Mixture density networks for the indirect estimation of reference intervals.

BACKGROUND: Reference intervals represent the expected range of physiological test results in a healthy population and are essential to support medical decision making. Particularly in the context of pediatric reference intervals, where recruitment regulations make prospective studies challenging to conduct, indirect estimation strategies are becoming increasingly important. Established indirect methods enable robust identification of the distribution of "healthy" samples from laboratory databases, which include unlabeled pathologic cases, but are currently severely limited when adjusting for essential patient characteristics such as age. Here, we propose the use of mixture density networks (MDN) to overcome this problem and model all parameters of the mixture distribution in a single step. RESULTS: Estimated reference intervals from varying settings with simulated data demonstrate the ability to accurately estimate latent distributions from unlabeled data using different implementations of MDNs. Comparing the performance with alternative estimation approaches further highlights the importance of modeling the mixture component weights as a function of the input in order to avoid biased estimates for all other parameters and the resulting reference intervals. We also provide a strategy to generate partially customized starting weights to improve proper identification of the latent components. Finally, the application on real-world hemoglobin samples provides results in line with current gold standard approaches, but also suggests further investigations with respect to adequate regularization strategies in order to prevent overfitting the data. CONCLUSIONS: Mixture density networks provide a promising approach capable of extracting the distribution of healthy samples from unlabeled laboratory databases while simultaneously and explicitly estimating all parameters and component weights as non-linear functions of the covariate(s), thereby allowing the estimation of age-dependent reference intervals in a single step. Further studies on model regularization and asymmetric component distributions are warranted to consolidate our findings and expand the scope of applications.

RIbench: A Proposed Benchmark for the Standardized Evaluation of Indirect Methods for Reference Interval Estimation.

BACKGROUND: Indirect methods leverage real-world data for the estimation of reference intervals. These constitute an active field of research, and several methods have been developed recently. So far, no standardized tool for evaluation and comparison of indirect methods exists. METHODS: We provide RIbench, a benchmarking suite for quantitative evaluation of any existing or novel indirect method. The benchmark contains simulated test sets for 10 biomarkers mimicking routine measurements of a mixed distribution of non-pathological (reference) values and pathological values. The non-pathological distributions represent 4 common distribution types: normal, skewed, heavily skewed, and skewed-and-shifted. To identify strengths and weaknesses of indirect methods, test sets have varying sample sizes and pathological distributions differ in location, extent of overlap, and fraction. For performance evaluation, we use an overall benchmark score and sub-scores derived from absolute z-score deviations between estimated and true reference limits. We illustrate the application of RIbench by evaluating and comparing the Hoffmann method and 4 modern indirect methods -TML (Truncated-Maximum-Likelihood), kosmic, TMC (Truncated-Minimum-Chi-Square), and refineR- against one another and against a nonparametric direct method (n = 120). RESULTS: For the modern indirect methods, pathological fraction and sample size had a strong influence on the results: With a pathological fraction up to 20% and a minimum sample size of 5000, most methods achieved results comparable or superior to the direct method. CONCLUSIONS: We present RIbench, an open-source R-package, for the systematic evaluation of existing and novel indirect methods. RIbench can serve as a tool for enhancement of indirect methods, improving the estimation of reference intervals.

Reference Intervals of Serum TSH from Mixed Distributions Using Truncation Points and the Kolmogorov-Smirnov Distance.

BACKGROUND: Serum TSH reference intervals (RIs) are methodology, population, and age specific. However, the ethical and practical challenges restrict the establishment of pediatric RIs using conventional approaches and advocates the use of indirect data mining-based algorithms. This study was carried out to estimate the reference interval of neonatal serum TSH in Pakistani population using an indirect approach. METHODS: A data mining of serum TSH results of neonates (≤ 1 month of age) from 2013 - 2018 was done. Two subgroups on the basis of age from birth to 5 days and 6 - 30 days were assessed. The German study group's pre-validated indirect algorithm 'KOSMIC' was utilized for the statistical analysis. RESULTS: A total of non-duplicate 82,299 neonatal serum TSH tests were retrieved over a period of 6 years, including 88% (n = 70,788) aged 0 - 5 days and 12% (n = 11,511) ranging from 6 days to 1 month. The estimated RIs for the first age partition was 0.7 (90% CI 0.6 - 0.8) to 15.5 (90% CI 12.9 - 16.2) and for the second group 0.7 (90% CI 0.5 - 0.9) to 7.8 (90% CI 6.1 - 9.9) µIU/mL. CONCLUSIONS: This study revealed age related trends in serum TSH. The study advocates the need for population specific RIs owing to the significant variations noted on comparison with previously published literature. Precise RIs become vital particularly when serum TSH is undertaken as a confirmatory test for presumptive positive results on newborn screening for congenital hypothyroidism.

