Volume 50, Issue 5 - Special issue: Reference values

Casual or systematic errors occurring in pre-analytical, analytical or post-analytical phases influence laboratory test results. The areas where pre-analytical phase errors most often arise are: timing of specimen collection; selection of specimen type; and time and temperature of storage/transport. Bone turnover markers are clinically useful in evaluating bone metabolism. Although unquestionably valuable tools, little is known about the pre-analytical precautions for their correct use and there is no consensus on kind of sample, or storage time and temperature before analysis. Moreover, biological variability, because of uncontrollable and controllable factors, will affect pre-analytical variability. Serum should be preferred to simplify blood drawing; therefore, only one tube should be used for the analysis of all bone markers. Short-term storage at 4°C may be advisable to preserve stability, immediate storage at –70°C is recommended for longer periods, while avoiding repeated freeze-thawing cycles. Sampling should be performed in the morning in fasting subjects who have abstained from physical exercise for 24 h. This review aimed to give a knowledge update on pre-analytical phase precautions in performing bone turnover marker measurement.

Cardiac troponins (cTn) are the preferred markers for the diagnosis of acute myocardial infarction (AMI). The guidelines recommend the use of the 99th percentile upper reference concentration of a healthy population as the diagnostic cut-off for AMI. However, a broad range of upper reference limits is still employed, complicating the diagnosis of AMI. This overview is meant to assist laboratory specialists to define an appropriate cut-off value for the diagnosis of AMI. Therefore, we provide an overview of the analytical performance and upper reference limits of seven (high-)sensitivity cTn assays: Roche high-sensitivity cTnT and ADVIA Centaur, Stratus CS, Dimension Vista, Vitros ECi, Access and Architect cTnI assays. It is shown that none of the reference populations completely met the guidelines, including those in package inserts. Forty percent of the studies collected less than the advised minimum of 300 subjects. Many studies (50%) did not report their inclusion criteria, while lower 99th percentile limits were observed when more stringent selection criteria were applied. Higher troponin cut-offs were found in men and elderly subjects, suggesting sex- and age-specific cut-offs would be considered. Therefore, there is still need for a large, rigorously screened reference population to more accurately establish cTn upper reference limits.

Reference change values (RCV) provide objective tools for assessment of the significance of differences in serial results from an individual. The concept is simple and the calculation easy, since all laboratories know their analytical imprecision (CV A ) and estimates of within-subject biological variation (CV I ) are available for a large number of quantities. Generally, CV I are constant over time, geography, methodology and in health and chronic stable disease. The formula is RCV=2 1/2 · Z · (CV A 2 + CV I 2 ) 1/2 , where Z is the number of standard deviations appropriate to the probability. Correct interpretation of the semantics describing the clinical use of RCV is vital for selection of the Z -score. Many quantities of clinically importance exist for which good estimates of RCV are unavailable. Derivation of CV I may be difficult for such quantities: flair and imagination are required in selecting populations with chronic but stable disease on whom CV I can be determined. RCV can be used for delta-checking and auto-verification and laboratory information management systems (LIMS) can be adapted to do this. Recently, log-normal transformation to obtain unidirectional RCV has been used. Gaps in knowledge of RCV still require filling since the need for measures of change is clearly expressed in guidelines.

An issue associated with standardization efforts is the need to develop useful reference intervals (RI). Lack of proper RI may hamper the implementation of standardization in Laboratory Medicine as standardization can modify analyte results and, without adequate RI, this can impair the result interpretation. Once defined, RI obtained with analytical procedures that produce results traceable to the corresponding reference system can be transferred among laboratories, providing that they use commercial assays that produce results traceable to the same reference system and populations have the same characteristics. Multicenter studies are needed for a robust definition of traceable RI, using experimental protocols that include well defined prerequisites. Particularly, employed methods must produce results that are traceable to the reference system for that specific analyte. Thus, the trueness of laboratories producing reference values should be verified and, if necessary, experimental results corrected in accordance with correlation results with the selected reference. If requirements in the adoption of traceable RI are fulfilled, the possibility of providing RI that are applicable to any laboratory, able to produce results traceable to the reference system, is realistic. The definition of traceable RI should hopefully cause the disappearance of different RI employed for the same analyte, providing more effective information to clinicians.

