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BACKGROUND: Measuring sex hormones is essential in diagnosing health issues such as testicular dysfunction, male infertility and feminization syndrome. However, there are no reports on reference intervals (RIs) in Chinese men. We conducted a nationwide multicenter study to establish RIs for seven sex hormones (luteinizing hormone [LH], follicle-stimulating hormone [FSH], prolactin [PRL], total testosterone [TT], free testosterone [FT], bioavailable testosterone [BAT] and estrogen [E2]), as well as sex hormone-binding globulin (SHBG). METHODS: In 2013, 1043 apparently healthy adult men from five representative cities in China (Beijing, Hangzhou, Guangzhou, Dalian and Urumqi) were recruited; hormones were measured using an automated immunoassay analyzer. Multiple regression analysis (MRA) was performed to identify sources of variation (SVs) that might influence the hormone serum levels. RIs were computed using the parametric method. RESULTS: Dalian and Hangzhou had significantly higher E2 values than other cities; age was a major source of variation for FSH, LH, PRL, SHBG, FT and BAT. FSH, LH and SHBG increased significantly with age, while PRL, FT and BAT decreased with age. TT showed no significant age-related changes. Median (RIs) derived without partition by age were as follows: FSH, 5.6 (1.9-16.3) IU/L; LH, 4.2 (1.6-10.0) IU/L; PRL, 189 (88-450) mIU/L; E2, 85 (4.7-195) pmol/L; SHBG, 29.4 (11.5-66.3) nmol/L; TT, 15.6 (7.4-24.5) nmol/L; FT, 0.31 (0.16-0.52) nmol/L; and BAT, 8.0 (3.7-13.2) nmol/L. RIs were also derived in accordance with between-city and between-age differences. CONCLUSIONS: RIs were established for sex hormones and SHBG in apparently healthy Chinese men in consideration of age.

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BACKGROUND: Reference intervals (RIs) play key roles in clinical diagnosis, treatment and prognosis. However, RIs for clinical testing tend to be confined to the general population, and RIs for pregnant women are not very comprehensive. In this study, we establish RIs for prolactin (PRL) in healthy pregnant and postpartum women in the Chinese population. METHODS: Healthy pregnant women (n=378) were divided into groups according to whether they were in the first, second or third trimester of pregnancy. Healthy postpartum women (n=493) were separated into four groups according to mode of delivery as follows: postvaginal (24 and 48 h) or postcesarean (24 and 48 h). Healthy, non-pregnant women (n=123) were enrolled as a control group. Serum PRL levels were measured by electrochemiluminescence immunoassay, and RIs were established for each group. RESULTS: The RIs for PRL were as follows: healthy non-pregnant women, 178.89-757.52 µIU/mL; first trimester, 621.20-3584.00 µIU/mL; second trimester, 1432.00-5349.68 µIU/mL; third trimester, 4087.33-9733.65 µIU/mL; 24 and 48 h postvaginal delivery (combined), 7865.36-10998.86 µIU/mL; and 24 and 48 h postcesarean delivery, 4556.41-7675.99 and 6578.45-9980.45 µIU/mL, respectively. CONCLUSIONS: PRL RIs for pregnant women were established according to trimester, days postpartum and mode of delivery, thus providing a clinical reference for medical staff.

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BACKGROUND: Hyperprolactinemia diagnosis and treatment is often compromised by the presence of biologically inactive and clinically irrelevant higher-molecular-weight complexes of prolactin, macroprolactin. The objective of this study was to evaluate the performance of two macroprolactin screening regimes across commonly used automated immunoassay platforms. METHODS: Parametric total and monomeric gender-specific reference intervals were determined for six immunoassay methods using female (n=96) and male sera (n=127) from healthy donors. The reference intervals were validated using 27 hyperprolactinemic and macroprolactinemic sera, whose presence of monomeric and macroforms of prolactin were determined using gel filtration chromatography (GFC). RESULTS: Normative data for six prolactin assays included the range of values (2.5th-97.5th percentiles). Validation sera (hyperprolactinemic and macroprolactinemic; n=27) showed higher discordant classification [mean=2.8; 95% confidence interval (CI) 1.2-4.4] for the monomer reference interval method compared to the post-polyethylene glycol (PEG) recovery cutoff method (mean=1.8; 95% CI 0.8-2.8). The two monomer/macroprolactin discrimination methods did not differ significantly (p=0.089). Among macroprolactinemic sera evaluated by both discrimination methods, the Cobas and Architect/Kryptor prolactin assays showed the lowest and the highest number of misclassifications, respectively. CONCLUSIONS: Current automated immunoassays for prolactin testing require macroprolactin screening methods based on PEG precipitation in order to discriminate truly from falsely elevated serum prolactin. While the recovery cutoff and monomeric reference interval macroprolactin screening methods demonstrate similar discriminative ability, the latter method also provides the clinician with an easy interpretable monomeric prolactin concentration along with a monomeric reference interval.