High-resolution pediatric reference intervals for 15 biochemical analytes described using fractional polynomials.

OBJECTIVES: Assessment of children's laboratory test results requires consideration of the extensive changes that occur during physiological development and result in pronounced sex- and age-specific dynamics in many biochemical analytes. Pediatric reference intervals have to account for these dynamics, but ethical and practical challenges limit the availability of appropriate pediatric reference intervals that cover children from birth to adulthood. We have therefore initiated the multi-center data-driven PEDREF project (Next-Generation Pediatric Reference Intervals) to create pediatric reference intervals using data from laboratory information systems. METHODS: We analyzed laboratory test results from 638,683 patients (217,883-982,548 samples per analyte, a median of 603,745 test results per analyte, and 10,298,067 test results in total) performed during patient care in 13 German centers. Test results from children with repeat measurements were discarded, and we estimated the distribution of physiological test results using a validated statistical approach (kosmic). RESULTS: We report continuous pediatric reference intervals and percentile charts for alanine transaminase, aspartate transaminase, lactate dehydrogenase, alkaline phosphatase, γ-glutamyl-transferase, total protein, albumin, creatinine, urea, sodium, potassium, calcium, chloride, anorganic phosphate, and magnesium. Reference intervals are provided as tables and fractional polynomial functions (i.e., mathematical equations) that can be integrated into laboratory information systems. Additionally, Z-scores and percentiles enable the normalization of test results by age and sex to facilitate their interpretation across age groups. CONCLUSIONS: The provided reference intervals and percentile charts enable precise assessment of laboratory test results in children from birth to adulthood. Our findings highlight the pronounced dynamics in many biochemical analytes in neonates, which require particular consideration in reference intervals to support clinical decision making most effectively.

Latent class distributional regression for the estimation of non-linear reference limits from contaminated data sources.

BACKGROUND: Medical decision making based on quantitative test results depends on reliable reference intervals, which represent the range of physiological test results in a healthy population. Current methods for the estimation of reference limits focus either on modelling the age-dependent dynamics of different analytes directly in a prospective setting or the extraction of independent distributions from contaminated data sources, e.g. data with latent heterogeneity due to unlabeled pathologic cases. In this article, we propose a new method to estimate indirect reference limits with non-linear dependencies on covariates from contaminated datasets by combining the framework of mixture models and distributional regression. RESULTS: Simulation results based on mixtures of Gaussian and gamma distributions suggest accurate approximation of the true quantiles that improves with increasing sample size and decreasing overlap between the mixture components. Due to the high flexibility of the framework, initialization of the algorithm requires careful considerations regarding appropriate starting weights. Estimated quantiles from the extracted distribution of healthy hemoglobin concentration in boys and girls provide clinically useful pediatric reference limits similar to solutions obtained using different approaches which require more samples and are computationally more expensive. CONCLUSIONS: Latent class distributional regression models represent the first method to estimate indirect non-linear reference limits from a single model fit, but the general scope of applications can be extended to other scenarios with latent heterogeneity.

Blood counts in adult and elderly individuals: defining the norms over eight decades of life.

