifestations of ATTR amyloidosis.
Substantial HCRU burden was observed in the 5 years preceding diagnosis for both the number of outpatient visits and hospital LOS. Previous reports have highlighted that the heterogeneous clinical manifestations of ATTR amyloidosis, which often mimic other conditions, may result in patients having multiple healthcare interactions before receiving an accurate diagnosis [9, 39, 40]. Results from the current analysis showed consistency of HCRU across the study cohort, and this utilization peaked one year prior to diagnosis (data not shown). While between-country variation in these findings can in part be attributed to the heterogeneity of ATTR amyloidosis manifestations, it is important to consider the underlying data sources from which these data were collected. The use of multiple databases, each representing different healthcare systems, varies in data collection objective and approach. For example, CELOSIA does not capture data from primary care settings, and Optum® CDM and MDV databases primarily collect data for billing and reimbursement purposes. Therefore, comparisons between countries should be regarded as descriptive.
The true population prevalence of ATTR amyloidosis has historically been difficult to ascertain, partially because of changes in patients’ diagnostic status over time, which suggests that screening may assist with early identification of undiagnosed cases. In turn, this may further speed earlier diagnosis, enable timely initiation of therapy, and potentially improve patient outcomes [41]. Optimizing patient care pathways and streamlining referral networks across specialties could potentially help facilitate a multidisciplinary, holistic approach, encompassing awareness of initial disease presentation, referral for early definitive diagnosis, and guideline-directed therapeutic intervention to improve outcomes [42]
The ultimate goal of conducting this analysis is to improve the lives of people living with ATTR amyloidosis. These results demonstrate notable phenotypic differences in survival, with ACM highest among patients with ATTRv mixed versus ATTRv-PN. The emergence of novel disease-modifying therapies for ATTR amyloidosis, such as TTR gene silencers and TTR protein stabilizers, facilitates timely diagnosis to have a greater impact on disease course for patients of all phenotypes [43, 44]. Indeed, treatment benefit is greatest when initiation begins in early stages of the disease [45]; however, variable and country-specific access limits treatment options for both healthcare professionals and patients [42]. The patterns observed in this analysis may reflect differences in access and reimbursement timing, particularly with regard to TTR gene silencers, patient refusal, or prescriber inertia during the study period. This inequality emphasizes the need to expand the availability of disease-specific treatment since they meaningfully impact patient quality of life, autonomy, and physical function [1].
The strengths of the OverTTuRe study include the multicountry aspect, offering a wide geographic scope to assess the contemporary epidemiology of ATTR amyloidosis across diverse healthcare settings and patient populations. The use of secondary healthcare databases to conduct population-based analyses supports the generalizability of findings in a real-world context. In the absence of a published consensus algorithm for the genotypic and phenotypic identification and categorization of patients with ATTR amyloidosis, we developed a coding-based algorithm to leverage possible insights from large administrative databases. OverTTuRe utilizes structured data collected across a range of measures to understand the entire disease journey of patients with ATTRv amyloidosis.
Limitations of OverTTuRe include secondary data that are not primarily intended for research, such as insurance claims databases, which collect data for billing and reimbursement purposes. The use of various unvalidated databases may have led to underreporting of key outcomes, including clinical manifestations, HCRU, and mortality. For example, MDV does not record deaths occurring outside MDV-affiliated hospitals, and CELOSIA does not capture data from primary care settings. These differences in data collection may influence observed findings, and between-country comparisons should be avoided. While considerable HCRU burden of ATTRv amyloidosis has been presented, it is worth noting that, due to the type of data used, this study lacked a control population, and HCRU burden should be viewed in that context. In addition, patient-reported outcomes are not available in OverTTuRe sources to date, demonstrating a lack of this type of data in large administrative and EHR databases.
