Nationwide Chinese study for establishing reference intervals for thyroid hormones and related tests

Utilization of five data mining algorithms combined with simplified preprocessing to establish reference intervals of thyroid-related hormones for non-elderly adults

BACKGROUND

Despite the extensive research on data mining algorithms, there is still a lack of a standard protocol to evaluate the performance of the existing algorithms. Therefore, the study aims to provide a novel procedure that combines data mining algorithms and simplified preprocessing to establish reference intervals (RIs), with the performance of five algorithms assessed objectively as well.

METHODS

Two data sets were derived from the population undergoing a physical examination. Hoffmann, Bhattacharya, Expectation Maximum (EM), kosmic, and refineR algorithms combined with two-step data preprocessing respectively were implemented in the Test data set to establish RIs for thyroid-related hormones. Algorithm-calculated RIs were compared with the standard RIs calculated from the Reference data set in which reference individuals were selected following strict inclusion and exclusion criteria. Objective assessment of the methods is implemented by the bias ratio (BR) matrix.

RESULTS

RIs of thyroid-related hormones are established. There is a high consistency between TSH RIs established by the EM algorithm and the standard TSH RIs (BR = 0.063), although EM algorithms seems to perform poor on other hormones. RIs calculated by Hoffmann, Bhattacharya, and refineR methods for free and total triiodo-thyronine, free and total thyroxine respectively are close and match the standard RIs.

CONCLUSION

An effective approach for objectively evaluating the performance of the algorithm based on the BR matrix is established. EM algorithm combined with simplified preprocessing can handle data with significant skewness, but its performance is limited in other scenarios. The other four algorithms perform well for data with Gaussian or near-Gaussian distribution. Using the appropriate algorithm based on the data distribution characteristics is recommended.

Free thyroxine measurement in clinical practice: how to optimize indications, analytical procedures, and interpretation criteria while waiting for global standardization

Thyroid dysfunctions are among the most common endocrine disorders and accurate biochemical testing is needed to confirm or rule out a diagnosis. Notably, true hyperthyroidism and hypothyroidism in the setting of a normal thyroid-stimulating hormone level are highly unlikely, making the assessment of free thyroxine (FT4) inappropriate in most new cases. However, FT4 measurement is integral in both the diagnosis and management of relevant central dysfunctions (central hypothyroidism and central hyperthyroidism) as well as for monitoring therapy in hyperthyroid patients treated with anti-thyroid drugs or radioiodine. In such settings, accurate FT4 quantification is required. Global standardization will improve the comparability of the results across laboratories and allow the development of common clinical decision limits in evidence-based guidelines. The International Federation of Clinical Chemistry and Laboratory Medicine Committee for Standardization of Thyroid Function Tests has undertaken FT4 immunoassay method comparison and recalibration studies and developed a reference measurement procedure that is currently being validated. However, technical and implementation challenges, including the establishment of different clinical decision limits for distinct patient groups, still remain. Accordingly, different assays and reference values cannot be interchanged. Two-way communication between the laboratory and clinical specialists is pivotal to properly select a reliable FT4 assay, establish reference intervals, investigate discordant results, and monitor the analytical and clinical performance of the method over time.

The reference intervals for thyroid hormones: A four year investigation in Chinese population

Introduction

The reference intervals (RIs) are of great importance for physicans to determine whether or not an individual is healthy. However, many clinical laboratories in China still adopted the default RI provided by the manufacturers; and these "uncalibrated" RIs might lead to the misdiagnosis of diseases. In the present study, we enroll reference people with the purpose of determining the RIs of serum triiodothyronine (T3), thyroxine (T4), free triiodothyronine (FT3), free thyroxine (FT4) and thyroid-stimulating hormone (TSH) in Chinese population, and explore the possible roles of age and sex on the levels of biomarkers.

Methods

Serum samples from 66,609 individuals who met the inclusion criteria were analyzed using an Roche Cobas E 601 hormone analyzer. The dynamic trends of biomarker were visually assessed by their concentrations over age and sex. Specific partitions were determined by the method of Harris and Boyd. RIs, corresponding to the 2.5th and 97.5th percentiles, as well as the 0.5th, 25th, 50th, 75th and 99.5th percentiles were calculated for each reference partition using a non-parametric rank approach.

Results

The serum level of T3, T4, FT4 or TSH showed a right-skewed distribution in both males and females while FT3 presented an approximate normal distribution. Females had a higher mode value of serum T3 or T4, but a lower mode value of serum TSH, FT3 or FT4. All five biomarkers did not need age partitioning according to the approach of harris and boyd, while T3 and FT3 need sex partitioning.