The blood count is one of the most common tests used for health assessment. In elderly individuals, selection of a 'healthy' reference population for laboratory assessment is difficult due to the high prevalence of chronic morbidities, leading to uncertainty regarding appropriate reference intervals. In particular, age-specific lower haemoglobin reference limits to define anaemia are controversial. Here, we applied a data mining approach to a large dataset of 3 029 904 clinical routine samples to establish blood count reference intervals. We excluded samples from units/specialists with a high proportion of abnormal blood counts, samples from patients with an unknown or decreased estimated glomerular filtration rate, and samples with abnormal test results in selected other analytes. After sample exclusion, 566 775-572 060 samples from different individuals aged 20-100 years were available for analysis. We then used an established statistical algorithm to determine the distribution of physiological test results and calculated age- and sex-specific reference intervals. Our results show substantial trends with age in haematology analytes' reference intervals. Most notably, haemoglobin and red cell counts decline in men with advanced age, accompanied by increases in red cell volume in both sexes. These findings were confirmed in an independent dataset, and suggest an at least partly physiologic cause.

Indirect determination of hematology reference intervals in adult patients on Beckman Coulter UniCell DxH 800 and Abbott CELL-DYN Sapphire devices.

Background Conventional establishment of reference intervals for hematological analytes is challenging due to the need to recruit healthy persons. Indirect methods address this by deriving reference intervals from clinical laboratory databases which contain large datasets of both physiological and pathological test results. Methods We used the "Reference Limit Estimator" (RLE) to establish reference intervals for common hematology analytes in adults aged 18-60 years. One hundred and ninety-five samples from 44,519 patients, measured on two different devices in a tertiary care center were analyzed. We examined the influence of patient cohorts with an increasing proportion of abnormal test results, compared sample selection strategies, explored inter-device differences, and analyzed the stability of reference intervals in simulated datasets with varying overlap of pathological and physiological test results. Results Reference intervals for hemoglobin, hematocrit, red cell count and platelet count remained stable, even if large numbers of pathological samples were included. Reference intervals for red cell indices, red cell distribution width and leukocyte count were sufficiently stable, if patient cohorts with the highest fraction of pathological samples were excluded. In simulated datasets, estimated reference limits shifted, if the pathological dataset contributed more than 15%-20% of total samples and approximated the physiological distribution. Advanced sample selection techniques did not improve the algorithm's performance. Inter-device differences were small except for red cell distribution width. Conclusions The RLE is well-suited to create reference intervals from clinical laboratory databases even in the challenging setting of a adult tertiary care center. The procedure can be used as a complement for reference interval determination where conventional approaches are limited.

Next-generation reference intervals for pediatric hematology.

Background Interpreting hematology analytes in children is challenging due to the extensive changes in hematopoiesis that accompany physiological development and lead to pronounced sex- and age-specific dynamics. Continuous percentile charts from birth to adulthood allow accurate consideration of these dynamics. However, the ethical and practical challenges unique to pediatric reference intervals have restricted the creation of such percentile charts, and limitations in current approaches to laboratory test result displays restrict their use when guiding clinical decisions. Methods We employed an improved data-driven approach to create percentile charts from laboratory data collected during patient care in 10 German centers (9,576,910 samples from 358,292 patients, 412,905-1,278,987 samples per analyte). We demonstrate visualization of hematology test results using percentile charts and z-scores (www.pedref.org/hematology) and assess the potential of percentiles and z-scores to support diagnosis of different hematological diseases. Results We created percentile charts for hemoglobin, hematocrit, red cell indices, red cell count, red cell distribution width, white cell count and platelet count in girls and boys from birth to 18 years of age. Comparison of pediatricians evaluating complex clinical scenarios using percentile charts versus conventional/tabular representations shows that percentile charts can enhance physician assessment in selected example cases. Age-specific percentiles and z-scores, compared with absolute test results, improve the identification of children with blood count abnormalities and the discrimination between different hematological diseases. Conclusions The provided reference intervals enable precise assessment of pediatric hematology test results. Representation of test results using percentiles and z-scores facilitates their interpretation and demonstrates the potential of digital approaches to improve clinical decision-making.

A Comparison of GFR Estimation Formulae in Pediatric Oncology.