It is also important to acknowledge certain limitations of the diagnostic coding-based algorithm used in this study. The study relies on clinical diagnosis codes to identify patients with ATTRv amyloidosis and then relies on accurate recording/coding of other neurological or cardiac features to correctly assign them to phenotypic subgroups. Such categorization may limit the availability of nuanced data on the nature and timing of early clinical manifestations and obscure the many ways a patient with ATTRv amyloidosis may present at diagnosis. Indeed, patients with a mixed phenotype exist on a dynamic and clinical spectrum and may not fit neatly into the group defined here. Differences in the granularity of amyloidosis diagnosis codes exist between databases, and coding practices differ across countries, thus impacting patient identification. The diagnostic coding-based algorithm used in this study may have introduced the possibility of misclassification bias; however, since the same algorithm was applied across all cohorts, such misclassification is likely to be nondifferential without any substantial impact on study findings. Further, variations in coding practices, as previously discussed, may have contributed to this potential issue. This may explain, in part, the low number of patients identified as having ATTRv-CM. Individuals with ATTRv-CM who also had neurological manifestations were automatically classified as mixed, possibly leading to misclassification. Additionally, this study sought to characterize patients with ATTRv amyloidosis, and the OverTTuRe algorithm was iteratively refined to optimize specificity. Thus, the number of patients identified with ATTRv amyloidosis may be an underestimate, with potential implications for the generalizability of study findings. Finally, while the algorithm was developed in consultation with the authors and other international amyloidosis experts, it was not clinically validated. Future validation studies utilizing registry data from patient cohorts are being considered.
Regarding the study population, genetic variant data were unavailable for all cohorts included in this study. TTR variants display distinct prevalence patterns across regions and have been shown to affect phenotype heterogeneity, prognosis, and treatment response [25, 27, 46–48]. The lack of genetic variant data in this study limits the interpretation of cross-country heterogeneity. The low number of patients from Denmark limits the generalizability of findings for this cohort, as most were excluded from this analysis due to having wild-type disease. Ongoing analyses of OverTTuRe will assess outcomes in patients with ATTRwt, providing further insights into the Denmark cohort.
Lastly, the current analysis does not include clinical and diagnostic results; however, this will be addressed in future OverTTuRe analyses.
Conclusions
This analysis from the OverTTuRe study highlights phenotypic heterogeneity associated with diverse clinical manifestations in patients with ATTRv amyloidosis, which translates into broad differences in outcomes. These results indicate a critical need for recognition of initial symptoms in the variant population at risk, heightened clinical suspicion to enable earlier diagnosis, and timely access to targeted therapies. Ongoing analyses within the OverTTuRe study program, including assessment of outcomes in patients with ATTRwt amyloidosis and from additional countries, will provide additional real-world insights into this disease.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
The authors would like to thank the patients and their families for their participation in this study. This study is based in part on data from the CPRD obtained under license from the UK Medicines and Healthcare Products Regulatory Agency. The data are provided by patients and collected by the NHS as part of their care and support. The ONS is also acknowledged as the provider of the ONS data contained within the CPRD data. The interpretation and conclusions contained in this study are those of the author/s alone. Copyright © (2024), reused with the permission of NHS Digital. All rights reserved. Approval for this study was granted by the CPRD Research Data Governance Committee (Protocol #: 23_003343). This study also gratefully utilized data from the CROSS-TRACKS cohort in Denmark (https://bmjopen.bmj.com/content/10/10/e039996) based on approval by the CROSS-TRACKS steering committee, and the research questions were investigated in collaboration with a CROSS-TRACKS representative. The authors acknowledge the CROSS-TRACKS Research Group and the steering committee at Horsens Regional Hospital, Denmark, for data infrastructure, methodological, and research inputs. Dr Krister Järbrink has changed affiliation since the completion of this study. The new affiliation is as follows: HSR Support, Bohusgatan 14, 411 39 Gothenburg (partially retired).
Medical Writing/Editorial Assistance
Medical writing support was provided by Lucy Helas, BSc, and editorial support was provided by Jess Fawcett, BSc, of the Prime Group of Companies (Knutsford, UK), funded by AstraZeneca according to Good Publication Practice guidelines (Link). AI-assisted technology was used to support the development of the plain language summary. The in-house AI-powered PLS writing tool was developed by AstraZeneca.