Conclusions

The present study not only determined the age- and sex-specific trends of the five thyroid hormones, but provided sex-stratified RIs for T3 and FT3, valuably contributing to the current literature and timely evaluation of thyroid health and disease.

Reference intervals for thyroid-stimulating hormone, free thyroxine, free triiodothyronine, and total triiodothyronine in the Lebanese adult population

BACKGROUND

For a better assessment of thyroid function, each laboratory should establish its own reference intervals (RI). In Lebanon, no previous study has been conducted to establish the reference values for thyroid function tests.

METHODS

This cross-sectional study included 301 volunteers aged between 18 and 65 years (65.8% women, 34.2% men), free from any thyroid pathology and any condition that could affect thyroid function tests. The reference intervals of thyroid-stimulating hormone (TSH), free T4 (FT4), free T3 (FT3), and total T3 (TT3) were measured on the Roche Cobas e411 machine. 39 subjects tested positive for thyroid peroxidase antibodies (TPOAb) and/or thyroglobulin antibodies (TGAb), were excluded from the study.

RESULTS

There was an increase in the 2.5^th percentile for the TSH compared to the value provided by the manufacturer (from 0.27 to 0.53 mlU/L) as well as a decrease in the 97.5^th percentile for the FT4, TT3, and FT3 (respectively, from 22 to 19.78 pmol/L for FT4, from 3.1 to 2.71 nmol/L for TT3, and from 6.80 to 6.10 pmol/L for FT3). Higher TT3 and FT3 values were noted in men compared to women (respectively, p = 0.068 and p < 0.0001). An age decrease in FT4 and FT3 was also observed (respectively, p = 0.045 and p < 0.0001).

CONCLUSION

The established RI of thyroid function tests for the Lebanese population were significantly different from the values recommended by the manufacturer (Roche Diagnostics). Changing our RI values will allow a more accurate diagnosis of thyroid dysfunction.

Age- and sex-specific reference intervals for thyroid hormones in a Chinese pediatrics: a prospective observational study of 1,279 healthy children

BACKGROUND

Thyroid hormones are essential for early neurocognitive development and growth and development in childhood and adolescence. However, the reference intervals (RIs) for thyroid hormones in Chinese pediatric individuals remain unclear. This study aimed to establish thyroid hormone RIs for a Chinese pediatric population according to appropriate age- and sex-specific partitioning.

METHODS

In this prospective observational study, a total of 1,279 healthy children (singletons, aged from 1 day to 12 years) were recruited, and serum samples were analyzed on a Mindray automated chemiluminescence immunoassay analyzer CL-6000i for thyroid hormone detection, including thyroid-stimulating hormone (TSH), free triiodothyronine (FT3), free thyroxine (FT4), total triiodothyronine (T3), and total thyroxine (T4). Age and sex-specific RIs were established, and the corresponding 95% confidence intervals (CIs) were calculated in accordance with the Clinical Laboratory Standards Institute (CLSI) document C28-A3 guidelines.

RESULTS

Quantile testing revealed that the median (P50) and RIs [2.5^th percentile (P2.5)-97.5^th percentile (P97.5)] for TSH, FT3, T3, and T4 of males differed significantly from those of females (P<0.05), except for FT4 (P=0.483). For FT3 and T3, the RIs of males were higher than that of females, and the RI of T4 for males was narrower and higher than that of females [P2.5-P97.5: 72.33-171.60 vs. 72.31-176.27 nmol/L; P50: 116.75 vs. 113.47 nmol/L, P=0.011]. RIs for TSH, FT3, FT4, T3, and T4 showed sex- and age-specific properties and displayed a wide variation during the first month of life but gradually narrowed and concentrated with increasing age. In addition, RIs of TSH, FT3, FT4, and T3 in males differed significantly from females in the first month of life (TSH: 1.46-10.87 vs. 1.08-11.35 mIU/L; FT3: 2.96-7.08 vs. 2.35-7.27 pmol/L, FT4: 13.34-28.65 vs. 13.82-31.83 pmol/L; T3: 0.83-2.33 vs. 0.72-2.46 nmol/L). The RI of T4 also exhibited a difference between males and females in the 9- to 12-year age group (59.31-150.72 vs. 63.29-146.94 pmol/L for males and females, respectively).

CONCLUSIONS

Pediatric RIs of thyroid hormones display age- and sex-specific trends. The RIs established in this study will improve the accuracy of TSH assay result interpretations and clinical decision-making in clinical laboratories that utilize the Mindray analytical platform.

Sources of variation and establishment of Russian reference intervals for major hormones and tumor markers

OBJECTIVES

A multicenter study was organized to explore sources of variation (SVs) of reference values (RVs) for 22 major immunochemistry analytes and to determine reference intervals (RIs) for the Russian population.

