Biological variation of inflammatory and iron metabolism markers in high-endurance recreational athletes; are these markers useful for athlete monitoring?

OBJECTIVES: To deliver biological variation (BV) data for serum hepcidin, soluble transferrin receptor (sTfR), erythropoietin (EPO) and interleukin 6 (IL-6) in a population of well-characterized high-endurance athletes, and to evaluate the potential influence of exercise and health-related factors on the BV. METHODS: Thirty triathletes (15 females) were sampled monthly (11 months). All samples were analyzed in duplicate and BV estimates were delivered by Bayesian and ANOVA methods. A linear mixed model was applied to study the effect of factors related to exercise, health, and sampling intervals on the BV estimates. RESULTS: Within-subject BV estimates (CVI) were for hepcidin 51.9 % (95 % credibility interval 46.9-58.1), sTfR 10.3 % (8.8-12) and EPO 27.3 % (24.8-30.3). The mean concentrations were significantly different between sex, but CVI estimates were similar and not influenced by exercise, health-related factors, or sampling intervals. The data were homogeneously distributed for EPO but not for hepcidin or sTfR. IL-6 results were mostly below the limit of detection. Factors related to exercise, health, and sampling intervals did not influence the BV estimates. CONCLUSIONS: This study provides, for the first time, BV data for EPO, derived from a cohort of well-characterized endurance athletes and indicates that EPO is a good candidate for athlete follow-up. The application of the Bayesian method to deliver BV data illustrates that for hepcidin and sTfR, BV data are heterogeneously distributed and using a mean BV estimate may not be appropriate when using BV data for laboratory and clinical applications.

Where is laboratory medicine headed in the next decade? Partnership model for efficient integration and adoption of artificial intelligence into medical laboratories.

OBJECTIVES: The field of artificial intelligence (AI) has grown in the past 10 years. Despite the crucial role of laboratory diagnostics in clinical decision-making, we found that the majority of AI studies focus on surgery, radiology, and oncology, and there is little attention given to AI integration into laboratory medicine. METHODS: We dedicated a session at the 3rd annual European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) strategic conference in 2022 to the topic of AI in the laboratory of the future. The speakers collaborated on generating a concise summary of the content that is presented in this paper. RESULTS: The five key messages are (1) Laboratory specialists and technicians will continue to improve the analytical portfolio, diagnostic quality and laboratory turnaround times; (2) The modularized nature of laboratory processes is amenable to AI solutions; (3) Laboratory sub-specialization continues and from test selection to interpretation, tasks increase in complexity; (4) Expertise in AI implementation and partnerships with industry will emerge as a professional competency and require novel educational strategies for broad implementation; and (5) regulatory frameworks and guidances have to be adopted to new computational paradigms. CONCLUSIONS: In summary, the speakers opine that the ability to convert the value-proposition of AI in the laboratory will rely heavily on hands-on expertise and well designed quality improvement initiative from within laboratory for improved patient care.

Critical review and meta-analysis of biological variation estimates for tumor markers.

OBJECTIVES: Biological variation data (BV) can be used for different applications, but this depends on the availability of robust and relevant BV data. In this study, we aimed to summarize and appraise BV studies for tumor markers, to examine the influence of study population characteristics and concentrations on BV estimates and to discuss the applicability of BV data for tumor markers in clinical practice. METHODS: Studies reporting BV data for tumor markers related to gastrointestinal, prostate, breast, ovarian, haematological, lung, and dermatological cancers were identified by a systematic literature search. Relevant studies were evaluated by the Biological Variation Data Critical Appraisal Checklist (BIVAC) and meta-analyses were performed for BIVAC compliant studies to deliver global estimates of within-subject (CVI) and between-subject (CVG) BV with 95% CI. RESULTS: The systematic review identified 49 studies delivering results for 22 tumor markers; four papers received BIVAC grade A, 3 B, 27 C and 15 D. Out of these, 29 CVI and 29 CVG estimates met the criteria to be included in the meta-analysis. Robust data are lacking to conclude on the relationship between BV and different disease states and tumor marker concentrations. CONCLUSIONS: This review identifies a lack of high-quality BV studies for many tumor markers and a need for delivery of BIVAC compliant studies, including in different disease states and tumor marker concentrations. As of yet, the state-of-the-art may still be the most appropriate model to establish analytical performance specifications for the majority of tumor markers.

