Comparison of four algorithms on establishing continuous reference intervals for pediatric analytes with age-dependent trend

Development of next-generation reference interval models to establish reference intervals based on medical data: current status, algorithms and future consideration

Evidence derived from laboratory medicine plays a pivotal role in the diagnosis, treatment monitoring, and prognosis of various diseases. Reference intervals (RIs) are indispensable tools for assessing test results. The accuracy of clinical decision-making relies directly on the appropriateness of RIs. With the increase in real-world studies and advances in computational power, there has been increased interest in establishing RIs using big data. This approach has demonstrated cost-effectiveness and applicability across diverse scenarios, thereby enhancing the overall suitability of the RI to a certain extent. However, challenges persist when tests results are influenced by age and sex. Reliance on a single RI or a grouping of RIs based on age and sex can lead to erroneous interpretation of results with significant implications for clinical decision-making. To address this issue, the development of next generation of reference interval models has arisen at an historic moment. Such models establish a curve relationship to derive continuously changing reference intervals for test results across different age and sex categories. By automatically selecting appropriate RIs based on the age and sex of patients during result interpretation, this approach facilitates clinical decision-making and enhances disease diagnosis/treatment as well as health management practices. Development of next-generation reference interval models use direct or indirect sampling techniques to select reference individuals and then employed curve fitting methods such as splines, polynomial regression and others to establish continuous models. In light of these studies, several observations can be made: Firstly, to date, limited interest has been shown in developing next-generation reference interval models, with only a few models currently available. Secondly, there are a wide range of methods and algorithms for constructing such models, and their diversity may lead to confusion. Thirdly, the process of constructing next-generation reference interval models can be complex, particularly when employing indirect sampling techniques. At present, normative documents pertaining to the development of next-generation reference interval models are lacking. In summary, this review aims to provide an overview of the current state of development of next-generation reference interval models by defining them, highlighting inherent advantages, and addressing existing challenges. It also describes the process, advanced algorithms for model building, the tools required and the diagnosis and validation of models. Additionally, a discussion on the prospects of utilizing big data for developing next-generation reference interval models is presented. The ultimate objective is to equip clinical laboratories with the theoretical framework and practical tools necessary for developing and optimizing next-generation reference interval models to establish next-generation reference intervals while enhancing the use of medical data resources to facilitate precision medicine.

Reference intervals: past, present, and future

Clinical laboratory test results alone are of little value in diagnosing, treating, and monitoring health conditions; as such, a clinically actionable cutoff or reference interval is required to provide context for result interpretation. Healthcare practitioners base their diagnoses, follow-up treatments, and subsequent testing on these reference points. However, they may not be aware of inherent limitations related to the definition and derivation of reference intervals. Laboratorians are responsible for providing the reference intervals they report with results. Yet, the establishment and verification of reference intervals using conventional direct methods are complicated by resource constraints or unique patient demographics. To facilitate standardized reference interval best practices, multiple global scientific societies are actively drafting guidelines and seeking funding to promote these initiatives. Numerous national and international multicenter collaborations demonstrate the ability to leverage combined resources to conduct large reference interval studies by direct methods. However, not all demographics are equally accessible. Novel indirect methods are attractive solutions that utilize computational methods to define reference distributions and reference intervals from mixed data sets of pathologic and non-pathologic patient test results. In an effort to make reference intervals more accurate and personalized, individual-based reference intervals are shown to be more useful than population-based reference intervals in detecting clinically significant analyte changes in a patient that might otherwise go unrecognized when using wider, population-based reference intervals. Additionally, continuous reference intervals can provide more accurate ranges as compared to age-based partitions for individuals that are near the ends of the age partition. The advantages and disadvantages of different reference interval approaches as well as the advancement of non-conventional reference interval studies are discussed in this review.

A pipeline for the fully automated estimation of continuous reference intervals using real-world data

Reference intervals are essential for interpreting laboratory test results. Continuous reference intervals precisely capture physiological age-specific dynamics that occur throughout life, and thus have the potential to improve clinical decision-making. However, established approaches for estimating continuous reference intervals require samples from healthy individuals, and are therefore substantially restricted. Indirect methods operating on routine measurements enable the estimation of one-dimensional reference intervals, however, no automated approach exists that integrates the dependency on a continuous covariate like age. We propose an integrated pipeline for the fully automated estimation of continuous reference intervals expressed as a generalized additive model for location, scale and shape based on discrete model estimates using an indirect method (refineR). The results are free of subjective user-input, enable conversion of test results into z-scores and can be integrated into laboratory information systems. Comparison of our results to established and validated reference intervals from the CALIPER and PEDREF studies and manufacturers' package inserts shows good agreement of reference limits, indicating that the proposed pipeline generates high-quality results. In conclusion, the developed pipeline enables the generation of high-precision percentile charts and continuous reference intervals. It represents the first parameter-less and fully automated solution for the indirect estimation of continuous reference intervals.