With the increasing use of decision limits (action limits, cut-off points) specified for a number of analytical components in diagnosis and for action in critical situations, formulated in national or international recommendations, the traditional interpretation of reference intervals has been uncertain, and sometimes the two concepts are being mixed up by incorporating risk calculations in the reference intervals. There is, therefore, a need to clarify the two concepts and to keep them definitely separated. Reference intervals are the 95% limits for the descriptions of the distributions of the values of analytical components measured on reference samples from reference individuals. Decision limits are based on guidelines from national and international expert groups defining specific concentrations of certain components as limits for decision about diagnosis or well-defined specific actions. Analytical quality specifications for reference intervals have been defined for bias since the 1990s, but in the recommendations specified in the clinical guidelines analytical quality specifications are only scarcely defined. The demands for negligible biases are, however, even more essential for decision limits, as the choice is no longer left to the clinician, but emerge directly from the concentration. Even a small bias will change the number of diseased individuals, so the demands for negligible biases are obvious. A view over the analytical quality as published gives a variable picture of bias for many components, but with many examples of considerable bias which must be critical – yet no specifications have been stipulated until now.

Permissible limits for internal and external quality assurance are either based on biological variation or on the state of the art (technical feasibility). The former approach has a scientific basis, but, in some cases, leads to limits which are either not achievable under the present technology, or which are not stringent enough. If proficiency testing is mandatory, stringent limits which cannot be fulfilled by the majority of laboratories could lead to juristic consequences. Therefore, most national guidelines were based on the state of the art, however, without providing the underlying reasoning. A simple algorithm for permissible limits in external quality assessment schemes (EQAS) is proposed based on biological variation, technical feasibility and correlated to the rate of false positive results. The proposed limits are compared with some limits from several EQAS (RiliBÄK, SEKK, RCPA, CLIA, PROLARIT). The suggested limits are slightly more stringent than the German RiliBÄK, less stringent than the Australasian guidelines and agreed best with the Czech SEKK and the Italian PROLARIT scheme. The graphical presentation of permissible limits strictly derived of biological variation with the proposed limits led to straight lines with different slopes and a cross-over at the limits for quantities with a medium biological variation (e.g., trijodthyronine). The greatest discordance between the various recommendations was observed for calcium, chloride, hemoglobin A 1c and sodium.

Background: The knowledge of biological variation (BV) data is important for clinical decisions and as a basis for defining analytical quality specifications. However, in gene\xadrating reliable data of biological variation there are still some unsolved problems, such as age dependence. The aim of our work is to verify this aspect. Methods: Twenty-six subjects divided into three groups by age were studied. Blood samples were collected in lithium heparin tubes for four weeks at one week intervals, on the same day of the week (Tuesday) and at the same time of day (8–9 a.m.) by the same phlebotomist. They were analysed in duplicate for creatinine, urate, calcium, albumin, total cholesterol, high density lipoprotein (HDL) and low density lipoprotein (LDL)-cholesterol, triglycerides and iron. After outlier exclusion by Cochran\u2019s test, components of biological variation were calculated by ANOVA. The significance of the differences between results of the classes was also calculated with the Student\u2019s test (t-test) and the Fisher\u2019s test (F-test). Results: Excluding albumin, the group 3 results (age range from 78 to 98 years) showed significantly lower CV within subjects (CV W ) than the other two groups. Conclusions: Our data seem to highlight the relevance of the age when choosing the reference subjects for biological variation studies. The level of within-subject biological variation of the elderly group may have been further reduced by the homogeneity of the group constituted by individuals living together in the same nursing home.