Author Contributions
Laura Davis, Krister Järbink, and Arti Gauvri Bhimjiyani contributed to the conceptualization and methodology of this study. Laura Davis contributed to the software and validation and, together with Johan Sundström, to the formal analysis, investigation, resources, and data curation. Kevin M. Alexander, Shun Kohsaka, Steen Hvitfeldt Poulsen, Astrid J. Terkelsen, J. Gustav Smith, Jason Wright, Krister Järbrink, Arti Gauvri Bhimjiyani, Laura Davis, Yuya Matsue, Lisa J. Anderson, and Björn Pilebro contributed to writing the original draft. All authors contributed to reviewing and editing the manuscript. Laura Davis and Arti Gauvri Bhimjiyani contributed to the visualization of this study. Arti Gauvri Bhimjiyani supervised this study and, together with Johan Sundström, contributed to the project administration.
Funding
This study, the accompanying graphical abstract, and the journal’s Rapid Service Fee, were funded by AstraZeneca.
Data Availability
The datasets used in the study were obtained from a third-party contracted to be strictly used within AstraZeneca; therefore are not publicly available.
Declarations
Conflicts of Interest
Kevin Alexander is a consultant to Alexion, Alnylam, Bayer, BridgeBio, Novo Nordisk, and Pfizer. Kevin Alexander is also an Editorial Board member of Cardiology and Therapy. He was not involved in the selection of peer reviewers for the manuscript nor in any of the subsequent editorial decisions. Shun Kohsaka has received investigator-initiated research funding from Novartis and AstraZeneca. Steen Hvitfeldt Poulsen has received consulting fees from BridgeBio; Pfizer, Alnylam, Novo Nordisk, Cytokinetics, Bayer and AstraZeneca. Astrid Terkelsen has received honorarium from Novo Nordisk DK, Sanofi, AstraZeneca, and Alnylam Sweden AB. J. Gustav Smith reports that his employer (Gothenburg University) is paid by AstraZeneca for his involvement in ANTHOLOGY (no personal payment). Johan Sundström reports direct or indirect stock ownership in companies (Sence Research AB, Symptoms Europe AB, MinForskning AB, Anagram kommunikation AB) providing services to companies and authorities in the health sector, including Amgen, AstraZeneca, Bayer, Boehringer, Eli Lilly, Gilead, GSK, Göteborg University, Itrim, Ipsen, Janssen, Karolinska Institutet, LIF, Linköping University, Novo Nordisk, Parexel, Pfizer, Region Stockholm, Region Uppsala, Sanofi, STRAMA, Takeda, TLV, Uppsala University, Vifor Pharma, WeMind. Jason Wright, Arti Gauvri Bhimjiyani, Krister Järbrink†, and Laura Davis are employees of, and hold stock in, AstraZeneca. Lisa Anderson has participated in an advisory board for Alnylam and has received travel support from Abbott and support as a Junior Fellow from Pfizer. Yuya Matsue has received honorarium from Otsuka Pharmaceutical Co., Ltd., EN Otsuka Pharmaceutical Co., Ltd., Novartis Pharma K.K., Ono Pharmaceutical Co., Ltd., AstraZeneca, Nippon Boehringer Ingelheim Co., Ltd., Bayer Yakuhin, Ltd., Kyowa Kirin Co., Ltd., Pfizer Japan Inc., and Alnylam Japan. He has also received collaborative research funding from Otsuka Pharmaceutical Co., Ltd., EN Otsuka Pharmaceutical Co., Ltd., Pfizer Japan Inc., Bayer Yakuhin, Ltd., Nippon Boehringer Ingelheim Co., Ltd., AstraZeneca K.K., Roche Diagnostics K.K., Grace Imaging Inc., and Omron Healthcare Co., Ltd. Björn Pilebro has received financial reimbursement for consulting from AstraZeneca and is an investigator in studies sponsored by Akcea Therapeutics, Alnylam Pharmaceuticals, Inc., and Intellia Therapeutics. Krister Järbrink was an employee and shareholder of AstraZeneca at the time of the study but has since changed employment.
