Continuous age- and sex-adjusted reference intervals of urinary markers for cerebral creatine deficiency syndromes: a novel approach to the definition of reference intervals

• Published in: Clinical chemistry (Baltimore, Md.) Md.), 2015-05, Vol.61 (5), p.760-768
• Main Authors: Mørkrid, Lars, Rowe, Alexander D, Elgstoen, Katja B P, Olesen, Jess H, Ruijter, George, Hall, Patricia L, Tortorelli, Silvia, Schulze, Andreas, Kyriakopoulou, Lianna, Wamelink, Mirjam M C, van de Kamp, Jiddeke M, Salomons, Gajja S, Rinaldo, Piero
• Format: Article
• Language: English
• Subjects: Age; Age Factors; Biomarkers - urine; Brain Diseases - urine; Creatine - deficiency; Creatine - urine; Expected values; Female; Humans; Laboratories; Male; Metabolism; Models, Biological; Pediatrics; Reference Standards; Regression analysis; Sex Factors; Statistical methods; Urine
• ISSN: 0009-9147; 1530-8561
• DOI: 10.1373/clinchem.2014.235564

Urinary concentrations of creatine and guanidinoacetic acid divided by creatinine are informative markers for cerebral creatine deficiency syndromes (CDSs). The renal excretion of these substances varies substantially with age and sex, challenging the sensitivity and specificity of postanalytical interpretation. Results from 155 patients with CDS and 12 507 reference individuals were contributed by 5 diagnostic laboratories. They were binned into 104 adjacent age intervals and renormalized with Box-Cox transforms (Ξ). Estimates for central tendency (μ) and dispersion (σ) of Ξ were obtained for each bin. Polynomial regression analysis was used to establish the age dependence of both μ[log(age)] and σ[log(age)]. The regression residuals were then calculated as z-scores = {Ξ - μ[log(age)]}/σ[log(age)]. The process was iterated until all z-scores outside Tukey fences ±3.372 were identified and removed. Continuous percentile charts were then calculated and plotted by retransformation. Statistically significant and biologically relevant subgroups of z-scores were identified. Significantly higher marker values were seen in females than males, necessitating separate reference intervals in both adolescents and adults. Comparison between our reconstructed reference percentiles and current standard age-matched reference intervals highlights an underlying risk of false-positive and false-negative events at certain ages. Disease markers depending strongly on covariates such as age and sex require large numbers of reference individuals to establish peripheral percentiles with sufficient precision. This is feasible only through collaborative data sharing and the use of appropriate statistical methods. Broad application of this approach can be implemented through freely available Web-based software.