Within- and between-subject biological variation data for tumor markers based on the European Biological Variation Study.

OBJECTIVES: Reliable biological variation (BV) data are required for the clinical use of tumor markers in the diagnosis and monitoring of treatment effects in cancer. The European Biological Variation Study (EuBIVAS) was established by the EFLM Biological Variation Working Group to deliver BV data for clinically important measurands. In this study, EuBIVAS-based BV estimates are provided for cancer antigen (CA) 125, CA 15-3, CA 19-9, carcinoembryonic antigen, cytokeratin-19 fragment, alpha-fetoprotein and human epididymis protein 4. METHODS: Subjects from five European countries were enrolled in the study, and weekly samples were collected from 91 healthy individuals (53 females and 38 males; 21-69 years old) for 10 consecutive weeks. All samples were analyzed in duplicate within a single run. After excluding outliers and homogeneity analysis, the BVs of tumor markers were determined by CV-ANOVA on trend-corrected data, when relevant (Røraas method). RESULTS: Marked individuality was found for all tumor markers. CYFRA 21-1 was the measurand with the highest index of individuality (II) at 0.67, whereas CA 19-9 had the lowest II at 0.07. The CV I s of HE4, CYFRA 21-1, CA 19-9, CA 125 and CA 15-3 of pre- and postmenopausal females were significantly different from each other. CONCLUSIONS: This study provides updated BV estimates for several tumor markers, and the findings indicate that marked individuality is characteristic. The use of reference change values should be considered when monitoring treatment of patients by means of tumor markers.

Critical appraisal and meta-analysis of biological variation estimates for kidney related analytes.

OBJECTIVES: Kidney markers are some of the most frequently used laboratory tests in patient care, and correct clinical decision making depends upon knowledge and correct application of biological variation (BV) data. The aim of this study was to review available BV data and to provide updated BV estimates for the following kidney markers in serum and plasma; albumin, creatinine, cystatin C, chloride, potassium, sodium and urea. CONTENT: Relevant studies were identified from a historical BV database as well as by systematic literature searches. Retrieved publications were appraised by the Biological Variation Data Critical Appraisal Checklist (BIVAC). Meta-analyses of BIVAC compliant studies with similar design were performed to deliver global estimates of within-subject (CVI) and between-subject (CVG) BV estimates. Out of the 61 identified papers, three received a BIVAC grade A, four grade B, 48 grade C, five grade D grade and one was not appraised as it did not report numerical BV estimates. Most studies were identified for creatinine (n=48). BV estimates derived from the meta-analysis were in general lower than previously reported estimates for all analytes except urea. For some measurands, BV estimates may be influenced by age or states of health, but further data are required. SUMMARY: This review provides updated global BV estimates for kidney related measurands. For all measurands except for urea, these estimates were lower than previously reported. OUTLOOK: For the measurands analyzed in this review, there are sufficient well-designed studies available to publish a trustworthy estimate of BV. However, for a number of newly appearing kidney markers no suitable data is available and additional studies are required.

The multicenter European Biological Variation Study (EuBIVAS): a new glance provided by the Principal Component Analysis (PCA), a machine learning unsupervised algorithms, based on the basic metabolic panel linked measurands.