Ethical Approval
OverTTuRe was performed in accordance with ethical principles that are consistent with the Declaration of Helsinki, International Conference on Harmonization (ICH), Good Clinical Practices (GCPs), Guidelines for Good Pharmacoepidemiology Practices (GPP), and the applicable legislation on noninterventional studies and/or observational studies. Obtaining informed consent from participants was not applicable as this study was solely based on secondary data from the following data sources: Optum’s de-identified Clinformatics® Data Mart Database (Optum® CDM) from the United States, Clinical Practice Research Datalink (CPRD) and Hospital Episode Statistics (HES) from the United Kingdom, Medical Data Vision (MDV) from Japan, CROSS-TRACKS from Denmark, and CELOSIA from Sweden. Ethical approval for the use of CELOSIA data in the OverTTuRe study was granted by the Swedish Ethical Review Authority. CPRD’s Research Data Governance approved the use of CPRD and HES data in the OverTTuRe study. The MDV utilizes anonymized data, which exempts clinical studies from the application of the Japanese Ethical Guidelines for Medical and Biological Research Involving Human Subjects. In this study, MDV anonymized the provided data; therefore, obtaining informed consent was deemed unnecessary. In Denmark, register-based studies require no ethical approval [32]. Optum® CDM does not require ethics approval, as the data is de-identified and fully compliant with the Health Insurance Portability and Accountability Act.
Footnotes
Krister Järbrink: Affiliation at time of study.
References
- 1.Nativi-Nicolau J, Karam C, Khella S, Maurer M. Screening for ATTR amyloidosis in the clinic: overlapping disorders, misdiagnosis, and multiorgan awareness. Heart Fail Rev. 2022;27(3):785–93. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Karam C, Mauermann ML, Gonzalez-Duarte A, et al. Diagnosis and treatment of hereditary transthyretin amyloidosis with polyneuropathy in the United States: recommendations from a panel of experts. Muscle Nerve. 2024;69(3):273–87. [DOI] [PubMed] [Google Scholar]
- 3.Rowczenio DM, Noor I, Gillmore JD, et al. Online registry for mutations in hereditary amyloidosis including nomenclature recommendations. Hum Mutat. 2014;35(9):E2403–12. [DOI] [PubMed] [Google Scholar]
- 4.Sekijima Y, Nakamura K. Hereditary transthyretin amyloidosis. In: Adam MP, Feldman J, Mirzaa GM, Pagon RA, Wallace SE, Amemiya A, editors. GeneReviews. Seattle: University of Washington; 1993. [PubMed] [Google Scholar]
- 5.Schmidt HH, Waddington-Cruz M, Botteman MF, et al. Estimating the global prevalence of transthyretin familial amyloid polyneuropathy. Muscle Nerve. 2018;57(5):829–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Poli L, Labella B, Cotti Piccinelli S, et al. Hereditary transthyretin amyloidosis: a comprehensive review with a focus on peripheral neuropathy. Front Neurol. 2023;14:1242815. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Finsterer J, Iglseder S, Wanschitz J, Topakian R, Löscher WN, Grisold W. Hereditary transthyretin-related amyloidosis. Acta Neurol Scand. 2019;139(2):92–105. [DOI] [PubMed] [Google Scholar]
- 8.Namiranian D, Geisler S. Neuromuscular complications of systemic amyloidosis. Am J Med. 2022;135(Suppl 1):S13–9. [DOI] [PubMed] [Google Scholar]
- 9.Adams D, Ando Y, Beirao JM, et al. Expert consensus recommendations to improve diagnosis of ATTR amyloidosis with polyneuropathy. J Neurol. 2021;268(6):2109–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.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(22):2872–91. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Ruberg FL, Berk JL. Transthyretin (TTR) cardiac amyloidosis. Circulation. 2012;126(10):1286–300. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Lousada I, Maurer M, Warner M, Guthrie S, Hsu K, Grogan M. Amyloidosis Research Consortium Cardiac Amyloidosis Survey: results from patients with AL and ATTR amyloidosis and their caregivers. JACC. 2018;71(11_Supplement):A890-A. [Google Scholar]
- 13.Cortese A, Vegezzi E, Lozza A, et al. Diagnostic challenges in hereditary transthyretin amyloidosis with polyneuropathy: avoiding misdiagnosis of a treatable hereditary neuropathy. J Neurol Neurosurg Psychiatry. 2017;88(5):457–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Collins P, Melinis N, Chung WY, et al. Misdiagnosis rates in ATTR-CM patients and associated symptoms. Eur Heart J. 2025;46(Supplement_1):ehaf784.2706.
