ESTIMATION OF HEALTH-STATE UTILITY VALUES IN PHENYLKETONURIA (PKU), VIA CLINICAL-EXPERT PROXY ASSESSMENT WITH A GENERIC MEASURE (SF-12V2) OF PATIENT-REPORTED IMPACTS FROM A DISEASE-SPECIFIC MEASURE (PKU-QOL): INTERIM RESULTS
Author(s)
Thomas OConnell, BA, MA1, Suzanne Hollander, MS, RD, LDN2, Suresh Vijay, MD3, Nicola Longo, MD4, Roberto T Zori, MD5, Jon Woolley, MS6, Ioannis Tomazos, MBA, PhD7;
1Medicus Economics, LLC, Cambridge, MA, USA, 2Children's Hospital Boston, Boston, MA, USA, 3Birmingham Children's Hospital, Birmingham, United Kingdom, 4University of California Los Angeles, Los Angeles, CA, USA, 5University of Florida, Pediatric Genetics and Metabolism, Gainesville, FL, USA, 6Medicus Economics, New York, NY, USA, 7PTC Therapeutics, Executive Director, Head of GHEOR, South Plainfield, NJ, USA
1Medicus Economics, LLC, Cambridge, MA, USA, 2Children's Hospital Boston, Boston, MA, USA, 3Birmingham Children's Hospital, Birmingham, United Kingdom, 4University of California Los Angeles, Los Angeles, CA, USA, 5University of Florida, Pediatric Genetics and Metabolism, Gainesville, FL, USA, 6Medicus Economics, New York, NY, USA, 7PTC Therapeutics, Executive Director, Head of GHEOR, South Plainfield, NJ, USA
OBJECTIVES: Elevated blood-Phe levels and diet restrictions impact health-related quality of life (HRQoL) in phenylketonuria (PKU). This study estimates the independent impact of elevated Phe levels vs. dietary restriction on the health-state (HS) of individuals with PKU.
METHODS: Descriptions of the impacts of PKU on HRQoL dimensions were developed based on patient-report (N=16; age ≥12 years; mean blood Phe: 615 µmol/L) via the PKU Quality of Life (PKU-QOL) disease-specific measure collected during clinical trials. HS varied by blood-Phe levels (classified based on American College of Medical Genetics and Genomics guidelines) and diet restrictions: HS1, elevated blood-Phe levels, significant diet restrictions; HS2, target blood-Phe levels, significant diet restrictions; HS3, target blood-Phe levels, liberalized diet. Using a generic measure (SF-12®v2 Health Survey - Proxy Version) which addresses dimensions of HRQoL affected in PKU (physical health, emotional wellbeing, vitality, social activities), clinical experts provided proxy assessment of how each HS would affect patients. Finally, utility values were estimated by applying existing United Kingdom (UK) SF-6Dv2 preference weights to responses.
RESULTS: In the interim data cut reported here, N=15 experts had completed the survey. The HRQoL dimensions that were considered most improved with controlled (vs. uncontrolled) blood Phe were mental health, role functioning, and vitality. Dimensions most improved with liberalized (vs. restricted) diet were role functioning, social functioning, mental health, and vitality. Independent utility impacts were calculated (means); for blood-Phe control, HS2 vs. HS1 was 0.22; for diet restrictions, HS3 vs. HS2 was 0.08.
CONCLUSIONS: This study illustrates use of patient-reported impacts on a disease-specific HRQoL measure, to develop HS descriptions for clinical experts’ proxy assessment using a generic HRQoL measure, allowing estimation of HS utility values. Results reflect the independent HRQoL impacts of metabolic control vs. diet restrictions in PKU, and the nature of HRQoL dimensions contributing to these impacts.
METHODS: Descriptions of the impacts of PKU on HRQoL dimensions were developed based on patient-report (N=16; age ≥12 years; mean blood Phe: 615 µmol/L) via the PKU Quality of Life (PKU-QOL) disease-specific measure collected during clinical trials. HS varied by blood-Phe levels (classified based on American College of Medical Genetics and Genomics guidelines) and diet restrictions: HS1, elevated blood-Phe levels, significant diet restrictions; HS2, target blood-Phe levels, significant diet restrictions; HS3, target blood-Phe levels, liberalized diet. Using a generic measure (SF-12®v2 Health Survey - Proxy Version) which addresses dimensions of HRQoL affected in PKU (physical health, emotional wellbeing, vitality, social activities), clinical experts provided proxy assessment of how each HS would affect patients. Finally, utility values were estimated by applying existing United Kingdom (UK) SF-6Dv2 preference weights to responses.
RESULTS: In the interim data cut reported here, N=15 experts had completed the survey. The HRQoL dimensions that were considered most improved with controlled (vs. uncontrolled) blood Phe were mental health, role functioning, and vitality. Dimensions most improved with liberalized (vs. restricted) diet were role functioning, social functioning, mental health, and vitality. Independent utility impacts were calculated (means); for blood-Phe control, HS2 vs. HS1 was 0.22; for diet restrictions, HS3 vs. HS2 was 0.08.
CONCLUSIONS: This study illustrates use of patient-reported impacts on a disease-specific HRQoL measure, to develop HS descriptions for clinical experts’ proxy assessment using a generic HRQoL measure, allowing estimation of HS utility values. Results reflect the independent HRQoL impacts of metabolic control vs. diet restrictions in PKU, and the nature of HRQoL dimensions contributing to these impacts.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
PCR103
Topic
Patient-Centered Research
Topic Subcategory
Health State Utilities
Disease
SDC: Diabetes/Endocrine/Metabolic Disorders (including obesity), SDC: Rare & Orphan Diseases