Trajectories of glycated hemoglobin of T2DM and progress of arterial stiffness: a prospective study

AIM

This study aimed to describe the different trajectories groups of HbA1c during the long-term treatment of diabetes and explore the effect of glycemic control on the progression of arterial stiffness.

METHOD

The study participants registered at the National Metabolic Management Center (MMC) of Beijing Luhe hospital. The latent class mixture model (LCMM) was used to identify distinct trajectories of HbA1c. We calculated the change value of baPWV (ΔbaPWV) of each participant between the whole follow-up time as the primary outcome. Then we examined the associations between each HbA1c trajectory pattern and ΔbaPWV using covariate-adjusted means (SE) of ΔbaPWV, which were calculated by multiple linear regression analyses adjusted for the covariates.

RESULTS

After data cleaning, a total of 940 type 2 diabetes patients aged 20-80 years were included in this study. According to the BIC, we identified four discrete trajectories of HbA1c: Low-stable, U-shape, Moderate-decrease, High-increase, respectively. Compared with the low-stable group of HbA1c, the adjusted mean values of baPWV were significantly higher in U-shape, Moderate-decrease, and High-increase groups (all P < 0.05, and P for trend < 0.001), the mean values (SE) were 82.73 (0.08), 91.19 (0.96), 116.00 (0.81) and 223.19 (11.54), respectively.

CONCLUSION

We found four different trajectories groups of HbA1c during the long-term treatment of diabetes. In addition, the result proves the causal relationship between long-term glycemic control and arterial stiffness on a time scale.

LMS-based continuous reference percentiles for 14 laboratory parameters in the CALIPER cohort of healthy children and adolescents

OBJECTIVES

Marked physiological changes in growth and development present challenges in defining pediatric reference intervals for biomarkers of health and disease. Lambda, Mu, and Sigma (LMS)-based statistical modeling provides a continuous normal distribution by negating skewness and variation, and is commonly used to establish growth charts. Such LMS reference curves are suggested to enhance laboratory test result interpretation. The current study establishes LMS-based continuous reference percentiles for 14 biomarkers in the CALIPER cohort of healthy children and adolescents.

METHODS

Data from healthy children and adolescents aged 1-<19 years were used to establish continuous reference percentiles using a novel LMS-based statistical method, including 2.5th, 25th, 50th, 75th, and 97.5th percentiles. The LMS approach applies a Box-Cox data transformation and summarizes continuous distributions by age via three curves: skewness (Lambda), median (Mu), and coefficient of variation (Sigma).

RESULTS

LMS-based percentiles and z-scores were generated for 14 common pediatric biomarkers that demonstrate dynamic concentration patterns with age (e.g., alkaline phosphatase) and/or wherein the magnitude of difference from the population mean may be clinically relevant (e.g., triglycerides). The LMS model captured age- and sex-specific distributions accurately and was not substantially influenced by outlying points.

CONCLUSIONS

This is the first study to establish LMS-based continuous reference percentiles for biochemical markers in a healthy Canadian pediatric population. The current LMS-based approach builds upon previous continuous reference interval models by providing graded percentiles to improve test result interpretation, particularly with repeated measures over time. This method may assist in facilitating a patient-centered approach to laboratory medicine.

Accuracy of equations for predicting 24-h urinary potassium excretion from spot urine samples in Chinese children

Accurate assessments of potassium intake in children are important for the early prevention of CVD. Currently, there is no simple approach for accurate estimation of potassium intake in children. We aim to evaluate the accuracy of 24-h urinary potassium excretion (24UKV) estimation in children using three common equations: the Kawasaki, Tanaka and Mage formulas, in a hospital-based setting. A total of 151 participants aged 5-18 years were initially enrolled, and spot urine samples were collected in the whole 24-h duration to measure the concentrations of potassium and creatinine. We calculated the mean difference, absolute and relative difference and misclassification rate between measured 24UKV and the predicted ones using Kawasaki, Tanaka and Mage formulas in 129 participants. The mean measured 24UKV was 1193·3 mg/d in our study. Mean differences between estimated and measured 24UKV were 1215·6, -14·9 and 230·3 mg/d by the Kawasaki, Tanaka and Mage formulas, respectively. All estimated 24UKV were significantly different from the measured values in all the time point (all P < 0·05), except for the predicted values from Tanaka formula using morning, afternoon and evening spot urine. The proportions with relative differences over 40 % were 87·2%, 32·5% and 47·3 % for Kawasaki, Tanaka and Mage formulas, respectively. Misclassification rates were 91·5 % for Kawasaki, 44·4 % for Tanaka and 58·9 % for Mage formula at the individual level. Our findings showed that misclassification could occur on the individual level when using Kawasaki, Tanaka and Mage formulas to estimate 24UKV from spot urine in the child population.