Background: Reference intervals are crucial decision-making tools aiding clinicians in differentiating between healthy and diseased populations. However, for children such values often are lacking or incomplete. Methods: Blood samples were obtained from 692 healthy children, aged 6 months to 18 years, recruited in daycare centers and schools. Twelve common general clinical chemistry analytes were measured on the Abbott Architect ci8200 platform; sodium, potassium, chloride, calcium, albumin-adjusted calcium, phosphate, magnesium, creatinine (Jaffe and enzymatic), cystatin C, urea and uric acid. Results: Age- and gender specific pediatric reference intervals were defined by calculating the 2.5th and 97.5th percentiles. Conclusions: The data generated is primarily applicable to a Caucasian population when using the Abbott Architect platform, but could be used by any laboratory if validated for the local patient population.

Background: The biorhythm of serum uric acid was evaluated in a large sample of a clinical laboratory database by spectral analysis and the influence of the gender and age on uric acid variability. Methods: Serum uric acid values were extracted from a large database of a clinical laboratory from May 2000 to August 2006. Outlier values were excluded from the analysis and the remaining data (n=73,925) were grouped by gender and age ranges. Rhythm components were obtained by the Lomb Scargle method and Cosinor analysis. Results: Serum uric acid was higher in men than in women older than 13 years (p<0.05). Compared with 0–12 year group, uric acid increased in men but not in women older than 13 years (p<0.05). Circannual (12 months) and transyear (17 months) rhythm components were detected, but they were significant only in adult individuals (>26 years, p<0.05). Cosinor analysis showed that midline estimating statistic of rhythm (MESOR) values were higher in men (range: 353–368 μmol/L) than in women (range: 240–278 μmol/L; p<0.05), independent of the age and rhythm component. The extent of predictable change within a cycle, approximated by the double amplitude, represented up to 20% of the corresponding MESOR. Conclusions: Serum uric acid biorhythm is dependent on gender and age and it may have relevant influence on preanalytical variability of clinical laboratory results.

Background: Serum amino acids, part of a pool of free amino acids, are influenced by metabolism and disease. Few reports exist describing their function and concentrations in serum. Our study aimed to determine age- and gender-related differences in serum amino acid concentrations in healthy Japanese patients, focusing on their inclusion in body proteins. Methods: Healthy patients with normal liver and kidney function were selected based on biochemical variables. Serum amino acid concentrations in 23–88-year-old patients (312 males, 252 females; 52.1±15.0 years) were evaluated to determine the normal values and to clarify the differences in concentration. The patients were divided into 11 groups according to their gender and age (in 5-year increments), and serum amino acid concentrations were determined as the normal values for each group. Results: Some amino acids increased or decreased with age. Values of leucine, threonine, methionine, histidine, glycine, serine and taurine decreased with age in males, whereas, those of threonine and serine decreased with age in females (p<0.05). In contrast, values of phenylalanine, aspartate, asparagine, glutamate, alanine, citrulline, ornithine, arginine and tyrosine increased with age in males, whereas, values of phenylalanine, lysine, asparagine, glutamate, glutamine, alanine, citrulline, ornithine, arginine, tyrosine and proline increased with age in females (p<0.05). Conclusions: We clarified basic trends of age- and gender-related amino acid concentrations in serum. In normal healthy Japanese people who ate normally and lived an independent life, there are significant age- and gender-related differences.