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Fundamento. La prolactina se puede presentar bajo varias formas moleculares siendo la forma monométrica (PRLm) la biológicamente activa. La presencia de macroprolactina (MPRL) puede originar un falso diagnóstico de hiperprolactinemia debido a la interferencia en el procedimiento de medida. El objetivo ha sido desarrollar un protocolo que permita diagnosticar la hiperprolactinemia monométrica, que además sea complementario al procedimiento que detecta MPRL. Material y métodos. La población de referencia para PRLm estaba formada por 122 mujeres y 140 hombres aparentemente sanos a los que se les extrajo sangre para la cuantificación de PRL. Además, se recogieron49 sueros (33 mujeres y 16 hombres) hiperprolactinémicos. Se cuantificó PRL en todas las muestras en un Immulite 2000. La detección de MPRL y de PRLm se realiza tras precipitación con polietilenglicol. Se confirmó el resultado por cromatografía de filtración en gel. Para la obtención de los valores de referencia se siguieron las indicaciones del Panel de Expertos de la IFCC. Resultados. Los valores de referencia de PRLm fueron 3,4-26,6 ¦Ìg/L y 4,6-16,4 ¦Ìg/L en mujeres y varones, respectivamente. De los 49 pacientes hiperprolactinémicos, en el57 % la concentración de PRLm tras PEG se encontraba fuera del intervalo de referencia previamente obtenido, confirmándosela presencia de hiperprolactinemia monométrica. Conclusiones. Se ha desarrollado e implantado un protocolo para la cuantificación de PRLm. La obtención del os valores de referencia de PRLm permite el diagnóstico de la hiperprolactinemia monométrica o activa de forma complementaria a la identificación de MPRL (AU)

Background. Prolactin can take several molecular forms of which the most biologically active is the monomericform (PRLm). The presence of macroprolactin (MPRL) can give rise to a false diagnosis of hyperprolactinemia due to interference in the measuring procedure. The aim was to develop a protocol that enables diagnosis of monomeric hyperprolactinemia, which should also be complementary to the procedure for detecting MPRL. Material and methods. The reference population for PRLm was made up of 122 healthy women and 140healthy men, from whom blood was extracted for PRL quantification. Additionally, 49 hyperprolactinemic serums (33 women and 16 men) were collected. PRL was quantified in all the samples in an Immulite 2000.The detection of MPRL and PRLm was carried out following precipitation with polyetylenglicol (PEG). The result was confirmed by gelatin filtration chromatography. The reference values were obtained following theindications of the Expert Panel of the IFCC. Results. The PRLm reference values were 3,4-26,6¦Ìg/L and 4,6-16,4 ¦Ìg/L in women and men, respectively. In 57% of the 49 hyperprolactinemic patients the concentration of PRL m following PEG fell outside the previously obtained reference interval, confirming the presence of monomeric hyperprolactinemia. Conclusions. A protocol for quantifying PRL m has been developed and implemented. Obtaining PRLm reference values makes it possible to diagnose monomeric oractive hyperprolactinemia in a complementary form to the identification of MPRL(AU)

