Timing and co-occurrence of symptoms prior to a diagnosis of light chain (AL) amyloidosis. Blood Cancer J 2024 May 26;14(1):61
Date
05/26/2024Pubmed ID
38796476Pubmed Central ID
PMC11127981DOI
10.1038/s41408-024-01040-8Scopus ID
2-s2.0-85194268737 (requires institutional sign-in at Scopus site)Abstract
It is well-established that most patients with systemic light chain (AL) amyloidosis have multi-organ involvement and are often diagnosed after a lag period of increasing symptoms. We leverage electronic health record (EHR) data from the TriNetX research network to describe the incidence, timing, and co-occurrence of precursor conditions of interests in a cohort of AL amyloidosis patients identified between October 2015-December 2020. Nineteen precursor diagnoses of interest representing features of AL amyloidosis were identified using ICD codes up to 36 months prior to AL amyloidosis diagnosis. Among 1,401 patients with at least 36 months of EHR data prior to AL amyloidosis diagnosis, 46% were females, 16% were non-Hispanic Black, and 6% were Hispanic. The median age was 71 (range, 21-91) years. The median number of precursor diagnoses was 5 with dyspnea and fatigue being the most prevalent. The time from the first occurrence of a precursor to AL diagnosis ranged from 3.2 to 21.4 months. Analyses of pairwise co-occurrence of specific diagnoses indicated a high association (Cole's coefficient >0.6) among the examined precursor diagnoses. These findings provide novel information about the timing and co-occurrence of key precursor conditions and could be used to develop algorithms for early identification of AL amyloidosis.
Author List
Singh A, Szabo A, Lian Q, Pezzin L, Sparapani R, D'Souza AAuthors
Liliana Pezzin PhD, JD Professor in the Institute for Health and Equity department at Medical College of WisconsinRodney Sparapani PhD Associate Professor in the Data Science Institute department at Medical College of Wisconsin
Aniko Szabo PhD Professor in the Data Science Institute department at Medical College of Wisconsin
MESH terms used to index this publication - Major topics in bold
AdultAged
Aged, 80 and over
Electronic Health Records
Female
Humans
Immunoglobulin Light-chain Amyloidosis
Male
Middle Aged
Time Factors
Young Adult