BACKGROUND: Application of potentially nephrotoxic chemotherapy requires continuous monitoring of renal function for toxicity and dosing. Novel pediatric glomerular filtration rate (GFR) estimating equations including cystatin C have been proposed to enhance the reliability of GFR calculation. MATERIALS AND METHODS: We examined a pediatric oncologic data set with a total of 363 GFR measurements. An analysis of distribution characteristics and comparison of medians was performed to compare creatinine and cystatin C-based GFR estimating formulae. Furthermore, we investigated the clinical impact of different equations in regard to therapeutic consequences. RESULTS: Significant differences in estimated GFR values were calculated depending on the applied formula (range of median GFR from 94.8 to 180.9 mL/min per 1.73 m2) which may result in different therapeutic consequences for the use of potentially nephrotoxic chemotherapeutic agents. Significant correlation for all examined formulae was identified, however there were large fluctuations among the correlation coefficients ranging from 0.254 to 1.0. CONCLUSION: This study compares proposed pediatric GFR estimating equations in a clinical setting. It underlines the current limitations and difficulties of GFR estimation including potential dosing errors. Cystitis C-based equations can be used as alternatives to creatinine-based estimations when the appropriate laboratory method has been applied. A comparative calculator for pediatric GFR estimating equations along with background information is provided at http://gfr.pedz.de and may support clinical decision-making.

Critical comments to a recent EFLM recommendation for the review of reference intervals.

In a recent EFLM recommendation on reference intervals by Henny et al., the direct approach for determining reference intervals was proposed as the only presently accepted "gold" standard. Some essential drawbacks of the direct approach were not sufficiently emphasized, such as unacceptably wide confidence limits due to the limited number of observations claimed and the practical usability for only a limited age range. Indirect procedures avoid these disadvantages of the direct approach. Furthermore, indirect approaches are well suited for reference limits with large variations during lifetime and for common reference limits.

Pediatric reference intervals for alkaline phosphatase.

BACKGROUND: Interpretation of alkaline phosphatase activity in children is challenging due to extensive changes with growth and puberty leading to distinct sex- and age-specific dynamics. Continuous percentile charts from birth to adulthood allow accurate consideration of these dynamics and seem reasonable for an analyte as closely linked to growth as alkaline phosphatase. However, the ethical and practical challenges unique to pediatric reference intervals have restricted the creation of such percentile charts, resulting in limitations when clinical decisions are based on alkaline phosphatase activity. METHODS: We applied an indirect method to generate percentile charts for alkaline phosphatase activity using clinical laboratory data collected during the clinical care of patients. A total of 361,405 samples from 124,440 patients from six German tertiary care centers and one German laboratory service provider measured between January 2004 and June 2015 were analyzed. Measurement of alkaline phosphatase activity was performed on Roche Cobas analyzers using the IFCC's photometric method. RESULTS: We created percentile charts for alkaline phosphatase activity in girls and boys from birth to 18 years which can be used as reference intervals. Additionally, data tables of age- and sex-specific percentile values allow the incorporation of these results into laboratory information systems. CONCLUSIONS: The percentile charts provided enable the appropriate differential diagnosis of changes in alkaline phosphatase activity due to disease and changes due to physiological development. After local validation, integration of the provided percentile charts into result reporting facilitates precise assessment of alkaline phosphatase dynamics in pediatrics.

Age- and sex-specific dynamics in 22 hematologic and biochemical analytes from birth to adolescence.

BACKGROUND: Pediatric laboratory test results must be interpreted in the context of interindividual variation and age- and sex-dependent dynamics. Reference intervals as presently defined for separate age groups can only approximate the age-related dynamics encountered in pediatrics. Continuous reference intervals from birth to adulthood are not available for most laboratory analytes because of the ethical and practical constraints of defining reference intervals using a population of healthy community children. We applied an indirect method to generate continuous reference intervals for 22 hematologic and biochemical analytes by analyzing clinical laboratory data from blood samples taken during clinical care of patients. METHODS: We included samples from 32 000 different inpatients and outpatients (167 000 samples per analyte) from a German pediatric tertiary care center. Measurements were performed on a Sysmex-XE 2100 and a Cobas Integra 800 during clinical care over a 6-year period. The distribution of samples considered normal was estimated with an established indirect statistical approach and used for the calculation of reference intervals. RESULTS: We provide continuous reference intervals from birth to adulthood for 9 hematology analytes (hemoglobin, hematocrit, red cell indices, red cell count, red cell distribution width, white cell count, and platelet count) and 13 biochemical analytes (sodium, chloride, potassium, calcium, magnesium, phosphate, creatinine, aspartate transaminase, alanine transaminase, γ-glutamyltransferase, alkaline phosphatase, lactate dehydrogenase, and total protein). CONCLUSIONS: Continuous reference intervals capture the population changes in laboratory analytes during pediatric development more accurately than age groups. After local validation, the reference intervals provided should allow a more precise consideration of these dynamics in clinical decision making.

