Considerations for Modeling Caregiver Spillover Within Economic Evaluations for Neurological Disorders: Spinal Muscular Atrophy (SMA), Duchenne Muscular Dystrophy (DMD), and Multiple Sclerosis (MS)
Author(s)
Eric Eric, NGONGA, MSc, C Simone Sutherland, PhD, Chui-ying Yip, PhD, Katya Galactionova, PhD.
Access Evidence, Roche, Basel, Switzerland.
Access Evidence, Roche, Basel, Switzerland.
OBJECTIVES: Despite consensus to capture the societal impact of informal care within economic evaluation (Pennington et al. 20221, Henry et al. 20242), little is known about how current methods for incorporating caregiver quality of life (QoL) into cost-effectiveness analyses (CEA) differ across disease areas. Here, analyses are presented for capturing caregiver QoLs in SMA, DMD and MS.
METHODS: This study utilized natural history data in economic models for neurological disorders, focusing on patient and caregiver quality-adjusted life years (QALYs) from societal versus National Health Service (NHS) perspectives. Two key approaches were evaluated: 1) absolute health state utility values (HSUV) for patients and caregivers (i.e. family QALYs); and 2) patient HSUV combined with caregiver disutilities. Modelling settings (e.g., time horizon, discount rate), parameterization (e.g. age, number of caregivers), and assumptions were aligned to relevant best practices, with sources noted. Scenario analyses also considered additional impacts like caregiver bereavement disutility (Song et al. 20103, Pennington et al 20254).
RESULTS: Modelling with the absolute utility approach for patient and caregiver HSUVs captures the full QoL, but results may be driven by caregiver QALYs since untreated disease results in low QALYs for patients. This is seen in untreated pre-symptomatic SMA, where negative utility values in some health states led to an overall negative patient QALY, which may also mute caregiver disease-related differences. Across the three diseases, estimated caregiver QALYs differ primarily due to age of onset (pediatric versus adult), disease progression and survival rates, caregiving burden, duration of bereavement, data source and utility instruments used to inform bereavement disutility, and modeling parameters like the time horizon
CONCLUSIONS: Methodological approaches, utility data sources, modelling parameterization, and disease course impact caregiver spillover effects in neurological diseases. Alignment on approaches and their influence by disease area may help decision makers interpret the estimated impacts within HTA economic evaluations.
METHODS: This study utilized natural history data in economic models for neurological disorders, focusing on patient and caregiver quality-adjusted life years (QALYs) from societal versus National Health Service (NHS) perspectives. Two key approaches were evaluated: 1) absolute health state utility values (HSUV) for patients and caregivers (i.e. family QALYs); and 2) patient HSUV combined with caregiver disutilities. Modelling settings (e.g., time horizon, discount rate), parameterization (e.g. age, number of caregivers), and assumptions were aligned to relevant best practices, with sources noted. Scenario analyses also considered additional impacts like caregiver bereavement disutility (Song et al. 20103, Pennington et al 20254).
RESULTS: Modelling with the absolute utility approach for patient and caregiver HSUVs captures the full QoL, but results may be driven by caregiver QALYs since untreated disease results in low QALYs for patients. This is seen in untreated pre-symptomatic SMA, where negative utility values in some health states led to an overall negative patient QALY, which may also mute caregiver disease-related differences. Across the three diseases, estimated caregiver QALYs differ primarily due to age of onset (pediatric versus adult), disease progression and survival rates, caregiving burden, duration of bereavement, data source and utility instruments used to inform bereavement disutility, and modeling parameters like the time horizon
CONCLUSIONS: Methodological approaches, utility data sources, modelling parameterization, and disease course impact caregiver spillover effects in neurological diseases. Alignment on approaches and their influence by disease area may help decision makers interpret the estimated impacts within HTA economic evaluations.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
EE152
Topic
Economic Evaluation, Health Technology Assessment, Methodological & Statistical Research
Topic Subcategory
Novel & Social Elements of Value
Disease
Neurological Disorders, No Additional Disease & Conditions/Specialized Treatment Areas