Background: Abbott Diagnostics have developed a new highly sensitive troponin I (hs-TnI) assay. We have assessed its analytical characteristics and applied the assay to a population of apparently cardio-healthy persons. Methods: We assessed imprecision, bias compared to the previous generation assay, matrix effects, and interferences and applied the assay to an apparently healthy population, deriving the 99th percentile limit of the distribution of values in reference populations for men and women separately. Results: The dynamic range of the assay was ranged from 0.5–50,000 ng/L (pg/mL). The 10% CV was at a concentration of 3.9 ng/L, and the 20% CV was at a concentration of 1.8 ng/L. The new and current version of the TnI assay were highly correlated [slope: 0.98 (95%CI:0.88–1.07), y -intercept:1.20 (95%CI:-2.35–4.75) r 2 =0.99]. The 99th percentile limit of the distribution of values in a reference population was different for males and females: for males 14.0 ng/L and for females 11.1 ng/L and at these concentrations the assay CV was 5.0%. TnI was detectable in nearly all patient samples from the healthy reference population (98.6%). Conclusions: This new hs-TnI assay is able to measure to an order of magnitude lower than the current generation TnI assay from the same manufacturer. With TnI being detectable in nearly all apparently healthy subject samples this suggests that TnI presence does not always indicate cardiomyocyte necrosis.

Background: Laboratory reference intervals are not necessarily reflecting the range in the background population. This study compared creatine kinase (CK) reference intervals calculated from a large sample from a Norwegian population with those elaborated by the Nordic Reference Interval Project (NORIP). It also assessed the pattern of CK-normalization after standardized control analyses. Methods: New upper reference limits (URL) CK values were calculated after exclusion of individuals with risk of hyperCKemia and including individuals with incidentally detected hyperCKemia after they had completed a standardized control analysis. After exclusion of 5924 individuals with possible causes of hyperCKemia, CK samples were analyzed in 6904 individuals participating in the 6th survey of The Tromsø Study. URL was defined as the 97.5 percentile. Results: New URL in women was 207 U/L. In men <50 years it was 395 U/L and in men ≥50 years 340 U/L. In individuals with elevated CK, normalization grade after control analysis was inversely correlated to the CK level (p<0.04). Conclusions: URL CK values in women and in men <50 years of age were in accordance with URL CK values given by the NORIP. In men ≥50 years, a higher URL was found and the findings suggest an upward adjustment of URL in this age group.

Background: Establishment of reliable reference intervals remains valuable for confirming validity and advancing standardization across methods and populations. Moreover, knowledge of the measurement uncertainty (U) and of the reference change value (RCV) has important applications in clinical chemistry. Methods: Starting from the information available in the laboratory data base (29,901 subjects) an initial selection was carried out by eliminating all subjects with a clinical or laboratory pathological report; data from 7581 0- to 20-year-old subjects (53.87% girls) remained in the study. These subjects, divided into nine age groups, were used to define reference distribution percentiles (2.5th, 50th and 97.5th) of serum thyrotropin (TSH), triiodothyronine (T3), thyroxine (T4), and free T4 (fT4), as well as U and RCV of these assays. Results: In early infancy, T4 and fT4 values were higher than in the older age groups. Serum T4 95th percentile reference value, useful for the diagnosis of hyperthyroidism, was 142.9 in 20-year-old boys and 230.4 nmol/L in early infants and serum T3 95th percentile was 2.6 and 3.5 nmol/L, respectively, while fT4 2.5th percentile reference value, useful for the diagnosis of hypothyroidism, was 9.6 and 13.0 pmol/L, respectively. Serum TSH 97.5th percentile showed less age variation, 4.38–4.88 mIU/L. Performance of the four assays resulted in approximately 20% Us, reflecting simple and complex imprecision, trueness, analytical and functional sensitivity. RCV of serum TSH (58.6%) was larger than for thyroid hormones (28.3%–34.7%), probably due to the high biological variation of this hormone. Conclusions: We have established reference interval for TSH and thyroid hormones, as well as Us for assessing reliability of measurements, and RCVs to alert users on the presence of clinical significant changes.