Indirect determination of pediatric blood count reference intervals.

BACKGROUND: Determination of pediatric reference intervals (RIs) for laboratory quantities, including hematological quantities, is complex. The measured quantities vary by age, and obtaining samples from healthy children is difficult. Many widely used RIs are derived from small sample numbers and are split into arbitrary discrete age intervals. Use of intra-laboratory RIs specific to the examined population and analytical device used is not yet fully established. Indirect methods address these issues by deriving RIs from clinical laboratory databases which contain large datasets of both healthy and pathological samples. METHODS: A refined indirect approach was used to create continuous age-dependent RIs for blood count quantities and sodium from birth to adulthood. The dataset for each quantity consisted of 60,000 individual samples from our clinical laboratory. Patient samples were separated according to age, and a density function of the proportion of healthy samples was estimated for each age group. The resulting RIs were merged to obtain continuous RIs from birth to adulthood. RESULTS: The obtained RIs were compared to RIs generated by identical laboratory instruments, and to population-specific RIs created using conventional methods. This comparison showed a high concordance of reference limits and their age-dependent dynamics. CONCLUSIONS: The indirect approach reported here is well-suited to create continuous, intra-laboratory RIs from clinical laboratory databases and showed that the RIs generated are comparable to those created using established methods. The procedure can be transferred to other laboratory quantities and can be used as an alternative method for RI determination where conventional approaches are limited.

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.

Temporal evolution and differential patterns of cellular reconstitution after therapy for childhood cancers.

The cellular reconstitution after childhood cancer therapy is associated with the risk of infection and efficacy of revaccination. Many studies have described the reconstitution after stem cell transplantation (SCT). The recovery after cancer treatment in children who have not undergone SCT has mainly been investigated in acute lymphoblastic leukemia (ALL), less for solid tumors. Here, we have examined the temporal evolution of total leukocyte, neutrophil and lymphocyte counts as surrogate parameters for the post-therapeutic immune recovery in a cohort of n = 52 patients with ALL in comparison to n = 58 patients with Hodgkin's disease (HD) and n = 22 patients with Ewing sarcoma (ES). Patients with ALL showed an efficient increase in blood counts reaching the age-adjusted lower limits of normal between 4 and 5 months after the end of maintenance therapy. The two groups of patients with HD and ES exhibited a comparably delayed recovery of total leukocytes due to a protracted post-therapeutic lymphopenia which was most pronounced in patients with HD after irradiation. Overall, we observed a clearly more efficient resurgence of total lymphocyte counts in patients aged below 12 years compared to patients aged 12 to 18 years. Our results underline that the kinetics of cellular reconstitution after therapy for HD and ES differ significantly from ALL and depend on treatment regimens and modalities as well as on patient age. This suggests a need for disease, treatment, and age specific recommendations concerning the duration of infection prophylaxis and the timing of revaccination.

Pharmacokinetic-pharmacodynamic modeling of maintenance therapy for childhood acute lymphoblastic leukemia.

In the treatment of childhood acute lymphoblastic leukemia (ALL), current protocols combine initial high-dose multiagent chemotherapy with prolonged oral therapy with 6-mercaptopurine (6MP) and low-dose methotrexate (MTX) maintenance therapy. Decades of research on ALL treatment have resulted in survival rates of approximately 90%. However, dose-response relationships vary widely between patients and insight into the influencing factors, that would allow for improved personalized treatment management, is insufficient. We use a detailed data set with measurements of thioguanine nucleotides and MTX in red blood cells and absolute neutrophil count (ANC) to develop pharmacokinetic models for 6MP and MTX, as well as a pharmacokinetic-pharmacodynamic (PKPD) model capable of predicting individual ANC levels and thus contributing to the development of personalized treatment strategies. Here, we show that integrating metabolite measurements in red blood cells into the full PKPD model improves results when less data is available, but that model predictions are comparable to those of a fixed pharmacokinetic model when data availability is not limited, providing further evidence of the quality of existing models. With this comprehensive model development leading to dynamics similar to simpler models, we validate the suitability of this model structure and provide a foundation for further exploration of maintenance therapy strategies through simulation and optimization.