OBJECTIVES: The European Biological Variation Study (EuBIVAS), which includes 91 healthy volunteers from five European countries, estimated high-quality biological variation (BV) data for several measurands. Previous EuBIVAS papers reported no significant differences among laboratories/population; however, they were focused on specific set of measurands, without a comprehensive general look. The aim of this paper is to evaluate the homogeneity of EuBIVAS data considering multivariate information applying the Principal Component Analysis (PCA), a machine learning unsupervised algorithm. METHODS: The EuBIVAS data for 13 basic metabolic panel linked measurands (glucose, albumin, total protein, electrolytes, urea, total bilirubin, creatinine, phosphatase alkaline, aminotransferases), age, sex, menopause, body mass index (BMI), country, alcohol, smoking habits, and physical activity, have been used to generate three databases developed using the traditional univariate and the multivariate Elliptic Envelope approaches to detect outliers, and different missing-value imputations. Two matrix of data for each database, reporting both mean values, and "within-person BV" (CVP) values for any measurand/subject, were analyzed using PCA. RESULTS: A clear clustering between males and females mean values has been identified, where the menopausal females are closer to the males. Data interpretations for the three databases are similar. No significant differences for both mean and CVPs values, for countries, alcohol, smoking habits, BMI and physical activity, have been found. CONCLUSIONS: The absence of meaningful differences among countries confirms the EuBIVAS sample homogeneity and that the obtained data are widely applicable to deliver APS. Our data suggest that the use of PCA and the multivariate approach may be used to detect outliers, although further studies are required.

The European Biological Variation Study (EuBIVAS): a summary report.

Biological variation (BV) data have many important applications in laboratory medicine. Concerns about quality of published BV data led the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) 1st Strategic Conference to indicate need for new studies to generate BV estimates of required quality. In response, the EFLM Working Group on BV delivered the multicenter European Biological Variation Study (EuBIVAS). This review summarises the EuBIVAS and its outcomes. Serum/plasma samples were taken from 91 ostensibly healthy individuals for 10 consecutive weeks at 6 European centres. Analysis was performed by Siemens ADVIA 2400 (clinical chemistry), Cobas Roche 8000, c702 and e801 (proteins and tumor markers/hormones respectively), ACL Top 750 (coagulation parameters), and IDS iSYS or DiaSorin Liaison (bone biomarkers). A strict preanalytical and analytical protocol was applied. To determine BV estimates with 95% CI, CV-ANOVA after analysis of outliers, homogeneity and trend analysis or a Bayesian model was applied. EuBIVAS has so far delivered BV estimates for 80 different measurands. Estimates for 10 measurands (non-HDL cholesterol, S100-ß protein, neuron-specific enolase, soluble transferrin receptor, intact fibroblast growth-factor-23, uncarboxylated-unphosphorylated matrix-Gla protein, human epididymis protein-4, free, conjugated and %free prostate-specific antigen), prior to EuBIVAS, have not been available. BV data for creatinine and troponin I were obtained using two analytical methods in each case. The EuBIVAS has delivered high-quality BV data for a wide range of measurands. The BV estimates are for many measurands lower than those previously reported, having an impact on the derived analytical performance specifications and reference change values.

Prevalence of metabolic syndrome among patients with schizophrenia in Ethiopia.

BACKGROUND: Globally, the prevalence of metabolic syndrome (MetS) is higher among patients with schizophrenia than the general population, and this leads to higher morbidity and mortality in this population. The aim of this study was to investigate the MetS prevalence among patients with schizophrenia in Ethiopia. METHODS: We conducted a cross-sectional analysis of baseline data of 200 patients with schizophrenia recruited from Amanuel Mental Specialized Hospital, Addis Ababa, Ethiopia. Lipid profile and blood glucose levels were measured using Roche Cobas 6000 clinical chemistry analyzer. The prevalence of MetS was assessed based on National Cholesterol Education Program Adult Treatment Panel III criteria. Patients' demographic information, clinical and laboratory data, lifestyle habits, particularly smoking and Khat chewing, were evaluated vis-à-vis MetS. RESULTS: The overall prevalence of MetS in patients with schizophrenia was 21.5% (17.1% male, 29.6% female) where Low HDL-cholesterol value was the most common metabolic disorders components in both males and females subgroups. In the multivariate analysis, the positive and negative symptoms score (PANSS, AOR = 1.03, 95% CI 1.001-1.054) was associated factors with MetS. CONCLUSION: In Ethiopia, patients with schizophrenia were found to have higher prevalence of MetS than the general population. Physicians/health care providers should routinely screen patients with schizophrenia for MetS and initiate timely management of those who develop the syndrome to reduce the health cost from caring for NCDs, improve the patients' quality of life, and prevent premature mortality.