Background: The present study was undertaken to establish serum thyroglobulin (Tg) normal reference values in a large group of healthy subjects. Methods: Four hundred and thirty-eight non-smoking healthy subjects were selected to assess the Tg reference values (209 males, 229 non-pregnant females, age 34.7±13.1 years). Inclusion criteria were: no personal or familial history of thyroid disease, thyrotropin levels from 0.5 to 2.00 mUI/L, negative thyroperoxidase and thyroglobulin antibodies. In addition, the patients had a normal size thyroid (females ≤18 mL, males ≤25 mL) without nodules on the thyroid ultrasound (TUS). According to National Academy of Clinical Biochemistry (NACB) criteria the Tg results were transformed to a logarithmic scale and reference ranges were calculated as mean±2 SD. Results: Serum Tg was measured on the Beckman Coulter UniCel DxI 800 automated platform by the simultaneous 1-step immunoenzymatic Access Thyroglobulin assay (Beckmann-Coulter SA, Nyon, Switzerland). Serum Tg levels were higher in females than in males (p=0.0022). Accordingly, gender-specific reference values were calculated (i.e., males: 1.40–29.2 ng/mL; females: 1.50–38.5 ng/mL). Conclusions: To the best of the authors’ knowledge, the first reference interval study for Tg that integrates NACB criteria and TUS assessment for the selection of the reference population is provided here.

Background: We aimed to assess determinants for serum calcitonin (CT) levels and to define reference ranges for different CT immunoassays integrating thyroid ultrasonography (TUS) and conventional clinical and biochemical criteria to select the reference population. Methods: Five hundred and nineteen thyroid-healthy subjects were included in this prospective cross-sectional population study. Thyroid volume was measured by TUS, while serum CT levels were measured by three different immunoassays. Results: Significant interassay differences were found and the agreement between assays was poor. CT levels were higher in males than in females in all immunoassays. Using the first two assays, both gender and thyroid volume were independent determinants for CT levels. While using the third assay, one thyroid volume was the only determinant for CT levels. Conclusions: Thyroid volume is a relevant determinant for CT levels. In the clinical practice, the difference of the thyroid sizes in males and females warrants gender-specific reference ranges.

Background: After modification of our routine cortisol assay, we questioned the reference ranges for basal and stimulated cortisol plasma concentration in children. Methods: We retrospectively addressed the relevance of using the manufacturer’s normal reference range for basal cortisol and investigated its response to glucagon-betaxolol testing. Results: Basal morning cortisol was 260 (98–604) nmol/L [manufacturer’s normal range (185–624) nmol/L: 26% subjects had “low” basal cortisol]. Upon testing cortisol increased to 502 (117–856) nmol/L. If a recently described 100% specificity threshold (403 nmol/L) is used it would amount to 31% adrenal insufficient children in apparently unaffected children. Basal and stimulated cortisol obtained with our prior radioimmunoassay (RIA) in a sub-group of subjects were lower: 411 (187–1061) and 770 (329–1542) nmol/L. Using the 403 nmol/L threshold with the radioimmunoassay would result in only 5% adrenal insufficient children. Conclusions: This shows again that laboratories have to advertise the need to establish reference values for given populations, both for basal or stimulated hormone levels. Failure to apply this rule will elicit false-positive and more critically, false-negative results.

Background: Diabetes in pregnancy imposes additional risks to both mother and infant. These increased risks are considered to be primarily related to glycaemic control which is monitored by means of glycated haemoglobin (HbA 1c ). The correlation of HbA 1c with clinical outcomes emphasises the need to measure HbA 1c accurately, precisely and for correct interpretation, comparison to appropriately defined reference intervals. Since July 2010, the HbA 1c assay in Irish laboratories is fully metrologically traceable to the IFCC standard. The objective was to establish trimester-specific reference intervals in pregnancy for IFCC standardised HbA 1c in non-diabetic Caucasian women. Methods: The authors recruited 311 non-diabetic Caucasian pregnant (n=246) and non-pregnant women (n=65). A selective screening based on risk factors for gestational diabetes was employed. All subjects had a random plasma glucose <7.7 mmol/L and normal haemoglobin level. Pregnancy trimester was defined as trimester 1 (T1, n=40) up to 12 weeks +6 days, trimester 2 (T2, n=106) 13–27 weeks +6 days, trimester 3 (T3, n=100) >28 weeks to term. Results: The normal HbA 1c reference interval for Caucasian non-pregnant women was 29–37 mmol/mol (Diabetes Control and Complications Trial; DCCT: 4.8%–5.5%), T1: 24–36 mmol/mol (DCCT: 4.3%–5.4%), T2: 25–35 mmol/mol (DCCT: 4.4%–5.4%) and T3: 28–39 mmol/mol (DCCT: 4.7%–5.7%). HbA 1c was significantly decreased in trimesters 1 and 2 compared to non-pregnant women. Conclusions: HbA 1c trimester-specific reference intervals are required to better inform the management of pregnancies complicated by diabetes.

