Indirect determination of biochemistry reference intervals using outpatient data

Abstract

The aim of this study was to determine reference intervals in an outpatient population from Vall d’Hebron laboratory using an indirect approach previously described in a Dutch population (NUMBER project). We used anonymized test results from individuals visiting general practitioners and analysed during 2018. Analytical quality was assured by EQA performance, daily average monitoring and by assessing longitudinal accuracy between 2018 and 2020 (using trueness verifiers from Dutch EQA). Per test, outliers by biochemically related tests were excluded, data were transformed to a normal distribution (if necessary) and means and standard deviations were calculated, stratified by age and sex. In addition, the reference limit estimator method was also used to calculate reference intervals using the same dataset. Finally, for standardized tests reference intervals obtained were compared with the published NUMBER results. Reference intervals were calculated using data from 509,408 clinical requests. For biochemical tests following a normal distribution, similar reference intervals were found between Vall d’Hebron and the Dutch study. For creatinine and urea, reference intervals increased with age in both populations. The upper limits of Gamma-glutamyl transferase were markedly higher in the Dutch study compared to Vall d’Hebron results. Creatine kinase and uric acid reference intervals were higher in both populations compared to conventional reference intervals. Medical test results following a normal distribution showed comparable and consistent reference intervals between studies. Therefore a simple indirect method is a feasible and cost-efficient approach for calculating reference intervals. Yet, for generating standardized calculated reference intervals that are traceable to higher order materials and methods, efforts should also focus on test standardization and bias assessment using commutable trueness verifiers.

Harmonization of indirect reference intervals calculation by the Bhattacharya method

“…It is important to remark that the same dataset from 2018 was used in a previous study [20] for calculating reference intervals using two indirect methods: The Dutch NUMBER method [11] and the German reference limit estimator method [16]. The calculated reference intervals were comparable with the mentioned results [20] for all the included analytical test.…”

“…It is important to remark that the same dataset from 2018 was used in a previous study [20] for calculating reference intervals using two indirect methods: The Dutch NUMBER method [11] and the German reference limit estimator method [16]. The calculated reference intervals were comparable with the mentioned results [20] for all the included analytical test. Comparison with other important reference interval studies such as CALIPER (direct method) [27], ARIA (indirect method) [28] and NORIP (direct method) [29] also gives comparable results for all tests, except for ALT.…”

“…A total of 1,067,794 clinical requests were selected (509,408 from 2018 and 558,386 from 2019). A detailed description of the dataset from 2018 is provided elsewhere [20].…”

The BioRef Infrastructure, a Framework for Real-Time, Federated, Privacy-Preserving, and Personalized Reference Intervals: Design, Development, and Application

“…Such standardization requires clear classification systems, for example, for the nomenclature, terminology, units, and formats used, to ensure the reproducibility of all the steps of the complete laboratory testing procedure, possibly for international application [15,16]. This is an ongoing global process, as laboratories in Europe [17][18][19][20][21][22], Africa [23][24][25], North America [26], Asia [27][28][29] and Australia [30] aim at deriving nation-specific RIs through multicenter studies.…”

Cohort Profile: Swiss BioRef: The building blocks of a nationwide IT infrastructure in Switzerland for generating precise reference intervals

“…for the nomenclature, terminology, units and formats used, to ensure reproducibility of all the steps of the total laboratory testing procedure, possibly for international application [10,11]. This is an on-going global process, as laboratories in Europe [12][13][14][15][16][17], Africa [18][19][20], North America [21], Asia [22][23][24] and Australia [25] aim to derive nation-specific RIs with multicentre studies. Despite this welcome effort, most studies have been conducted with very lenient inclusion/exclusion criteria due to a missing overarching definition of "health", covering both the normative aspects (well-being and functioning) and more descriptive aspects of health evaluation (test result assessment).…”