METHODS

According to IFCC Committee on Reference Intervals and Decision Limits (C-RIDL) protocol, 758 healthy volunteers were recruited in St. Petersburg, Moscow, and Yekaterinburg. Serum samples were tested for five tumor markers, 17 hormones and related tests by Beckman Coulter's UniCel DxI 800 immunochemistry analyzer. SVs were explored using multiple regression analysis and ANOVA. Standard deviation ratio (SDR) of 0.4 was used as primary guide for partitioning RIs by gender and age.

RESULTS

SDR for between-city difference was <0.4 for all analytes. Secondary exclusion of individuals was done under the following conditions: for female sex-hormones, those with contraceptives (8%); for CA19-9, those supposed to have negative Lewis blood-group (10.5% males and 11.3% females); for insulin, those with BMI≥28 kg/m2 (31%); for the thyroid panel, those with anti-thyroid antibodies (10.3% males; 24.5% females), for CEA those with smoking habit (30% males and 16% females). Gender-specific RIs were required for all analytes except CA19-9, CA15-3, thyroid-related tests, parathyroid hormone, and insulin. Age-specific RIs were required for alpha-fetoprotein, CEA, all sex-hormones for females, FSH and progesterone for both sexes. RIs were generally derived by parametric method after Gaussian transformation using modified Box-Cox formula. Exceptions were growth hormone, estradiol for females in postmenopause, and progesterone for females in premenopause, for which nonparametric method was required due to bimodal distribution and/or insufficient detection limit.

CONCLUSION

RIs for major hormones and tumor markers specific for the Russian population were derived based on the up-to-date internationally harmonized protocol by careful consideration of analyte-specific SVs.

Establishment of variation source and age-related reference interval models for 22 common biochemical analytes in older people using real-world big data mining

BACKGROUND

the ageing population has increased in many countries, including China. However, reference intervals (RIs) for older people are rarely established because of difficulties in selecting reference individuals. Here, we aimed to analyse the factors affecting biochemical analytes and establish RI and age-related RI models for biochemical analytes through mining real-world big data.

METHODS

data for 97,220 individuals downloaded from electronic health records were included. Three derived databases were established. The first database included 97,220 individuals and was used to build age-related RI models after identifying outliers by the Tukey method. The second database consisted of older people and was used to establish variation source models and RIs for biochemical analytes. Differences between older and younger people were compared using the third database.

RESULTS

sex was the main source of variation of biochemical analytes for older people in the variation source models. The distributions of creatinine and uric acid were significantly different in the RIs of biochemical analytes for older people established according to sex. Age-related RI models for biochemical analytes that were most affected by age were built and visualized, revealing various patterns of changes from the younger to older people.

CONCLUSION

the study analysed the factors affecting biochemical analytes in older people. Moreover, RI and age-related RI models of biochemical analytes for older people were established to provide important insight into biological processes and to assist clinical use of various biochemical analytes to monitor the status of various diseases for older people.

Gender and age-specific reference intervals of common biochemical analytes in Chinese population: Derivation using real laboratory data

BACKGROUND

Indirect sampling methods are not only inexpensive but also efficient for establishing reference intervals (RIs) using clinical data. This study was conducted to select fully normal records to establish ageand gender-specific RIs for common biochemical analytes by laboratory data mining.

METHODS

In total, 280,206 records from 2014 to 2018 were obtained from Peking Union Medical College Hospital. Common biochemical analytes total protein, albumin, total bilirubin (TBil), direct bilirubin (DBil), alanine aminotransferase (ALT), glutamyltranspeptidase (GGT), alkaline phosphatase (ALP), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), potassium, sodium, chlorine, calcium, urea, glucose, uric acid (UA), inorganic phosphorus, creatinine (Cr), total cholesterol, triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol] were measured using an automatic analyzer. Sources of variation were identified by multiple regression analysis. The 2.5th and 97.5th percentiles were calculated as the lower and upper limits of the RIs, respectively.

RESULTS

Gender was the major source of variation among the 13 common biochemical analytes with an rp > 0.15. In contrast to the value listed in the WS/T 404, nearly all RIs established in this study were significantly narrower. Furthermore, age-specific RIs should be determined for DBil, LDH, and urea, whereas gender-specific RIs are suggested for GGT, LDH, and urea.

CONCLUSIONS

We recommend that gender-specific RIs should be established for ALT, AST, GGT, DBil, TBil, UA, and Cr as well as genderand age-specific RIs for urea and ALP. Through indirect sampling, ageand gender-specific RIs for common biochemical analytes were established and analyzed.