Harnessing Digital Patient Monitoring and Primary Care Records to Map the Disease Burden of Multiple Myeloma in the United Kingdom
Author(s)
Kim Summers, BSc, MSc, PhD1, Orlando Agrippa, BSc, MBA1, Muna Yusuf, BSc, MSc1, Tushar Singh, MSc1, Simon Stern, MB BS, FRCP, FRCPath2, Andrea Preston, BPharm, MSc, MRPharmS1.
1Sanius Health, London, United Kingdom, 2Epsom & St Helier University Hospitals NHS Trust, Carshalton, United Kingdom.
1Sanius Health, London, United Kingdom, 2Epsom & St Helier University Hospitals NHS Trust, Carshalton, United Kingdom.
OBJECTIVES: To evaluate the feasibility and utility of combining longitudinal primary care (PC) data and patient-generated health data (PGHD) to characterise treatment exposure, symptom burden, and unmet needs in people with Multiple Myeloma (MM).
METHODS: Retrospective analysis performed for 275 UK patients with MM-linked CTV3 codes in PC records extracted data on demographics, clinical events, prescribing, and comorbidities. Prospective data (n=36) were captured (January-May 2025) using a patient co-designed digital interface collecting patient-reported outcomes (PROs; EQ-5D-5L, ‘My POS’) and wearable-derived metrics (sleep, activity, vitals). Variation by sex, age, and treatment line was analysed using linear mixed models.
RESULTS: The PC cohort (51% female; mean age 77) had a mean of 11 years since first diagnosis, with 53% deceased at censure. Across PC histories, patients averaged 20 unique repeat PC-issued medications, 31 CTV3 codes (essential hypertension (27%), deep venous thrombosis (17%), lower back pain (16%)), and 16 PC contacts annually. Females showed higher prescribing rates (21.5 vs. 18.4) and comorbidity burden (35.5 vs. 25.5 codes). Patients aged 80+ had greater comorbidity (34.5) despite fewer contacts.
App-based monitoring over a median 70 days captured 38,827 datapoints. 23 reported first (1L), 4 second (2L), 3 third-line or above (3L+), and 4 ‘off-treatment’. Weakness scored highest for symptom severity (3.8/5), followed by drowsiness (2.7) and poor mobility (2.6). EQ-5D-5L averaged 0.706 and VAS 66.0.
Subgroup variation saw females record lower SpO2 (96% vs. 98%, p=0.002). Tingling severity increased with age (p=0.031). 3L+ reported higher breathlessness than off-treatment (4.9 vs. 0.5, p=0.050), and 1L recorded higher SpO2 than 3L+ (98% vs. 96%, p=0.046).
CONCLUSIONS: This work demonstrates how clinical and real-time PGHD can complement each other to build a more complete picture of MM burden, revealing initial variation across subgroups. Such approaches have the potential to inform responsive, personalised models of care and improve outcomes monitoring in routine practice.
METHODS: Retrospective analysis performed for 275 UK patients with MM-linked CTV3 codes in PC records extracted data on demographics, clinical events, prescribing, and comorbidities. Prospective data (n=36) were captured (January-May 2025) using a patient co-designed digital interface collecting patient-reported outcomes (PROs; EQ-5D-5L, ‘My POS’) and wearable-derived metrics (sleep, activity, vitals). Variation by sex, age, and treatment line was analysed using linear mixed models.
RESULTS: The PC cohort (51% female; mean age 77) had a mean of 11 years since first diagnosis, with 53% deceased at censure. Across PC histories, patients averaged 20 unique repeat PC-issued medications, 31 CTV3 codes (essential hypertension (27%), deep venous thrombosis (17%), lower back pain (16%)), and 16 PC contacts annually. Females showed higher prescribing rates (21.5 vs. 18.4) and comorbidity burden (35.5 vs. 25.5 codes). Patients aged 80+ had greater comorbidity (34.5) despite fewer contacts.
App-based monitoring over a median 70 days captured 38,827 datapoints. 23 reported first (1L), 4 second (2L), 3 third-line or above (3L+), and 4 ‘off-treatment’. Weakness scored highest for symptom severity (3.8/5), followed by drowsiness (2.7) and poor mobility (2.6). EQ-5D-5L averaged 0.706 and VAS 66.0.
Subgroup variation saw females record lower SpO2 (96% vs. 98%, p=0.002). Tingling severity increased with age (p=0.031). 3L+ reported higher breathlessness than off-treatment (4.9 vs. 0.5, p=0.050), and 1L recorded higher SpO2 than 3L+ (98% vs. 96%, p=0.046).
CONCLUSIONS: This work demonstrates how clinical and real-time PGHD can complement each other to build a more complete picture of MM burden, revealing initial variation across subgroups. Such approaches have the potential to inform responsive, personalised models of care and improve outcomes monitoring in routine practice.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
PCR104
Topic
Clinical Outcomes, Patient-Centered Research, Real World Data & Information Systems
Topic Subcategory
Patient Engagement, Patient-reported Outcomes & Quality of Life Outcomes
Disease
Oncology, Rare & Orphan Diseases