- 15.Doneddu PE, Moretti G, Di Stefano V, et al. Prevalence of hereditary transthyretin amyloidosis in CIDP patients with red flags: a multicenter genetic screening and misdiagnosis analysis. J Neurol. 2025;272(8):515. [DOI] [PubMed] [Google Scholar]
- 16.Manganelli F, Fabrizi GM, Luigetti M, Mandich P, Mazzeo A, Pareyson D. Hereditary transthyretin amyloidosis overview. Neurol Sci. 2022;43(Suppl 2):595–604. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Rozenbaum MH, Large S, Bhambri R, et al. Impact of delayed diagnosis and misdiagnosis for patients with transthyretin amyloid cardiomyopathy (ATTR-CM): a targeted literature review. Cardiol Ther. 2021;10(1):141–59. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Godara A, Riesenburger RI, Zhang DX, et al. Association between spinal stenosis and wild-type ATTR amyloidosis. Amyloid. 2021;28(4):226–33. [DOI] [PubMed] [Google Scholar]
- 19.Donnelly JP, Hanna M, Sperry BW, Seitz WH Jr. Carpal tunnel syndrome: a potential early, red-flag sign of amyloidosis. J Hand Surg Am. 2025;50(11):1370–8. [DOI] [PubMed] [Google Scholar]
- 20.Sperry BW, Reyes BA, Ikram A, et al. Tenosynovial and cardiac amyloidosis in patients undergoing carpal tunnel release. J Am Coll Cardiol. 2018;72(17):2040–50. [DOI] [PubMed] [Google Scholar]
- 21.Tamasauskas D, Tamasauskiene L. Transthyretin amyloidosis in patients with spinal stenosis who underwent spinal surgery: a systematic review and meta-analysis. Front Neurol. 2024;15:1425862. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Lauppe R, Liseth Hansen J, Fornwall A, et al. Healthcare resource use of patients with transthyretin amyloid cardiomyopathy. ESC Heart Fail. 2022;9(3):1636–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Wixner J, Dispenzieri A, Amass L, et al. Survival in a contemporary, real-world cohort of patients with mixed-phenotype transthyretin amyloid cardiomyopathy treated with Tafamidis: an analysis from THAOS. Cardiol Ther. 2025. 10.1007/s40119-025-00421-9. (online ahead of print). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Coelho T, Maurer MS, Suhr OB. THAOS—The Transthyretin Amyloidosis Outcomes Survey: Initial report on clinical manifestations in patients with hereditary and wild-type transthyretin amyloidosis. Curr Med Res Opin. 2013;29(1):63–76. [DOI] [PubMed] [Google Scholar]
- 25.Gentile L, Coelho T, Dispenzeri A, et al. A 15-year consolidated overview of data in over 6000 patients from the Transthyretin Amyloidosis Outcomes Survey (THAOS). Orphanet J Rare Dis. 2023;18(1):350. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Delgado D, Dabbous F, Shivappa N, et al. Epidemiology of transthyretin (ATTR) amyloidosis: a systematic literature review. Orphanet J Rare Dis. 2025;20(1):29. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Lozeron P, Theaudin M, Mincheva Z, et al. Effect on disability and safety of Tafamidis in late onset of Met30 transthyretin familial amyloid polyneuropathy. Eur J Neurol. 2013;20(12):1539–45. [DOI] [PubMed] [Google Scholar]
- 28.Planté-Bordeneuve V, Gorram F, Salhi H, et al. Long-term treatment of transthyretin familial amyloid polyneuropathy with tafamidis: a clinical and neurophysiological study. J Neurol. 2017;264(2):268–76. [DOI] [PubMed] [Google Scholar]
- 29.Brito D, Albrecht FC, de Arenaza DP, et al. World Heart Federation consensus on transthyretin amyloidosis cardiomyopathy (ATTR-CM). Glob Heart. 2023;18(1):59. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Gillmore JD, Hahn K, Smith JG, et al. Rationale and design of ANTHOLOGY: an ATTR Amyloidosis Real-World Evidence Program aiming to address gaps in amyloidosis care. Cardiol Ther. 2025;14(3):477–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.ClinicalTrials.gov. NCT06355934. OverTTuRe: Characteristics, Treatment Patterns and Outcomes of Patients With ATTR Amyloidosis (OverTTuRe). 2024. https://clinicaltrials.gov/study/NCT06355934. Accessed 15 May 2024.
