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

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.

Complete Blood Count Reference Intervals for Children Aged Less Than 1 to 12 Years in the Northern Region of Ghana

Reliable laboratory diagnostic results are key for evaluating and improving children's health. To interpret these results, child-specific reference intervals (RIs), which account for constant biological changes and physiological development with sex and age, are required, as recommended by the Clinical and Laboratory Standards Institute (CLSI). This study presents age- and sex-specific reference intervals for complete blood count (CBC) parameters in children (<1-12 years old) in the Northern Region of Ghana. In this cross-sectional study, 600 healthy children from randomly sampled schools in Tamale (the Northern Region) were recruited and screened. Data from 388 eligible children were used to nonparametrically determine the reference intervals of CBC parameters at the 2.5th and 97.5th percentiles. The CBC reference intervals were compared for variations in sex and age groups using the Wilcoxon rank-sum test. There were no statistically significant differences in most CBC parameters by sex (RBC, Hb, HCT, MCH, RDW (CV/SD), WBC, LYM#, MON#(%) NEU#(%), EOS#(%), and BAS#(%); p > 0.05) and age group (RBC, MCV, RDW (CV/SD), WBC, LYM#, MON#(%) NEU#(%), EOS#(%), and BAS%; p > 0.05). However, there were observable differences between this locally established CBC reference interval and that used for children at Tamale Teaching Hospital (manufacturer's RIs). This study emphasises the importance of determining reference intervals representative of the local child population and incorporating them into the current reporting system of laboratories in the Northern Region to ensure the provision of effective and efficient healthcare services.

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.

Establishing pregnancy-specific haematological reference intervals in Ghana; a three-center cross-sectional study

BACKGROUND

Abnormal intra-pregnancy haematological variables are associated with adverse feto-maternal outcomes. However, the reference intervals (RIs) employed in sub-Saharan Africa to inform clinical decisions are generally imported. Since RIs are influenced by age, geographical location, and race, we hypothesized that context specific RIs should be established in Ghana to contextualize intra-pregnancy decision making.

METHODS

This cross-sectional study retrospectively retrieved data of 333 pregnant women with no known clinically determined intra-pregnancy complications; 22 participants in their first trimester (T1; 1-13 weeks), 177 in their T2 (14-27 weeks), and 132 in T3 (28-41 weeks). RIs for haematological parameters were non-parametrically determined at 2.5th and 97.5th percentiles in accordance with CLSI guidance document EP28-A3c. Two-sample comparisons were undertaken using Wilcoxon rank-sum tests whereas more than two-sample comparisons were undertaken using Kruskal-Wallis test. Statistical significance was set at p <0.05 under the two-tailed assumptions.

RESULTS

In accordance with WHO trimester-specific haemoglobin cutoffs, anaemia prevalence was a moderate (T1: 36.4%; 8/22 & T2: 31.6%; 56/177) to severe (T3:68.0%; 90/132) public health problem. Additionally, 9.3% (31/333) individuals had high gestational haemoglobin levels (Hb >13.0 g/dL). Moreover, haemoglobin (T2: 8.6-14.3 vs T3: 7.5-13.6 g/dL), MCH (T2: 22.5-69.8 vs T3: 21.6-31.9 pg), MCHC (T2: 30.2-51.8 g/L vs T3: 30.5-37.9 g/L), TWBC (T2: 4.0-13.4 vs T3: 4.1-13.0 x 109/L) required trimester specific RIs, compared to RBC (2.8-5.1 x 1012/L), MCV (66.2-100.2 fL), and platelet counts (106.3-388.3 x 109/L) that each required combined reference intervals.

CONCLUSIONS

The intra-pregnancy haematological RIs determined have appreciable lower limits; there is the need to determine context-specific thresholds for haematological variables predictive of positive and/or adverse maternal and infant health outcomes.

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.

Age- and sex-specific reference intervals for complete blood count parameters in capillary blood for Chinese neonates and infants: A prospective study

BACKGROUND

The reference intervals (RIs) of laboratory tests are essential for disease diagnosis, therapy monitoring, and health assessment. They are also significant for clinicians to discriminate between subjects with disease and healthy subjects. However, RIs for complete blood count (CBC) parameters in capillary blood for children are deficient. This study aimed to establish capillary blood RIs for blood cell parameters in neonates and infants from birth to 2 years of age in Zhengzhou.

METHODS

We prospectively collected a total of 1840 capillary blood specimens from healthy subjects from birth to 2 years of age. Hematology RIs were established by analyzing capillary blood sample data, and RIs and 90 % confidence intervals (CIs) were calculated according to Clinical and Laboratory Standards Institute (CLSI) C28-A3 guidelines.

RESULTS

RIs were established for hematological parameters of capillary blood in neonates and infants from birth to 2 years of age. The levels of almost all hematological parameters, except for the lymphocyte (LYMPH), platelet (PLT), and thrombocytocrit (PCT) parameters, peaked in the first month after birth and then decreased to lower levels within 6 months. There were significant sex differences in most erythrocyte-related parameters, with higher levels in males than in females. Erythrocyte-related parameters showed an increasing tendency with increasing age after the second month. Neutrophil (NEUT) levels were high on the third day of life, declined to a nadir in the first month, and then slowly increased with age. LYMPH levels were low at birth and began to increase after birth, peaked at approximately-six months of age and then gradually declined with age. PLT and PCT levels showed an increasing trend during the first month, while the other parameters showed a decreasing trend. All platelet-related and leukocyte-related parameters showed no significant difference with sex.

CONCLUSION

We provide comprehensive age- and sex-specific RIs, including RIs for neonates in Henan. Our study provides more comprehensive reference ranges for Child Health Hospital and children's medical institutions, which may facilitate preliminary screening, diagnosis, and therapy.