500,000-plus US patients are estimated to carry undiagnosed ATTRwt-CM, against only 70,000-100,000 diagnosed and treated today, and the gap is closing at 10,000-15,000 new diagnoses a year.
Two independent methods size the US ATTR cardiomyopathy population, and triangulating them, rather than averaging them, is what defines the addressable opportunity. The epidemiology method starts from the aging US population with heart failure with preserved ejection fraction: an estimated 500,000 or more Americans aged 70 and over are believed to carry undiagnosed ATTR wild-type cardiomyopathy (ATTRwt-CM), based on autopsy and imaging-cohort prevalence studies. The registry and claims method counts confirmed, treated patients directly: IQVIA diagnosis-trend data and manufacturer commercial data put the currently diagnosed and treated population at 70,000 to 100,000, with tafamidis holding roughly 60 percent share and acoramidis 15 to 20 percent since its November 2024 launch. New diagnoses are running at 10,000 to 15,000 a year as Tc-PYP scintigraphy awareness grows among cardiologists, which is the rate at which the gap between the two methods is closing.
A second, structurally distinct sub-population sits alongside the wild-type pool: hereditary ATTR carriers of the V122I (Val122Ile) variant, concentrated in the African American population at an estimated 3 to 4 percent carrier rate and totaling 100,000 or more people, the large majority still undiagnosed. ATTR polyneuropathy adds a third, smaller pool: 5,000 to 10,000 hereditary patients estimated against only 3,000 to 4,000 currently diagnosed and treated, a gap driven by a 4-to-5-year misdiagnosis delay in which ATTR-PN is commonly mistaken for CIDP or diabetic neuropathy. Our sensitivity analysis ranks the diagnosis-rate growth trajectory, not the underlying prevalence estimate, as the assumption most likely to move the sized total over a 3-to-5-year forecast window.
US ATTR sizing — epidemiology-based estimate versus registry-confirmed diagnosed population
| Sizing Method | Population Estimate | Source |
|---|---|---|
| Epidemiology-based (undiagnosed ATTRwt-CM, 70+ with HFpEF) | 500,000+ patients | Autopsy and imaging-cohort prevalence studies |
| Registry-based (diagnosed and treated) | 70,000-100,000 patients | IQVIA ATTR-CM diagnosis trends 2024; Pfizer/BridgeBio commercial data |
| Annual new-diagnosis rate | 10,000-15,000/year | Tc-PYP scintigraphy awareness trend, IQVIA 2024 |
| Hereditary Val122Ile sub-segment | 100,000+ estimated carriers (3-4% rate), mostly undiagnosed | Quarta CC et al., NEJM 2015 |
Sources: IQVIA ATTR-CM diagnosis trends 2024; Pfizer tafamidis and BridgeBio acoramidis commercial data; Quarta CC et al., NEJM 2015 (Val122Ile); Ruberg FL et al., Circulation 2019.
What this model answers
Every section answers a named commercial question your team is asking, scoped to your asset.
Delivers
- Epidemiology-based prevalence methodology
- registry/claims-based diagnosed-and-treated count
- the 10,000-15,000/year new-diagnosis rate closing the gap
Delivers
- Val122Ile carrier-rate methodology (3-4% in the African American population)
- the 100,000+ carrier estimate
- genetic-testing case-finding implications distinct from wild-type screening
Delivers
- Sensitivity ranking of every input
- why diagnosis-rate growth (Tc-PYP awareness) outranks the underlying prevalence estimate
- scenario ranges tied to screening-programme expansion
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Commission This ModelWhat's inside
- Why diagnosis-rate growth, not the underlying prevalence estimate, is the assumption most likely to move the total
- Pressure-tested against the epidemiology-versus-registry gap before the rest of the model is built out
- Autopsy and imaging-cohort prevalence for undiagnosed ATTRwt-CM in the 70+ HFpEF population
- The 500,000+ estimate this implies
- IQVIA diagnosis-trend and commercial-share data for the 70,000-100,000 diagnosed-and-treated population
- Tafamidis and acoramidis share cross-check
- Where the two methods agree and diverge
- The diagnosis-rate growth trajectory as the explanation for the gap
- Diagnosis-rate growth ranked above prevalence estimate as the binding assumption
- Scenario ranges tied to Tc-PYP screening-programme expansion
- The full triangulated model, including Val122Ile and ATTR-PN sub-segments, re-runnable with your own assumptions
- The open sizing questions your team must close before the number is used in planning
Included with every brief
How AXLRx builds this model
Prepared by MoatRx analysts.
Every AXLRx market sizing model triangulates at least two independent methods, epidemiology-based and registry/claims-based, before accepting a patient count. This is a sizing model, a static patient count, distinct from a Patient Flow or forecasting model that models dynamic revenue and uptake.
US ATTR sizing sources: IQVIA ATTR-CM diagnosis trends 2024, Pfizer and BridgeBio commercial data, Ruberg FL et al. (Circulation 2019), and Quarta CC et al. (NEJM 2015) for the Val122Ile carrier-rate estimate.
- Epidemiology-based undiagnosed ATTRwt-CM estimate verified against Ruberg FL et al., Circulation 2019, and autopsy/imaging-cohort prevalence literature
- Registry-based diagnosed-and-treated count and drug-share split verified against IQVIA ATTR-CM diagnosis trends 2024 and Pfizer/BridgeBio commercial data
- Val122Ile carrier-rate estimate verified against Quarta CC et al., NEJM 2015
Frequently asked questions
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