Age- and sex-specific pediatric reference intervals for neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, and platelet-to-lymphocyte ratio.

INTRODUCTION: Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) are emerging biomarkers for systemic inflammation and have been shown to predict morbidity and mortality for several diseases. However, lack of pediatric reference intervals (RIs) prevents their comprehensive use in patient care and medical research. MATERIAL AND METHODS: We calculated reference intervals and corresponding confidence intervals for NLR, PLR, and LMR from birth to 18 years using a data-mining approach: We analyzed 232 746 blood counts from 60 685 patients performed during patient care and excluded patients with elevated C-reactive protein and procalcitonin. Test results were separated according to age and sex, and the distribution of physiological ratios was estimated using an indirect approach (refineR). Additionally, we investigated the ratios' diagnostic benefit for different inflammatory diseases (acute appendicitis, asthma, Bell's palsy, Henoch-Schonlein purpura, and cystic fibrosis) using the newly obtained reference intervals. RESULTS: We estimated age- and sex-specific reference intervals from birth to adulthood for NLR, PLR, and LMR. Analyses in pediatric inflammatory diseases showed that PLR and LMR were poor markers to detect the examined inflammatory diseases, while NLR was significantly increased in patients with appendicitis and asthma. CONCLUSION: We provide pediatric reference intervals for NLR, PLR, and LMR to improve the interpretation of these biomarkers in children.

Differences between capillary and venous blood counts in children-A data mining approach.

BACKGROUND: Capillary sampling of blood counts is a well-established alternative to venipuncture in paediatrics. However, the sampling method has to be considered when interpreting test results, as measurements differ. Ethical and practical considerations prevent simultaneous venous and capillary sample acquisition in comprehensive paediatric cohorts that span all ages for the purpose of a direct method comparison, resulting in uncertainty regarding the interpretation of capillary test results. METHODS: We applied a data mining method to calculate the differences between capillary and venous blood count analytes using laboratory data collected during patient care. We examined 486 401 blood counts performed between 2010 and 2017 in two German paediatric tertiary care centers in children from birth to 18 years analysed on SYSMEX XE-2100 and SYSMEX XE-5000 devices, and analysed the differences between capillary and venous test results in 15 218 paired samples performed within 24 h. RESULTS: We identified the mean systematic differences between capillary and venous (capillary-venous) test results for haemoglobin (+6.5 g/L), haematocrit (+2.38%), platelet count (-7.01 × 109 /l), red cell count (+0.18 × 1012 /L), white cell count (-0.64 × 109 /L), mean corpuscular cell volume (+2.07 fl), mean corpuscular haemoglobin (+0.33 pg), mean corpuscular haemoglobin concentration (-4.4 g/L) and red cell distribution width (+0.40%). The effect of age on these mean deltas is negligible, while the levels of test results influence the difference between capillary and venous test results in most analytes. CONCLUSIONS: Our results improve guidance regarding the interpretation of capillary test results for children of all ages and in both physiological and pathological ranges.

Indirect determination of serum creatinine reference intervals in a Pakistani pediatric population using big data analytics.

BACKGROUND: The indirect methods of reference intervals (RI) establishment based on data mining are utilized to overcome the ethical, practical challenges and the cost associated with the conventional direct approach. AIM: To generate RIs for serum creatinine in children and adolescents using an indirect statistical tool. METHODS: Data mining of the laboratory information system was performed for serum creatinine analyzed from birth to 17 years for both genders. The timeline was set at six years from January 2013 to December 2018. Microsoft Excel 2010 and an indirect algorithm developed by the German Society of Clinical Chemistry and Laboratory Medicine's Working Group on Guide Limits were used for the data analysis. RESULTS: Data were extracted from 96104 samples and after excluding multiple samples for the same individual, we calculated RIs for 21920 males and 14846 females, with stratification into six discrete age groups. CONCLUSION: Serum creatinine dynamics varied significantly across gender and age groups.