Current State of Pediatric Reference Intervals and the Importance of Correctly Describing the Biochemistry of Child Development: A Review

Importance

Appropriately established pediatric reference intervals are critical to the clinical decision-making process and should reflect the physiologic changes that occur during healthy child development. Reference intervals used in pediatric care today remain highly inconsistent across a broad range of common clinical biomarkers.

Observations

This narrative review assesses biomarker-specific pediatric reference intervals and their clinical utility with respect to the underlying biological changes occurring during development. Pediatric reference intervals from PubMed-indexed articles published from January 2015 to April 2021, commercial laboratory websites, study cohorts, and pediatric reference interval books were all examined. Although large numbers of pediatric reference intervals are published for some biomarkers, very few are used by clinical and commercial laboratories. The patterns, extent, and timing of biomarker changes are highly variable, particularly during developmental stages with rapid physiologic changes. However, many pediatric reference intervals do not capture these changes and thus do not accurately reflect the underlying biochemistry of development, resulting in significant inconsistencies between reference intervals.

Conclusions and Relevance

There is a need to correctly describe the biochemistry of child development as well as to identify strategies to develop accurate and consistent pediatric reference intervals for improved pediatric care.

Age and sex specific reference intervals of 13 hematological analytes in Chinese children and adolescents aged from 28 days up to 20 years: the PRINCE study

OBJECTIVES

Pediatric Reference Intervals in China (PRINCE) is a nationwide initiative that aims to establish and validate harmonized reference intervals (RIs) for Chinese children and adolescents, in which 15,150 healthy volunteers aged up to 20 years were recruited from 11 centers to establish RIs and 7,557 children and adolescents were enrolled from 21 centers to validate RIs.

METHODS

The complete blood cell counts (CBC) of venous whole blood were measured by hematology analyzers through Sysmex systems in different centers. Age- and sex-specific RIs were calculated according to the guidelines.

RESULTS

Unlike adults with certain levels of analyte concentrations, hematological parameters of children changed through growth and development. Red blood cell counts, hemoglobin, and hematocrit increased with age, and revealed higher concentrations in boys than girls after puberty. White blood cell counts and platelet counts showed significant higher levels than adults before 2 years of age, and then gradually decreased without distinct sex differences. In addition, lymphocyte counts decreased with age while neutrophil counts showed an opposite trend. The lower and upper limits of pediatric RIs of CBC were different from those of adults.

CONCLUSIONS

The validation of RIs indicated that the PRINCE study provided a version of RIs suitable for most of regions in China. This first harmonized pediatric RIs of CBC across China provided a robust database to understand the dynamic changes of hematologic parameters from birth to adolescence, and will contribute to clinical diagnosis and prognosis evaluation for pediatric patients as well.

Reference equations for pulmonary diffusing capacity using segmented regression show similar predictive accuracy as GAMLSS models

Purpose

To determine whether generalised additive models of location, scale and shape (GAMLSS) developed for pulmonary diffusing capacity are superior to segmented (piecewise) regression models, and to update reference equations for pulmonary diffusing capacity for carbon monoxide (DLCO) and nitric oxide (DLNO), which may be affected by the equipment used for its measurement.

Methods

Data were pooled from five studies that developed reference equations for DLCO and DLNO (n=530 F/546 M; 5–95 years old, body mass index 12.4–39.0 kg/m²). Reference equations were created for DLCO and DLNO using both GAMLSS and segmented linear regression. Cross-validation was applied to compare the prediction accuracy of the two models as follows: 80% of the pooled data were used to create the equations, and the remaining 20% was used to examine the fit. This was repeated 100 times. Then, the root-mean-square error was compared between both models.

Results

In males, GAMLSS models were 7% worse to 3% better compared to segmented regression for DLCO and DLNO. In females, GAMLSS models were 2% worse to 5% better compared to segmented linear regression for DLCO and DLNO. The Hyp'Air Compact measured DLNO and alveolar volume (VA) that was approximately 16–20 mL/min/mm Hg and 0.2–0.4 L higher, respectively, compared to the Jaeger MasterScreen Pro. The measured DLCO was similar between devices after controlling for altitude.

Conclusions

For the development of pulmonary function reference equations, we propose that segmented linear regression can be used instead of GAMLSS due to its simplicity, especially when the predictive accuracy is similar between the two models, overall.