- 32.Riis AH, Kristensen PK, Petersen MG, Ebdrup NH, Lauritsen SM, Jørgensen MJ. Cohort profile: CROSS-TRACKS: a population-based open cohort across healthcare sectors in Denmark. BMJ Open. 2020;10(10):e039996. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Quan H, Li B, Couris CM, et al. Updating and validating the Charlson Comorbidity Index and Score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol. 2011;173(6):676–82. [DOI] [PubMed] [Google Scholar]
- 34.Conceição I, González-Duarte A, Obici L, et al. “Red-flag” symptom clusters in transthyretin familial amyloid polyneuropathy. J Peripher Nerv Syst. 2016;21(1):5–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Nativi-Nicolau J, Fine NM, Ortiz-Pérez JT, et al. Clinical manifestations and healthcare utilization before diagnosis of transthyretin amyloidosis. J Comp Eff Res. 2022;11(14):1031–44. [DOI] [PubMed] [Google Scholar]
- 36.Alexander K, Dasgupta N, Mathisen J, Møller SHG, Tvistholm A, Maurer M. Temporal trends in the incidence and prevalence of transthyretin amyloid cardiomyopathy in the USA: an observational database study. J Card Fail. 2025;31(1):268. [Google Scholar]
- 37.Damy T, Bourel G, Slama M, 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(1):345. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Fine N, Ducharme A, Matte G, Mezei M, Bril V, Delgado D. Diagnosis and management of mixed phenotype hereditary transthyretin amyloidosis: a case-based, Canadian perspective. CJC Open. 2025;7(5):614–27. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Lane T, Fontana M, Martinez-Naharro A, et al. Natural history, quality of life, and outcome in cardiac transthyretin amyloidosis. Circulation. 2019;140(1):16–26. [DOI] [PubMed] [Google Scholar]
- 40.Lousada I, Comenzo RL, Landau H, Guthrie S, Merlini G. Patient experience with hereditary and senile systemic amyloidoses: a survey from the Amyloidosis Research Consortium. Orphanet J Rare Dis. 2015;10(1):P22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Martyn T, Rubio AC, Estep JD, Hanna M. Opportunities for earlier diagnosis and treatment of cardiac amyloidosis. Methodist Debakey Cardiovasc J. 2022;18(5):27–39. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Kittleson MM, Ruberg FL, Ambardekar AV, 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(11):1076–126. [DOI] [PubMed] [Google Scholar]
- 43.Mallus M, Rizzello V. Treatment of amyloidosis: present and future. Eur Heart J Suppl. 2023;25:B99–103. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Anan I. Advances in the treatment of transthyretin amyloidosis. eGastroenterology. 2025;3(3):e100198. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Elliott P, Drachman BM, Gottlieb SS, et al. Long-term survival with tafamidis in patients with transthyretin amyloid cardiomyopathy. Circ Heart Fail. 2022;15(1):e008193. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Maurer MS, Hanna M, Grogan M, et al. Genotype and phenotype of transthyretin cardiac amyloidosis: THAOS (Transthyretin Amyloid Outcome Survey). J Am Coll Cardiol. 2016;68(2):161–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Merlini G, Plante-Bordeneuve V, Judge DP, et al. Effects of tafamidis on transthyretin stabilization and clinical outcomes in patients with non-Val30Met transthyretin amyloidosis. J Cardiovasc Transl Res. 2013;6(6):1011–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Waddington-Cruz M, Wixner J, Amass L, et al. Characteristics of patients with late- vs. early-onset Val30Met transthyretin amyloidosis from the Transthyretin Amyloidosis Outcomes Survey (THAOS). Neurol Ther. 2021;10(2):753–66. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The datasets used in the study were obtained from a third-party contracted to be strictly used within AstraZeneca; therefore are not publicly available.