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Abstract Details

Epidemiology and Patient Journey in Inclusion Body Myositis (IBM): A Machine Learning (ML) Methodology Applied to Claims Data in the United States (US)
General Neurology
P10 - Poster Session 10 (5:00 PM-6:00 PM)
2-004

Evaluate epidemiology and diagnostic journey of US patients with IBM.
IBM, a rare, progressive disease characterized by invasion of healthy muscle by highly differentiated cytotoxic CD8+ T cells, is associated with loss of grip strength, difficulty walking, and/or dysphagia. Published global epidemiologic prevalence estimates range from 1.3−50.5/million. We sought to estimate the number of symptomatic undiagnosed IBM patients and define the patient journey.
Patients with ≥2 IBM International Classification of Diseases, Tenth Revision (ICD-10) diagnoses between 8/1/2019 and 7/30/2022 (Real Chemistry claims database) were compared with a matched cohort without IBM. Demographics, time to diagnosis, IBM-related symptoms, and resource utilization were assessed. Separately, we used machine learning (ML) to synthesize an “Ideal Patient Population” (IPP) consisting of individuals with ≥2 IBM ICD-10 diagnoses between 1/1/2020 and 4/15/2024 and ≥1 muscle biopsy or myositis antibody test to develop algorithms that identified symptomatic but undiagnosed patients.

Patient journey: 2435 patients were qualified. 61% were male; 71% were aged ≥65 years at diagnosis. Pain and weakness were predominant pre-diagnosis symptoms, followed by (vs controls): mobility conditions (23% vs 4%), falling (16% vs 4%), and difficulty swallowing (15% vs 2%). Median time between first IBM-related symptom and first IBM ICD-10 diagnosis claim was 4.4 years (3.3 years when pain was excluded as a symptom). In the year before diagnosis, 30% presented to the emergency department (controls, 17%); 20% who were admitted stayed an average of 1 week. Epidemiology: The IPP comprised 1633 patients; over 80% had a mobility condition, and 65% suffered a fall. The US diagnosed prevalence estimate was 26.45/million. Prevalence of symptomatic but undiagnosed patients ranged from 18.72 (highly specific algorithm) to 123.93/million (highly sensitive algorithm).
There are at least as many symptomatic undiagnosed patients with IBM as there are diagnosed patients. Earlier recognition of IBM is needed to provide appropriate care.
Authors/Disclosures
Devon Grochowski
PRESENTER 		Ms. Grochowski has received personal compensation for serving as an employee of IPM.ai, Real Chemistry.
David C. Bradley Mr. Bradley has nothing to disclose.
Raymond Mankoski Raymond Mankoski has received personal compensation for serving as an employee of The NemetzGroup LLC.
Karen Tubridy, PharmD Ms. Tubridy has received personal compensation for serving as an employee of Abcuro. Ms. Tubridy has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Verseau Therapeutics. Ms. Tubridy has stock in Akebia Therapeutics.