Author(s)
Birkegård C1, Blevins LS2, Clemmons DR3, Fleseriu M4, Hoffman AR5, Kerr JM6, Sun T7, Tarp J8, Tritos NA9, Yuen K10
1Novo Nordisk A/S, Søborg, Denmark, 2University of California, San Francisco, San Francisco, CA, USA, 3University of North Carolina School of Medicine, Chapel Hill, NC, USA, 4Northwest Pituitary Center, Oregon Health and Science University, Portland, OR, USA, 5Stanford University, Stanford, CA, USA, 6University of Colorado Health Sciences Center, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA, 7Novo Nordisk A/S, Copenhagen, Denmark, 8Novo Nordisk A/S, Søborg, 84, Denmark, 9Massachusetts General Hospital, Boston, MA, USA, 10Barrow Pituitary Center, Barrow Neurological Institute and St. Joseph's Hospital and Medical Center, University of Arizona College of Medicine and Creighton School of Medicine, Phoenix, AZ, USA
OBJECTIVES: Adult growth hormone deficiency (AGHD) is associated with abnormal body composition, impaired cognitive function, reduced quality of life and, in patients with hypopituitarism, increased mortality. AGHD is often underdiagnosed and therefore, undertreated. This study aimed to develop an algorithm to categorise people into three groups by their likelihood of having AGHD, using administrative claims data. METHODS: Design of the initial algorithm was informed by published guidelines, combining diagnoses, procedures and pituitary medication codes, in order to categorise people by their likelihood of having AGHD (high, moderate or low). The algorithm underwent stepwise refinement based on feedback from an expert committee and thorough application of the algorithm to a US cohort (random sample of adults with ≥6 months of data in the Truven Health MarketScan Commercial Databases). RESULTS: For the high-likelihood group, the final algorithm required at least one of the following: ≥1 diagnosis of predefined conditions; diagnosis of ≥3 pituitary hormone deficiencies besides AGHD; GH replacement therapy (aged ≥18 years) and absence of a non-AGHD diagnosis; or treatment with ≥3 pituitary hormones besides GH (aged ≥18 years) and absence of a non-AGHD diagnosis. For the moderate-likelihood group, the final algorithm comprised not satisfying criteria for the high-likelihood group and either ≥1 diagnostic test for GHD or ≥2 pituitary hormone deficiency tests besides GH, each with unknown results. People who did not satisfy any of the aforementioned criteria were categorised into the low-likelihood group. Application of the final algorithm to the US cohort (10 million people) identified 0.55%, 18.36% and 81.09% with a high, moderate and low likelihood of having AGHD, respectively. CONCLUSIONS: This novel, administrative claims-based algorithm developed in the present study could enable clinicians to assess patients with varying likelihood of having AGHD, who may not have been diagnosed with GH deficiency, but may benefit from further testing.
Conference/Value in Health Info
2020-11, ISPOR Europe 2020, Milan, Italy
Value in Health, Volume 23, Issue S2 (December 2020)
Code
PDB82
Topic
Epidemiology & Public Health, Methodological & Statistical Research, Real World Data & Information Systems
Topic Subcategory
Health & Insurance Records Systems
Disease
Diabetes/Endocrine/Metabolic Disorders