Background: Varying concentrations of adiponectin are present in human breast milk. This study aimed to determine the relationship between milk adiponectin concentration and the hormonal and inflammatory status of breast-feeding women. Methods: Blood and breast milk samples were collected from 157 breast-feeding women enrolled at 1–180 post-partum lactation days. The milk and serum adiponectin concentrations were measured by radioimmunoassays. The serum oestradiol, prolactin, thyroxine, triiodothyronine, cortisol and insulin concentrations were measured by the chemiluminescent immunometric method. The leptin, resistin and ghrelin concentrations were measured by the immunometric methods. Results: The milk, but not serum, adiponectin concentration increased during the 180-day lactation period and displayed a positive correlation (r=0.748; p<0.001) to the lactation day. The milk adiponectin concentration was positively correlated to the maternal serum ghrelin concentration (r=0.299; p<0.001) and inversely to the maternal serum oestradiol (r=–0.366; p<0.001), prolactin (r=–0.444; p<0.001), thyroxine (r=–0.355; p<0.001), triiodothyronine (r=–0.291; p<0.001), cortisol (r=–0.537; p<0.001), and C-reactive protein (r=–0.483; p<0.001) concentrations. The milk adiponectin concentration was positively correlated to the milk leptin (r=0.344; p<0.001) and ghrelin (r=0.458; p<0.001) concentrations, and inversely to milk resistin concentration (r=–0.518; p<0.001). The serum adiponectin concentration in breastfed infants was positively correlated (r=0.711; p<0.001) to the adiponectin concentration in the consumed breast milk. Conclusions: The adiponectin concentration in breast milk increases over time during lactation and is affected by the maternal hormonal and inflammatory status.

Background: Early detection of patients with chronic kidney disease is of great importance. This study developed reference limits for serum creatinine and serum cystatin C concentrations and for the estimated glomerular filtration rate (eGFR) in healthy subjects from the general population aged 25–65 years. Methods: This study defined a reference population including 985 subjects from the first follow-up of the Study of Health in Pomerania. Serum creatinine was measured with a modified kinetic Jaffé method. Serum cystatin C was measured with a nephelometric assay. The eGFR was calculated from serum creatinine according to the Cockcroft-Gault (eGFR CG ) and the Modification of Diet in Renal Disease (eGFR MDRD ) equation, respectively, as well as from serum cystatin C according to the formula by Larsson (eGFR Larsson ). Non-parametric quantile regression was used to estimate the reference limits. For serum creatinine and serum cystatin C the 95th percentile and for eGFR CG , eGFR MDRD and eGFR Larsson the 5th percentile were selected as reference limits. All data was weighted to reflect the age- and sex-structure of the German population in 2008. Results: The reference limits for serum creatinine (men: 1.11–1.23 mg/dL; women: 0.93–1.00 mg/dL) and serum cystatin C levels (men: 0.92–1.04 mg/L; women: 0.84–1.02 mg/L) increased with advancing age. The reference limits for eGFR decreased with increasing age (eGFR CG men: 106.0–64.7 mL/min, women 84.4–57.9 mL/min; eGFR MDRD men: 82.5–62.2 mL/min/1.73 m 2 , women 75.0–58.2 mL/min/1.73 m 2 ; eGFR Larsson men: 85.5–72.9 mL/min, women 94.5–75.7 mL/min). Conclusions: This study presents age- and sex-specific reference limits for five measures of renal function based on quantile regression models.

