Assessment of Amyloidosis Patient Pathways
Research type
Research Study
Full title
Using Patient Data in Amyloidosis to Understand Complex Diagnosis Pathways and Treatment Patterns
IRAS ID
200728
Contact name
Rito Bergemann
Contact email
Sponsor organisation
GlaxoSmithKline (GSK)
Duration of Study in the UK
2 years, 0 months, 0 days
Research summary
Amyloidosis is a rare life-limiting disease that can progress rapidly. Due to the rarity of amyloidosis and range of manifestations of the disease (often presenting as vague symptoms), patients often experience delays in diagnosis or may even remain undiagnosed. Delay in detection of amyloidosis may have an adverse impact on modifying the progression of the disease, even for those patients who receive therapy. Before a confirmed diagnosis of amyloidosis is finally provided to a patient, patients have often been seen by multiple physicians and may have received multiple incorrect diagnoses.
The aim of the research is to build a research platform for patients with amyloidosis. Management of all UK patients with amyloidosis is via the National Amyloidosis Centre (NAC) based at the Royal Free Hospital, although other aspects of their medical care are also be provided locally to the patient in secondary care and tertiary care centres.
Combination of the England HES data with the NAC clinical amyloidosis dataset will provide a better understanding of the patient pathways across the NHS secondary care system before and after diagnosis. This will help identify barriers to patient diagnosis and treatment and support existing NHS diagnostic / detection process for patients with amyloidosis.This research will be conducted as a joint collaboration between the NAC, GSK and IMS.
This research will focus on understanding
i) the healthcare resource utilization (based on HES data) of amyloidosis cohorts (defined by the NAC dataset through amyloid subtype and variant protein)
ii) testing the feasibility of finding undiagnosed patients through development of a predictive algorithm which could flag patients with a high probability of having particular subtypes of amyloidosis from their data “phenotype”. The potential is that this could support "non specialist" clinicians to assist earlier diagnosis.REC name
London - Surrey Research Ethics Committee
REC reference
16/LO/1065
Date of REC Opinion
20 Jun 2016
REC opinion
Favourable Opinion