Routine blood tests as an active surveillance to monitor COVID-19 prevalence. A retrospective study.

BACKGROUND: In Italy, one of the country most affected by the COVID-19 pandemic, the first autochthonous case appeared in Lombardy on February 20th, 2020. One month later, the number of -COVID-19 patients in Lombardy exceeded 17000 and about 3500 had died. Because of this rapid increase in infected people scientists wonder whether SARS-CoV-2 was already highly circulating in Lombardy before such date. Plasma levels of aspartate aminotransferase (AST) and lactate dehydrogenase (LDH) were shown to be -highly increased in COVID-19 patients. Monitoring their levels in Emergency Room patients during the months preceding February 20th, 2020, might shade light on the prevalence of the disease in the pre-COVID-19 period. METHODS: We retrospectively analyzed the AST and LDH levels from more than 30.000 patients admitted to the San Raffaele Hospital Emergency Room (ER) between September 2019 and May 2020 as well as between September 2018 and May 2019. The number of patients diagnosed with respiratory tract diseases were also analyzed. RESULTS: Data showed that the ER averaged AST and LDH levels are highly sensitive to the presence of COVID-19 patients. During, the months preceding February 20th, 2020, AST and LDH levels, as well as the number of patients diagnosed with respiratory tract diseases were similar to their 2019 counterparts. CONCLUSIONS: No significant evidence showing that a large number of COVID-19 patients were admitted to the San Raffaele Hospital ER before February 20th, 2020, was found. Thus, the virus was likely circulating, within the Hospital catchment area, either in low amounts or through asymptomatic individuals. Because of the high LDH and AST levels' variations induced by COVID-19, routine blood tests might be exploited as a surveillance indicator for a possible second wave.

European Biological Variation Study (EuBIVAS): Within- and Between-Subject Biological Variation Data for 15 Frequently Measured Proteins.

BACKGROUND: The European Biological Variation Study (EuBIVAS) was established to deliver rigorously determined data for biological variation (BV). Here, EuBIVAS-based BV estimates are provided for α1-acid glycoprotein, α1-antitrypsin, albumin, ß2-microglobulin, ceruloplasmin, complement component 3, complement component 4, C-reactive protein (CRP), cystatin C, haptoglobin, IgA, IgG, IgM, soluble transferrin receptor (sTfR), and transferrin (Trf), together with their associated analytical performance specifications (APSs) and reference change values (RCVs). METHOD: Serum samples from weekly blood samplings of 91 healthy study participants (38 males and 53 females, ages 21-69 years old) over 10 consecutive weeks in 6 European laboratories were stored at -80 °C before duplicate analysis on a Roche Cobas c702. Outlier and variance homogeneity analyses were performed followed by CV-ANOVA on trend-corrected data if relevant, to determine BV and analytical variation estimates with CI and the associated RCV. RESULTS: For the acute phase proteins, several participants experienced mild inflammatory episodes during the study, requiring exclusion of 7% of the 25290 results. Within-subject BV (CVI) estimates for specific proteins obtained in our study were lower than those available in the online 2014 BV database, except for Trf, whereas between-subject BV (CVG) estimates were similar. CVI and CVG estimates for sTfR, which have not previously been published, were 6.0% and 19.1%, respectively. CONCLUSIONS: In addition to new BV estimates for sTfR, this EuBIVAS substudy generated more demanding APS for frequently requested plasma specific proteins. APS for CRP should not be calculated from BV data except when CRP is used as a risk factor for cardiovascular disease.

Biological variation estimates for prostate specific antigen from the European Biological Variation Study; consequences for diagnosis and monitoring of prostate cancer.

