Identification and mapping of Real-World Data Sources for Giant Cell Arteritis (GCA) and Polymyalgia Rheumatica (PMR)
Author(s)
Julie Le Moal Mouchet, PhD1, Valeria Jordan Mondragon, Physician2, Samprati Avasthi, MPH3, Jagrut Vaishnav, Postgraduate in Pharmacy3;
1Novartis Pharma AG, Basel, Switzerland, 2Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA, 3Novartis Healthcare Pvt Ltd, Hyderabad, India
1Novartis Pharma AG, Basel, Switzerland, 2Novartis Pharmaceuticals Corporation, East Hanover, NJ, USA, 3Novartis Healthcare Pvt Ltd, Hyderabad, India
Presentation Documents
OBJECTIVES: In recent years, there has been a growing demand for real-world data (RWD) as supportive evidence to traditional clinical studies. We aimed to identify real-world datasources for Giant Cell Arteritis (GCA) and Polymyalgia Rheumatica (PMR).
METHODS: A targeted literature review was conducted using MEDLINE and EMBASE for the last 5 years (2019 - May 2024) to identify publications on RWD for GCA and PMR. The search strategy was built using the PICO framework and a 2-step screening process on abstracts and full-texts was performed. A list of unique GCA and PMR datasources was derived. Detailed information for 44 variables was extracted, covering datasource type, study design, demographics, risk factors, biopsy, imaging techniques, clinical and laboratory parameters, treatment, relapse, death, hospital visits/readmissions, emergency visits, costs, patient-reported outcomes (PRO), and potential data access and linkage with other sources.
RESULTS: A total of 2242 publications were retrieved from the literature search and 99 unique datasources were identified; 30% were disease-specific and 70% were generic. Among the disease-specific datasources, most were focused on GCA (n=25; 83%), followed by PMR (n=2; 7%) and both indications (n=3; 10%). Europe (83%) was largely covered, followed by North America (13%) and Japan (3%). A total of 10 registries, mainly focusing on GCA, were identified. Across all sources (n=99), the most widely reported parameters were age (95%), gender (93%), labs including C-reactive protein (CRP; 62%) and erythrocyte sedimentation rate (ESR; 48%), glucocorticoids (60%), biopsy (48%), visual complications (46%), certain comorbidities like diabetes mellitus (44%). The least reported parameters include genetics (2%), emergency visits and costs (3%), and PROs (1-3%).
CONCLUSIONS: There is a lack of disease-specific sources for both GCA and PMR, with only 9 and 1 registries identified respectively. This underscores the need for future collaborations to collect robust RWD to better understand GCA and PMR.
METHODS: A targeted literature review was conducted using MEDLINE and EMBASE for the last 5 years (2019 - May 2024) to identify publications on RWD for GCA and PMR. The search strategy was built using the PICO framework and a 2-step screening process on abstracts and full-texts was performed. A list of unique GCA and PMR datasources was derived. Detailed information for 44 variables was extracted, covering datasource type, study design, demographics, risk factors, biopsy, imaging techniques, clinical and laboratory parameters, treatment, relapse, death, hospital visits/readmissions, emergency visits, costs, patient-reported outcomes (PRO), and potential data access and linkage with other sources.
RESULTS: A total of 2242 publications were retrieved from the literature search and 99 unique datasources were identified; 30% were disease-specific and 70% were generic. Among the disease-specific datasources, most were focused on GCA (n=25; 83%), followed by PMR (n=2; 7%) and both indications (n=3; 10%). Europe (83%) was largely covered, followed by North America (13%) and Japan (3%). A total of 10 registries, mainly focusing on GCA, were identified. Across all sources (n=99), the most widely reported parameters were age (95%), gender (93%), labs including C-reactive protein (CRP; 62%) and erythrocyte sedimentation rate (ESR; 48%), glucocorticoids (60%), biopsy (48%), visual complications (46%), certain comorbidities like diabetes mellitus (44%). The least reported parameters include genetics (2%), emergency visits and costs (3%), and PROs (1-3%).
CONCLUSIONS: There is a lack of disease-specific sources for both GCA and PMR, with only 9 and 1 registries identified respectively. This underscores the need for future collaborations to collect robust RWD to better understand GCA and PMR.
Conference/Value in Health Info
2025-05, ISPOR 2025, Montréal, Quebec, CA
Value in Health, Volume 28, Issue S1
Code
RWD119
Topic
Real World Data & Information Systems
Disease
SDC: Musculoskeletal Disorders (Arthritis, Bone Disorders, Osteoporosis, Other Musculoskeletal), SDC: Systemic Disorders/Conditions (Anesthesia, Auto-Immune Disorders (n.e.c.), Hematological Disorders (non-oncologic), Pain)