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BACKGROUND: Macroprolactin is an important source of immunoassay interference that commonly leads to misdiagnosis and mismanagement of hyperprolactinemic patients. We used the predominant immunoassay platforms for prolactin to assay serum samples treated with polyethylene glycol (PEG) and establish and validate reference intervals for total and monomeric prolactin. METHODS: We used the Architect (Abbott), ADVIA Centaur and Immulite (Siemens Diagnostics), Access (Beckman Coulter), Elecsys (Roche Diagnostics), and AIA (Tosoh) analyzers with samples from healthy males (n = 53) and females (n = 93) to derive parametric reference intervals for total and post-PEG monomeric prolactin. Concentrations of immunoreactive prolactin isoforms in serum samples from healthy individuals were established by gel filtration chromatography (GFC). We then used samples from 22 individuals whose hyperprolactinemia was entirely attributable to macroprolactin and 32 patients with true hyperprolactinemia to compare patient classifications and prolactin concentrations measured by GFC with the newly derived post-PEG reference intervals. RESULTS: Parametric reference intervals for post-PEG prolactin in male and female serum samples, respectively, were (in mIU/L): 61-196, 66-278 (Centaur); 63-245, 75-381 (Elecsys); 70-301, 92-469 (Access); 72-229, 79-347 (Architect); 73-247, 83-383 (AIA); and 78-263, 85-394 (Immulite). Concordance between GFC and immunoassay-specific post-PEG reference intervals was observed in 311 of 324 cases and for 31 of 32 patients with true hyperprolactinemia and 17 of 22 patients with macroprolactinemia. Results leading to misclassification occurred in a few analyzers for 5 macroprolactinemia patient samples with relatively minor increases in post-PEG prolactin (mean 61 mIU/L). CONCLUSIONS: Our validated normative reference data for sera pretreated with PEG and analyzed on the most commonly used immunoassay platforms should facilitate the more widespread introduction of macroprolactin screening by clinical laboratories.

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We measured serum follicle-stimulating hormone (FSH), luteinizing hormone (LH) and prolactin concentrations on a bioMérieux Mini Vidas system in a pediatric population ranging in age from 1 to 19 years. Reference intervals were established separately for females and males, with stratification by age group and by Tanner's pubertal stage. FSH values were higher in females than in males, and were lowest in both sexes of age class 2 (4-8 years), increasing thereafter to the upper limit for stage PIV (females) and stage PV (males). LH values showed a similar pattern of change: concentrations were lowest for class 1 (1-3 years) and class 2 (4-8 years), and highest for stage PII (females) and stage PV (males). No significant difference was observed according to gender. Prolactin values did not differ markedly according to gender or pubertal status.

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BACKGROUND: Increased serum concentrations of macroprolactin are a relatively common cause of misdiagnosis and mismanagement of hyperprolactinemic patients. METHODS: We studied sera from a cohort of 42 patients whose biochemical hyperprolactinemia was explained entirely by macroprolactin. Using 5 pretreatments, polyethylene glycol (PEG), protein A (PA), protein G (PG), anti-human IgG (anti-hIgG), and ultrafiltration (UF), to deplete macroprolactin from sera before immunoassay, we compared residual prolactin concentrations with monomer concentrations obtained by gel-filtration chromatography (GFC). A monomeric prolactin standard was used to assess recovery and specificity of the pretreatment procedures. RESULTS: Residual prolactin concentrations in all pretreated sera differed significantly (P < 0.001) from monomeric concentrations obtained after GFC. PEG underestimated (mean, 75%), whereas PA, PG, anti-hIgG, and UF overestimated (means, 178%, 151%, 178%, and 112%, respectively) the amount of monomer present. Of the 5 methods examined, PEG correlated best with GFC (r = 0.80) followed by PG (r = 0.78), PA (r = 0.72), anti-hIgG (r = 0.70), and UF (r = 0.61). After UF or pretreatment with anti-hIgG or PEG, recovery of monomeric prolactin standard was low: 60%, 85%, and 77% respectively. In contrast, pretreatment with PA or PG gave almost quantitative recovery. CONCLUSIONS: None of the methods examined yielded results identical to the GFC method. PEG pretreatment yielded results that correlated best and is recommended as the first-choice alternative to GFC.

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There is a growing pressure on clinical chemistry laboratories to conform to quality standards that require the evaluation and expression of the uncertainty of results of measurement. Nevertheless, there is some reluctance to accept the uncertainty concept in the analytical community due to difficulty in evaluating uncertainty in practice. For example, often the uncertainty of some uncertainty components is not known very well in clinical chemistry measurements, such as those associated with matrix effects or with the values of the calibrators. Moreover, it is not clear how to interpret uncertainty in relation to diagnostic criteria, reference ranges and other decision limits in clinical chemistry practice. Hence, the value of reporting the uncertainty of the measurement result is not obvious. In this paper it is suggested a relatively simple, logical procedure for evaluating measurement uncertainty based on the principles in the Guide for the Expression of Uncertainty of Measurement (GUM). The measurement process is partitioned into elements that are well known to the analyst, namely sampling, calibration, and analysis. The corresponding model function expresses the result of a measurement as the value obtained by the analytical procedure multiplied by the correction factors for sampling bias, for bias caused by the calibrators, and for other types of bias. Under normal conditions, when the measurement procedure is validated and corrected for all known bias, the expected value of each correction factor is one. The uncertainty that remains with regard to sampling, manufacturing of calibrators and other types of bias is combined with the analytical imprecision to yield a combined uncertainty of a result of measurement. The advantages of this approach are: (i) Data from the method validation, internal quality control and from participation in external quality control schemes can be used as input in the uncertainty evaluation process. (ii) The partition of the measurement into well-defined tasks highlights the different responsibilities of the clinical chemistry laboratory and of the manufacturer of reagents and calibrators. (iii) The approach can be used to harmonize the uncertainty evaluation process, which is particularly relevant for laboratories seeking accreditation under ISO 17025. The application of the proposed model is demonstrated by evaluating the uncertainty of a result of a measurement of prolactin in human serum. In the example it is shown how to treat the uncertainty associated with a calibrator supplied with a commercial analytical kit, and how to evaluate the uncertainty associated with matrix effects.