Background: Biological variation is important for determining analytical goals and for establishing the magnitude of change between two consecutive measurements. The aim of this study was to determine the biological variation for S100β and lactate dehydrogenase in patients diagnosed with malignant melanoma but without evidence of disease recurrence. Methods: The biological variation of S100β and lactate dehydrogenase was estimated from a mean of four consecutive measurements in 32 patients diagnosed with malignant melanoma but without evidence of disease recurrence, 3 months after tumor resection or 4 months after finishing adjuvant treatment. The mean sampling interval was 3 months. Results: Mean concentrations of S100β and lactate dehydrogenase were 0.0557 μg/L and 6.3 μkat/L, respectively. Between-run analytical variation was 3.5% at 0.181 μg/L for S100β and 3.5% at 2.83 μkat/L for lactate dehydrogenase. Biological variations obtained for S100β and lactate dehydrogenase were 14.2% and 8.2%, respectively. The analytical goals (defined as 50% of biological variation) were 7.1% for S100β and 4.1% for lactate dehydrogenase. Conclusions: The estimation of biological variation allows us to calculate analytical goals and reference change values. These are necessary tools for the correct interpretation of serial measurements in patient follow-up.

Background: Kallikrein 6 (KLK6) is a serine protease involved in numerous cellular processes, up-regulated in many cancers and associated with some neurodegenerative disorders. The aim of this study was to establish a reference interval and estimate the biological variation of KLK6 in serum samples of adults. Furthermore, levels of this protein in patients with renal failure were also studied. Methods: Serum samples from healthy volunteers (n=136) were collected. Between 15 and 18 additional samples from four of these subjects were obtained over a period of 2 months. Samples from individuals (n=1043) who visited the University Health Network for a routine check-up were collected to study the association between KLK6 with age and gender. Samples from patients with renal failure (n=106) were also obtained and KLK6 and creatinine concentrations were analyzed by ELISA and an automated enzymatic method, respectively. Results: The reference interval was established to be 1.04–3.93 ng/mL. The index of individuality was 0.43 and the reference change value was 35%. Only two serum samples would be required to estimate the homeostatic setting point of an individual. There is a weak but highly significant positive correlation between KLK6 and age (p<0.0001). Furthermore, there is a significant positive correlation between serum concentrations of KLK6 and creatinine (p<0.0001), in patients with renal failure. Conclusions: The established reference interval for KLK6 and the estimation of its biological variation will further aid in the clinical use of this protein as a serum marker of malignancy and other diseases.

Background: Faecal immunochemical tests (FIT) are becoming widely used in colorectal cancer screening. Estimation of faecal haemoglobin concentration in a large group prompted an observational study on gender and age. Methods: A single estimate of faecal haemoglobin concentration was made using quantitative automated immunoturbidimetry. Potential reference intervals were calculated for men and women and for age quintiles according to the Clinical and Laboratory Standards Institute Approved Guideline. The percentages of positive results were calculated at a number of concentrations. The percentages of individuals who fell into different risk groups were assessed. Results: The 97.5 percentiles, potential upper reference limits, were 519 ng haemoglobin/mL (90% CI: 468–575) for men and 283 ng haemoglobin/mL (90% CI: 257–316) for women. Concentrations increased with age in both genders. Decision limits have advantages over reference intervals. At any cut-off concentration, more men are declared positive than women and more older people are declared positive than younger people. Future risk of neoplasia is higher in men than in women and in older people. Conclusions: Faecal haemoglobin concentrations vary with gender and age. More tailored strategies are needed in screening programmes. Faecal haemoglobin concentration could be included in individual risk assessment scores. These data should assist in screening programme design.

