Systematic Review Exposes Gaps in Statistical Methods for Paediatric Reference Intervals
A systematic review of 238 publications found that 70% of paediatric reference interval studies still rely on discrete age-group methods, which can produce misleading cut-offs near age boundaries. Only 23% employed continuous modelling approaches such as the LMS method or quantile regression. The authors call for broader adoption of continuous reference interval estimation and improved reporting of statistical methodology.
The original study
Statistical methods used in the estimation of age-specific paediatric reference intervals for laboratory blood tests: A systematic review.
- Authors
- Hoq M, Canterford L, Matthews S, Khanom G, Ignjatovic V, Monagle P, et al.
- Journal
- Clinical biochemistry
- Type
- Journal Article, Systematic Review
- PMID
- 32795472
Original abstract
INTRODUCTION: There is an emerging realisation that paediatric reference intervals (RIs) estimated using discrete age-groups may be misleading, especially close to age cut-off values. This limitation has been addressed by estimating RIs that vary continuously with age. This systematic review examines the range of statistical methods used over the past 25 years for estimation of age-specific RIs, and identifies trends in usage and reporting. METHODS: Literature searches were conducted using predefined search criteria for original publications between 1993 and 2018 on the MEDLINE and Embase databases. Data related to sample size, treatment of age (as categorical or continuous), and statistical methods were extracted from the selected publications. RESULTS: A total of 238 publications were reviewed. Not all publications reported the statistical methods used in different steps. Among the publications, 167 (70%) reported discrete age-group RIs, 54 (23%) reported continuous RIs and 17 (7%) reported both types of RIs. The nonparametric statistical method was commonly used for discrete age-group RIs (64%, n = 117), whereas a wide variety of curve-fitting approaches, including Cole's lambda-mu-sigma method (28%, n = 20), parametric curve-based methods (28%, n = 20), generalised additive model for location, scale and shape method (13%, n = 9) and quantile regression (11%, n = 8) were used for continuous RIs. CONCLUSIONS: Improvement in the reporting of statistical methods used for estimating age-specific paediatric RIs is required. There has been insufficient uptake of methods for producing continuous RIs, especially for biomarkers that display strong age-dependence.