Impact of the Choice of IGF-I Assay and Normative Dataset on the Diagnosis and Treatment of Growth Hormone Deficiency in Children

Abstract

Background: The analysis of insulin-like growth factor I (IGF-I) is an important tool for pediatricians in the diagnosis and treatment of growth hormone deficiency in children. However, significant differences exist in IGF-I assays and normative datasets, which can have important clinical consequences. Methods: IGF-I analyses were performed using the IDS-iSYS platform on 1,897 samples from pediatric patients (0.5–18 years old). Z-scores were calculated based on normative IGF-I data from Bidlingmaier et al. (SD-BM) [J Clin Endocrinol Metab. 2014 May; 99(5): 1712–21] and normative IGF-I data from the IGF-I harmonization program in the Netherlands (SD-NL). The differences in Z-scores were analyzed at relevant clinical decision points (–2 SD, +2 SD). These normative datasets were also compared to normative data reported by Elmlinger et al. [Clin Chem Lab Med. 2004; 42(6): 654–64]. Results: The difference in Z-score between SD-BM and SD-NL was highest in males between 0 and 3 years old, exceeding 2 SD. Clinically relevant discordance between both Z-scores at –2 and +2 SD was found in 12.7% of all samples. The IGF-I levels at –2 and +2 SD reported in the normative dataset of Elmlinger et al. were up to 100% higher than the IGF-I levels reported by Bidlingmaier et al. or the Dutch harmonization program. Conclusion: Pediatricians and laboratory specialists should be aware of relevant differences that can exist between IGF-I assays and normative data. Well-defined pediatric reference ranges for the IDS-iSYS platform are highly desirable.

Reference values for IGF-I serum concentration in an adult population: use of the VARIETE cohort for two new immunoassays

“…This discordance might have important implications for clinical practice. This does not mean that an assay is better than another, which cannot be indicated by this study, this only means that the use of different IGF-1 assays for a single patient might affect treatment decisions and dose adjustments in children and adults, especially when IGF-1 levels are borderline (6,11).…”

Important Tools for Use by Pediatric Endocrinologists in the Assessment of Short Stature

“…IGF-1 concentrations change with age and gender so that normative data have been determined from large numbers of healthy children and adolescents ( 87 ). This enables appropriate correction to provide SDS values, although the correct normative data should be used because diverse cohorts may give different reference measurements ( 90 , 91 ). Such differences may give clinically relevant variation when used to establish a diagnosis of GH deficiency ( 92 ).…”

IGF-1 and IGF-1 SDS – fit for purpose?

“…Dear Editor, Three recent publications (1,2,3) have reported that the differences in IGF-1 normative data significantly impact the classification of patients with growth hormone (GH) excess and deficiency disorders in such a way that clinical performance is severely flawed. This concerns not only pediatric but also adult patients.…”

“…Two extensive multicenter publications reporting IGF-1 reference values including SDS calculation, stressed the tremendous efforts needed to establish age-and sex-dependent normative data for IGF-1, the limited comparability of IGF-1 assays and the differences between various normative datasets available (5,6). However, despite all efforts, recent reports have shown that variation in IGF-1 normative data still impacts the classification of patients with GH-related disorders, not only in pediatric patients (GH deficiency) but also in adult acromegaly patients (1,2,3).…”

“…The 'Dutch' harmonized reference values are based on samples measured at university hospitals in Utrecht and Amsterdam, using DiaSorin Liaison® XL and Siemens Immulite® 1000 harmonized data, consisting of 1500 subjects (695 males and 805 females, 2-75 years of age). There were 207 pediatric samples from 0-18 years (106 males, 101 females), previously addressed in the publication of Broeren et al (3), used for the LMS curve fitting. In each of the age groups approximately 25 subjects were included.…”