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Pure acetylcholinesterase (EC 3.1.1.7) from Electrophorus electricus has been covalently coupled to rat prolactin using the heterobifunctional reagent: N-succinimidyl-4 (N-maleimidomethyl) cyclohexane-1-carboxylate (SMCC). This conjugate was used as a tracer in a competitive enzyme immunoassay using a rabbit antiserum, raised against rat prolactin, as first antibody. The assay was performed in 96-well microtiter plates coated with a mouse monoclonal anti-rabbit immunoglobulin antibody. This second antibody solid phase ensured separation of bound and free moieties of the tracer during the specific immunoreaction. The total reaction volume was 150 microliters. Each component (tracer, antiserum and standard) was added in a volume of 50 microliters. The sensitivity of the assay was good since calculation indicated a detection threshold of 25 pg (0.5 ng/ml) and a B/Bo 50% value of 220 pg (4.4 ng/ml). Intra-assay variation was better than 10% over a wide range (135 to 2500 pg) with an optimum of 4% at 300 pg. The inter-assay coefficient of variation was less than 15% for rat plasma samples in the concentration range of 8 to 1000 ng/ml. The good parallelism observed between the standard curve and sample dilution curves, and recovery experiments, indicated that direct assay is possible. This was confirmed by molecular sieve fractionation of plasma samples. The reliability of the assay was confirmed by good correlation with conventional radioimmunoassay (r = 0.996, slope = 0.978).

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Three ampouled preparations of purified human prolactin were assessed by 20 laboratories in eight countries for their suitability to serve as International Standards for the estimation of human prolactin in serum. Bioassays (pigeon crop sac assays and NB2 cell assays) were carried out in two laboratories, radioreceptor assays by one laboratory and radioimmunoassays by 17 laboratories. By physicochemical analysis the preparations appeared similar. Each preparation contained small amounts of contaminants and/or prolactin variants. No major differences among the three preparations were detected by immunoassay although, in one radioreceptor assay system, one of the preparations was found to differ from the other two. On the basis of all the available information, the Expert Committee on Biological Standardization of the World Health Organization (ECBS) in 1986 established the preparation in ampoules coded 83/562 as the Second International Standard for Prolactin and in October 1988 established the preparation in ampoules coded 84/500 as the Third International Standard for Prolactin. A value of 0.053 IU (53 mIU) prolactin activity/ampoule was assigned to both the Second and Third IS on the basis that this unitage would, insofar as possible, maintain continuity of the IU defined by the First International Reference Preparation of Prolactin, human, for Immunoassay (coded 75/504).

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As authorized by the World Health Organization 29th Expert Committee on Biological Standardization, the preparation of human prolactin in ampoules coded 75/504 has been established as the International Reference Preparation (IRP) of human prolactin for immunoassay. From the results of a collaborative study, to which 15 laboratories in nine countries contributed, with the agreement of the participants, the content of each ampoule is defined as 0.650 International Units (i.u.; 650 mi.u.) immunoassay. The results of this collaborative study show that the IRP is adequately stable and suitable for use as a standard for the determination of prolactin in human plasma and serum. Estimates of the prolactin content of human plasma and serum made in the various laboratories have been compared and show good agreement in ranking order, but only fair agreement in the numerical value of the estimates. Numerical agreement is poor between estimates of the human prolactin content of two samples identical except for coding; this shows the difficulty in achieving continuity of estimates when any laboratory calibrates a replacement standard.

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