Background: Optical analysis of erythrocytes can provide information on the hemoglobin concentration and content of reticulocytes and mature erythrocytes. Such parameters have proven clinical utility in anemia diagnosis and therapy monitoring. For interpretation, reliable reference ranges are needed. The aim of this study was to establish reference intervals for extended erythrocyte and reticulocyte parameters as measured with the Abbott CELL-DYN Sapphire hematology analyzer. Secondary aims were to study sample stability and to investigate gender- and age dependency of the reference ranges. Methods: Extended RBC parameters were measured in routine samples of a primary health care laboratory. The study cohort included 8161 samples of unique individuals, which were analyzed using Bhattacharya statistics. As a comparison, reference intervals were calculated in a subset of individuals without iron depletion. Results: The majority of erythrocyte and reticulocyte para\xadmeters were normally distributed, allowing calculation of reference intervals. Only for hypo- and hyperchromic erythrocytes non-parametric statistics had to be used. The reference range for mean cellular hemoglobin content of reticulocytes (MCHr) was 28.5–34.5 pg (1.77–2.14 fmol) in the entire study group and 26.0–35.1 pg (1.60–2.17 fmol) in the non iron-depleted subgroup. No differences between sexes were found. Most parameters showed significant age effects in children and adolescents. Conclusions: Reference intervals have been established for extended RBC and reticulocyte parameters for the CELL-DYN Sapphire. Gender effects could not be demonstrated and age effects were of limited size, except for individuals younger than 18 years. Extended RBC parameters are stable for at least 6 h after blood collection.

Background: Haematological assessment is crucial for evaluating athletes healthy status. Professional athletes experience physiological modifications during competitions and over a season: the risk of sports anaemia is high. Few descriptions of haematological parameters behaviour during a 3-weeks cycling stage race have been published. Methods: We studied nine professional cyclists engaged in the 2011 Giro d’Italia stage race. Pre-analytical and analytical phases tightly followed academic and anti-doping authorities’ recommendations. Haematological and iron metabolism parameters were measured days -1 (pre-race), 12 and 22 during the race. Results: Haemoglobin, red blood cells and haematocrit decreased during the race with a stabilisation in the second half, but final values were lower than baseline. Reticulocytes did not modify, whilst the immature reticulocyte fraction increased. No differences were found in red blood cells volume and corpuscular haemoglobin content, neither in iron metabolism markers. The acute phase proteins, haptoglobin and C-reactive protein, both increased over the race, while haemoglobin and haptoglobin were inversely related. Conclusions: These data are important for improving the knowledge of physiological modifications in haematological and iron metabolism parameters of professional athletes during highly demanding competitions. This is the first report, in the ambit of a stage race, in which the pre-analytical phase standardisation has been applied.

Background: Lens culinaris agglutinin-reactive α-fetoprotein (AFP-L3) and des-γ-carboxy prothrombin (DCP) have been routinely used as serological tumor markers of hepatocellular carcinoma (HCC) for surveillance. The aims of this study were: (i) to determine the biological variation of AFP-L3 and DCP in patients with chronic hepatitis C; and (ii) to calculate the reference change values (RCVs) of AFP-L3 and DCP. Methods: Ten patients with cirrhosis due to hepatitis C virus (HCV) infection and without HCC were enrolled in the study. Serum samples were collected at 14-day intervals, and 10 samples in total were obtained for each patient. AFP-L3 and DCP levels were measured by microchip capillary electrophoresis and liquid-phase binding assay. Intra-individual (CV I ) and inter-individual (CV G ) biological variations and RCVs were estimated from the data generated. Results: The CV I was 29.0% for AFP-L3 and 24.6% for DCP, and CV G was 63.5% for AFP-L3 and 40.4% for DCP. The RCVs for AFP-L3 and DCP were 68.3% and 58.5%, respectively. Conclusions: Increases in values for AFP-L3 and DCP within 68.3% and 58.5% may be biological variations. Clinician should take these variations into consideration for the management of patients with HCV infection under surveillance of HCC.