THE EXTENT OF TREATMENT RESPONSE AND PREFERENCE HETEROGENEITY IN MAJOR DEPRESSIVE DISORDER: IMPLICATIONS FOR POPULATION-LEVEL RESOURCE ALLOCATION
Author(s)
Jason Shafrin, PhD1, Nadine Zawadzki, PhD2, Cheryl Neslusan, PhD3.
1Senior Managing Director, Center for Healthcare Economics and Policy, FTI Consulting, Los Angeles, CA, USA, 2FTI Consulting, Los Angeles, CA, USA, 3Johnson and Johnson, Titusville, NJ, USA.
1Senior Managing Director, Center for Healthcare Economics and Policy, FTI Consulting, Los Angeles, CA, USA, 2FTI Consulting, Los Angeles, CA, USA, 3Johnson and Johnson, Titusville, NJ, USA.
OBJECTIVES: Health Economics Methods Advisory (HEMA) draft guidance recommends using "average preferences" for population-level resource allocation decisions. However, this approach may be problematic when treatments have heterogeneous treatment responses or when patient preferences are heterogeneous. As a first step in investigating the implications of these potential drivers of systematic differences in outcomes and/or costs, this study reviewed published literature in the disease area of major depressive disorder (MDD) that examined treatment response heterogeneity, patient preferences, and preference impact on treatment effectiveness via adherence.
METHODS: Targeted literature searches were conducted in PubMed and Google Scholar, supplemented with forward/backward citation searches. We identified: (1) clinical and real-world data studies that tested for variation in treatment responses across patient subgroups; (2) quantitative and qualitative patient preference studies; and (3) studies linking preferences to adherence and outcomes. The final set of studies included those that were published in 2010 or later.
RESULTS: Twenty-three studies documented treatment response heterogeneity. Effect modifiers included: inflammatory/metabolic biomarkers (n=6), demographic characteristics (n=5), neurophysiology (n=4), psychological traits (n=2), symptoms (n=2), comorbidities (n=3), and medical history (n=1). Across patient subgroups, the relative benefit of one treatment vs. another in achieving remission ranged from 1.3-fold to 15-fold. Nineteen studies showed variation in patient preferences for treatment attributes including modality (n=13), efficacy (n=6), side effects (n=6), cost (n=1), convenience (n=1), intensity (n=1), and lifestyle changes (n=1). Subgroups explored included different sociodemographic characteristics, degrees of disease severity, and treatment histories. Five studies reported on evidence linking treatment preference to adherence and/or health outcomes.
CONCLUSIONS: There is marked systematic treatment response and preference heterogeneity in MDD across multiple patient subgroups. Population-level resource allocation decisions that ignore such factors will result in wasted resources and poorer health outcomes. Future research will estimate the impact of such decisions (e.g. “one-size-fits-all” step therapy protocols) on outcomes and costs in MDD.
METHODS: Targeted literature searches were conducted in PubMed and Google Scholar, supplemented with forward/backward citation searches. We identified: (1) clinical and real-world data studies that tested for variation in treatment responses across patient subgroups; (2) quantitative and qualitative patient preference studies; and (3) studies linking preferences to adherence and outcomes. The final set of studies included those that were published in 2010 or later.
RESULTS: Twenty-three studies documented treatment response heterogeneity. Effect modifiers included: inflammatory/metabolic biomarkers (n=6), demographic characteristics (n=5), neurophysiology (n=4), psychological traits (n=2), symptoms (n=2), comorbidities (n=3), and medical history (n=1). Across patient subgroups, the relative benefit of one treatment vs. another in achieving remission ranged from 1.3-fold to 15-fold. Nineteen studies showed variation in patient preferences for treatment attributes including modality (n=13), efficacy (n=6), side effects (n=6), cost (n=1), convenience (n=1), intensity (n=1), and lifestyle changes (n=1). Subgroups explored included different sociodemographic characteristics, degrees of disease severity, and treatment histories. Five studies reported on evidence linking treatment preference to adherence and/or health outcomes.
CONCLUSIONS: There is marked systematic treatment response and preference heterogeneity in MDD across multiple patient subgroups. Population-level resource allocation decisions that ignore such factors will result in wasted resources and poorer health outcomes. Future research will estimate the impact of such decisions (e.g. “one-size-fits-all” step therapy protocols) on outcomes and costs in MDD.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
HPR109
Topic
Health Policy & Regulatory
Topic Subcategory
Reimbursement & Access Policy