CHARACTERIZING WEIGHT DISTRIBUTION PATTERNS IN INDIVIDUALS WITH ACHONDROPLASIA ACROSS AGE: EVIDENCE FROM THE CLARITY COHORT WITH IMPLICATIONS FOR ECONOMIC MODELING
Author(s)
Andrew Howe, BA, PharmD1, Paul Miner, PharmD2, Carol Zhao, MS3, Longwen Zhao, MS3, Domenic Mantella, PharmD4, Kaysen Bala, PharmD4, Terry Cozza, PsyD4, Zeinab Choucair, MD4.
1National Director Field HEOR, Ascendis Pharma, Palo Alto, CA, USA, 2Medical, Ascendis Pharma, Palo Alto, CA, USA, 3Medical Affairs-Biostats, Ascendis Pharma, Palo Alto, CA, USA, 4Medical Affairs, Ascendis Pharma, Palo Alto, CA, USA.
1National Director Field HEOR, Ascendis Pharma, Palo Alto, CA, USA, 2Medical, Ascendis Pharma, Palo Alto, CA, USA, 3Medical Affairs-Biostats, Ascendis Pharma, Palo Alto, CA, USA, 4Medical Affairs, Ascendis Pharma, Palo Alto, CA, USA.
OBJECTIVES: Achondroplasia (ACH), a rare genetic condition characterized by skeletal dysplasia and disproportionate short stature, is associated with a wide range of complications and progressive weight accumulation relative to height. Accurate characterization of weight distribution across age groups is critical for pharmacoeconomic modeling, weight-based dose bands framework validation, and health technology assessment. This study quantified the proportion of individuals with ACH falling within the navepegritide weight-based dose bands across pediatric age strata to inform weight-based dosing frameworks and cost estimation in health economic evaluations.
METHODS: Weight data were simulated using parametric Monte Carlo simulation (normal distribution) and used to produce observations of sex-by-age-month strata. Weight bands were defined: 8-9.9, 10-13.4, 13.5-17.5, 17.6-23, 23.1-30.5, 30.6-41.2, 41.3-55.9, 56-73.5, and 73.6-90kg. The analysis was conducted using pediatric patients 2-18 years of age diagnosed with achondroplasia. Sensitivity analyses were conducted using published growth plate fusion data across different anatomical sites.
RESULTS: Results indicated that 3.6% of the simulations in the <10 kg weight band were predominantly <3 years of age, 27.4% of those in the 10-17.5kg range were predominately between 3-5 years of age, 34.5% of simulations were in the 17.6-30.5kg range and were predominately between 5-15 years of age, 30.8% in the 30.6-55.9kg range were predominately >15 years of age and 3.4% of those weighing ≥56 kg were predominately from 15-18 years of age. Sensitivity analyses using epiphyseal growth plate fusion (modified stage 5 grading) demonstrated comparable findings across assessment sites, with estimates for simulation weights ≥56 kg ranging from 1.9% (distal tibia) to 4.3% (radius).
CONCLUSIONS: Quantification of age-specific weight distribution across USPI-aligned weight bands provides a framework for weight-based dosing assessments and economic modeling in ACH. These findings may improve model input assumptions and support reimbursement decision-making. External validation is warranted to assess generalizability across healthcare settings.
METHODS: Weight data were simulated using parametric Monte Carlo simulation (normal distribution) and used to produce observations of sex-by-age-month strata. Weight bands were defined: 8-9.9, 10-13.4, 13.5-17.5, 17.6-23, 23.1-30.5, 30.6-41.2, 41.3-55.9, 56-73.5, and 73.6-90kg. The analysis was conducted using pediatric patients 2-18 years of age diagnosed with achondroplasia. Sensitivity analyses were conducted using published growth plate fusion data across different anatomical sites.
RESULTS: Results indicated that 3.6% of the simulations in the <10 kg weight band were predominantly <3 years of age, 27.4% of those in the 10-17.5kg range were predominately between 3-5 years of age, 34.5% of simulations were in the 17.6-30.5kg range and were predominately between 5-15 years of age, 30.8% in the 30.6-55.9kg range were predominately >15 years of age and 3.4% of those weighing ≥56 kg were predominately from 15-18 years of age. Sensitivity analyses using epiphyseal growth plate fusion (modified stage 5 grading) demonstrated comparable findings across assessment sites, with estimates for simulation weights ≥56 kg ranging from 1.9% (distal tibia) to 4.3% (radius).
CONCLUSIONS: Quantification of age-specific weight distribution across USPI-aligned weight bands provides a framework for weight-based dosing assessments and economic modeling in ACH. These findings may improve model input assumptions and support reimbursement decision-making. External validation is warranted to assess generalizability across healthcare settings.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
EE102
Topic
Economic Evaluation, Methodological & Statistical Research, Real World Data & Information Systems
Topic Subcategory
Value of Information
Disease
Genetic, Regenerative & Curative Therapies, Musculoskeletal Disorders (Arthritis, Bone Disorders, Osteoporosis, Other Musculoskeletal), Pediatrics, Rare & Orphan Diseases