Amyloidosis is a rare disease, multisystemic condition in which a protein is deposited in various organs and tissues, leading to their dysfunction and potentially fatal consequences.
Symptoms are not specific to amyloidosis and other conditions can cause similar clinical manifestations, thus the disease can be easily misdiagnosed or overlooked. Currently, real-life data on the patient journey, including clinical outcomes, disease progression, treatment patterns, healthcare resource utilisation and management of patients with amyloidosis is limited.
The overall aim of this study is to assess the distribution of the disease, pre- and post-diagnosis disease journeys, including baseline characteristics, treatment patterns and selected clinical, economic, and humanistic outcomes in patients with amyloidosis in the United Kingdom (UK). Utilizing UK Clinical Practice Research Database (CPRD) data for the historic anonymized patient’s records will allow us to have a better understanding of the early presentation and progression of the disease across the UK. This study will help to establish improved recommendations for diagnostic and therapeutic procedures in the follow-up of both pre-symptomatic patients and those with diagnosed and undiagnosed amyloidosis.
Amyloidosis is a set of disorders due to misfolding, aggregation and accumulation of certain proteins, known as amyloid deposits, in various tissues or organs leading to cellular damage, organ dysfunction, and eventually death. Based on the protein that forms the amyloid fibrils, amyloidosis can be classified as systemic light-chain (AL) amyloidosis, systemic amyloid A (AA) amyloidosis, and transthyretin amyloidosis (ATTR). A recent study using data from the UK National Amyloidosis Centre database, reported that the number of cases of amyloidosis increased by 670% from 1987-1999 to 2010-2019. (1)
Amyloidosis is often overlooked or misdiagnosed in patients, at least early in its course, due to the non-specific, heterogenous, multisystem presentation. As the disease progresses, the symptoms often mimic those of other more common diseases, further complicating and delaying diagnosis.
The overall aim of this study is to provide a UK perspective on the epidemiology, pre- and post-diagnosis disease journeys, including baseline characteristics, treatment patterns and selected clinical, economic, and humanistic outcomes in patients with amyloidosis, and to better understand how the disease is presented to support early recognition, diagnosis, and treatment for the benefit of patients in the UK.
Methods and analysis plan:
This study will include data from patients aged ≥18 years with a diagnosis code for amyloidosis.
We will include patients with diagnosed amyloidosis from the CPRD Aurum or GOLD data or from their linked HES records. Patients will be followed until exit from the database (loss to follow-up), death, or end of database period (data collection). Index date is defined as the first date of amyloidosis diagnosis anytime in a patient’s medical records. All available medical history before the index date will be used to assess patient demographics, clinical characteristics and healthcare resource utilisation before diagnosis.
The following will be measured at amyloidosis diagnosis (index date) and prior to diagnosis:
Patient characteristics; demographics, family history, comorbidities, key comorbidities and clinical characteristics of relevance to amyloidosis.
Healthcare resource utilisation (HCRU); number of hospital admissions, number of bed days, medications and total cost of care stratified by inpatient, outpatient, and pharmacy costs when available.
These will be measured after amyloidosis diagnosis (post index date):
Management, including pharmacologic treatment and patterns, as well as medical procedures.
Changes in clinical characteristics, functional status, HCRU, and health related quality of life (HRQoL) (when available).
Death and cause of death (when available).
He Gao - Chief Investigator - AstraZeneca Ltd - UK Headquarters
Emily Peach - Corresponding Applicant - AstraZeneca Ltd - UK Headquarters
Benjamin Heywood - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
Christopher Morgan - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
Corinna (Lai San) Hong - Collaborator - AstraZeneca Ltd - UK Headquarters
Elgan Mathias - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
Eric Wittbrodt - Collaborator - AstraZeneca Ltd - UK Headquarters
Ewan Laws - Collaborator - AstraZeneca Ltd - UK Headquarters
Jil Billy Mamza - Collaborator - AstraZeneca Ltd - UK Headquarters
Krister Järbrink - Collaborator - Astra Zeneca R&D Molndal Sweden
Leah Fisher - Collaborator - Pharmatelligence Limited t/a Human Data Sciences
Mara Habash - Collaborator - AstraZeneca Ltd - UK Headquarters
Meg Parbrook - Collaborator - AstraZeneca Ltd - UK Headquarters
Ruiqi Zhang - Collaborator - AstraZeneca Ltd - UK Headquarters
Shikta Das - Collaborator - AstraZeneca Ltd - UK Headquarters
Stefan Franzén - Collaborator - AstraZeneca AB (Sweden)
Emily Peach - Collaborator - AstraZeneca Ltd - UK Headquarters
Ewan Laws - Collaborator - AstraZeneca Ltd - UK Headquarters
HES Accident and Emergency;HES Admitted Patient Care;HES Diagnostic Imaging Dataset;HES Outpatient;ONS Death Registration Data;Patient Level Index of Multiple Deprivation;Practice Level Index of Multiple Deprivation