Continuous reference intervals for 21 biochemical and hematological analytes in healthy Chinese children and adolescents: the PRINCE study

OBJECTIVES

Critical gaps have existed in pediatric reference intervals in China. In this study, we presented the sex and age distributions of 21 laboratory analytes from childhood to adolescence, and established the corresponding continuous reference intervals based on direct samples.

METHODS

We used the data from the Pediatric Reference Intervals in China (PRINCE), which is a nation-wide cross-sectional study enrolling 15,150 healthy children and adolescents aged 0 - <20 years from 11 centers across China. Blood samples were collected and analyzed by trained staff following standard operating procedures. Biochemical tests were performed with Cobas C702 at the central laboratory, and hematological tests were performed with Sysmex XE, XN, or XS that satisfy the national standards at each participating center. Children younger than 3 months were excluded due to high neonatal variability and insufficient samples. Continuous reference intervals were calculated using the generalized additive models for location, shape, and scale, and were validated among another 387 healthy volunteers.

RESULTS

We provided pediatric continuous reference intervals for 21 commonly used biochemical and hematological analytes in China, and depicted the changes in analyte concentrations from 3 months to 20 years. The out-of-range values for all analytes were less than 10%, indicating a well applicability of the continuous reference intervals to the general pediatric population.

CONCLUSIONS

This is the first comprehensive report of continuous reference intervals based on healthy Chinese children, reflecting the complex dynamic trends of analytes from infancy to adulthood. Applying continuous reference intervals to clinical practice would not only improve the laboratory test result interpretation, but also help better clinical decision making.

Continuous reference curves for common hematology markers in the CALIPER cohort of healthy children and adolescents on the Sysmex XN-3000 system

INTRODUCTION

Clinicians and healthcare professionals rely heavily on health-associated standards, such as reference intervals (RIs), for appropriate laboratory test result interpretation. RIs are commonly partitioned into discrete age/sex bins based on statistical and/or clinical significance. In pediatric hematology, such partitioning does not adequately represent complex variation in analyte concentrations throughout maturation. The objective of this study was to establish continuous RIs for common hematological parameters in the healthy pediatric Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER) cohort.

METHODS

Data from healthy CALIPER children and adolescents (6 months-<19 years) were used to generate continuous RIs (ie, 2.5th and 97.5th quantiles) for 19 hematological parameters. Continuous curves were statistically established with nonparametric quantile regressions. Flagging rate analysis was completed for the established continuous upper and lower reference limits and subsequently compared to previously published discrete CALIPER reference intervals for all parameters.

RESULTS

Continuous RIs were established for 19 hematology parameters, where seven required sex-specific reference curves. Based on flagging rate assessment, continuous RIs appear to more accurately estimate hematological reference limits over the pediatric age range, especially for analytes with complex age- and sex-specific reference value patterns.

CONCLUSIONS

This is the first study to generate continuous RIs for a breadth of hematological markers in a healthy pediatric Canadian population. The increased power of continuous reference intervals to accurately estimate the complex relationship between hematological analyte concentration and age during a time of extensive growth and development is expected to improve laboratory test result interpretation and, subsequently, pediatric clinical decision-making.

Continuous reference intervals for 19 endocrine, fertility, and immunochemical markers in the CALIPER cohort of healthy children and adolescents

BACKGROUND

Reference intervals are traditionally partitioned into discrete ranges by major covariates such as age and sex. However, discrete reference intervals often oversimplify the complex relationship between analyte concentration and age. Continuous reference intervals have been suggested to more accurately represent this complex relationship, particularly in pediatrics. The objective of this study was to establish continuous reference intervals for endocrine, fertility, and additional immunochemical parameters in the CALIPER cohort of healthy children and adolescents.

METHODS

Continuous reference intervals from 1 to 18.5 years of age were established using retrospective CALIPER data collected from healthy Canadian children and adolescents. Continuous reference intervals (2.5th and 97.5th percentiles) were determined for 19 parameters by nonparametric quantile regression. Total and yearly flagging rates were calculated for the upper and lower continuous reference limits and compared to previously published partitioned reference limits.

RESULTS

Continuous reference intervals were established for 19 endocrine, fertility, and additional immunochemical parameters, with 11 requiring sex-specific reference curves. Continuous reference intervals assessed both visually and by flagging rate analysis more accurately represented the relationship between analyte concentration and age, particularly for parameters with complex reference value patterns.

CONCLUSION

This is the first comprehensive report to establish continuous reference intervals for several immunochemical parameters including endocrine and fertility markers in a healthy paediatric Canadian cohort. The ability of continuous reference intervals to provide a better estimate of age-related changes in reference values suggest their potential to improve paediatric laboratory test result interpretation and clinical decision-making.