BACKGROUND: Prostate-specific antigen (PSA) is central in the diagnosis of prostate cancer. However, high-quality biological variation (BV) estimates for PSA are scarce. Here BV estimates from the European Biological Variation Study (EuBIVAS) for total (tPSA), free (fPSA), conjugated PSA (cPSA), and percent free PSA (%fPSA) are provided. METHOD: EuBIVAS samples were collected weekly from thirty-seven healthy males (22-59 years) for 10 weeks. All samples, stored at -80 °C, were measured in duplicate with a Roche Cobas e801. Outlier and homogeneity analysis were performed followed by CV-ANOVA to determine BV, analytical variation, analytical performance specifications (APS), reference change values (RCV) and the number of samples required to estimate the homeostatic set points. RESULTS: Within-subject BV estimates were for tPSA 6.8% (6.1-7.4); fPSA 7.1% (6.5-7.7) cPSA: 8.8% (8.0-9.7) and %fPSA 5.3% (4.8-5.8), delivering RCV for increase of 15-20% and indicating that one sample is sufficient to estimate the homeostatic set points within ±15%. BV estimates for tPSA were lower than previously published estimates. Estimates for fPSA, cPSA and %fPSA have not previously been reported in healthy subjects. CONCLUSIONS: Highly powered EuBIVAS BV estimates of tPSA, fPSA, cPSA and %fPSA provide updated APS and RCV for monitoring for prostate cancer.

Within-subject and between-subject biological variation estimates of 21 hematological parameters in 30 healthy subjects.

BACKGROUND: The complete blood count (CBC) is used to evaluate health status in the contexts of various clinical situations such as anemia, infection, inflammation, trauma, malignancies, etc. To ensure safe clinical application of the CBC, reliable biological variation (BV) data are required. The study aim was to define the BVs of CBC parameters employing a strict protocol. METHODS: Blood samples, drawn from 30 healthy subjects (17 females, 13 males) once weekly for 10 weeks, were analyzed using a Sysmex XN 3000 instrument. The data were assessed for normality, trends, outliers and variance homogeneity prior to coefficient of variation (CV)-analysis of variance (ANOVA). Sex-stratified within-subject (CVI) and between-subjects (CVG) BV estimates were determined for 21 CBC parameters. RESULTS: For leukocyte parameters, with the exception of lymphocytes and basophils, significant differences were found between female/male CVI estimates. The mean values of all erythrocyte-, reticulocyte- and platelet parameters differed significantly between the sexes, except for mean corpuscular hemoglobin concentration, mean corpuscular volume and platelet numbers. Most CVI and CVG estimates appear to be lower than those previously published. CONCLUSIONS: Our study, based on a rigorous protocol, provides updated and more stringent BV estimates for CBC parameters. Sex stratification of data is necessary when exploring the significance of changes in consecutive results and when setting analytical performance specifications.

Short- and medium-term biological variation estimates of leukocytes extended to differential count and morphology-structural parameters (cell population data) in blood samples obtained from healthy people.

BACKGROUND: Recent studies showed that some cell population data (CPD) parameters of neutrophils may be useful for diagnosing myelodysplastic syndromes and sepsis, for the differential diagnosis of acute promyelocytic leukemia, and some CPD parameters of lymphocytes may be a valuable tool for preliminary screening of B cell lymphoproliferative disease. Notwithstanding the knowledge, no information has been made available about their analytical quality specification. This study was aimed to define short- and medium-term biological variation (BV) estimates and reference change value (RCV) of leukocyte count, extended leukocyte differential and CPD. METHODS: The study population consisted of 43 healthy volunteers, who participated in the assessment of medium-term (21 volunteers; blood sampling once a week for 5 consecutive weeks) and short-term (22 volunteers; blood sampling once a day for 5 consecutive days) BV, using Sysmex XN. Outlier analysis was carried out before CV-ANOVA, to determine BV estimates and their confidence intervals. RESULTS: The medium-term and short-term within-subject BV (CVI) was comprised between 0.6-19.7% and 0.2-21.9%, whereas the medium-term and short-term between-subjects BV (CVG) was comprised between 1.2-61.5% and 1.1-58.5%. The RCVs were found to be similar for all the parameters, in both arms of the study, except for some CPD parameters. CONCLUSION: This study allowed accurately estimating the BV of many leukocyte parameters, some of which have not been currently explored. The kinetics of some leukocyte turnover suggests the use of short-term BV data for calculating analytical goals and RCV.