Search

Background Hematological parameters have many applications in athletes, from monitoring health to uncovering blood doping. This study aimed to deliver biological variation (BV) estimates for 9 hematological parameters by a Biological Variation Data Critical Appraisal Checklist (BIVAC) design in a population of recreational endurance athletes and to assess the effect of self-reported exercise and health-related variables on BV. Methods Samples were drawn from 30 triathletes monthly for 11 months and measured in duplicate for hematological measurands on an Advia 2120 analyzer (Siemens Healthineers). After outlier and homogeneity analysis, within-subject (CVI) and between-subject (CVG) BV estimates were delivered (CV-ANOVA and log-ANOVA, respectively) and a linear mixed model was applied to analyze the effect of exercise and other related variables on the BV estimates. Results CVI estimates ranged from 1.3% (95%CI, 1.2-1.4) for mean corpuscular volume to 23.8% (95%CI, 21.6-26.3) for reticulocytes. Sex differences were observed for platelets and OFF-score. The CVI estimates were higher than those reported for the general population based on meta-analysis of eligible studies in the European Biological Variation Database, but 95%CI overlapped, except for reticulocytes, 23.9% (95%CI, 21.6-26.5) and 9.7% (95%CI, 6.4-11.0), respectively. Factors related to exercise and athletes’ state of health did not appear to influence the BV estimates. Conclusions This is the first BIVAC-compliant study delivering BV estimates that can be applied to athlete populations performing high-level aerobic exercise. CVI estimates of most parameters were similar to the general population and were not influenced by exercise or athletes’ state of health.

In vitro diagnostics (IVD) testing is a powerful tool for medical diagnosis, and patients‘ safety is guaranteed by a complex system of personnel qualification of the specialist in laboratory medicine, of process control, and legal restrictions in healthcare, most of them under national regulation. Direct-to-consumer laboratory testing (DTCT) is testing ordered by the consumer and performed either by the consumer at home or analysis of self-collected samples in a laboratory. However, since DTCT are not always subject to effective competent authority oversight, DTCT may pose risks to lay persons using and relying on it for healthcare decision-making. Laboratory medicine specialists should be very cautious when new DTCTs are introduced. As qualified professionals, they should feel obliged to warn and educate patients and the public about the risks of inappropriate and harmful DTCT.

Objectives Accurate prothrombin time international normalized ratio (INR) results are essential for safe anticoagulation treatment. Patients are treated both in primary and secondary healthcare, therefore equivalence of INR results from point-of-care (POC) and hospital measurement procedures (MPs) are important. It is not possible to evaluate this equivalence in traditional external quality assessment (EQA). The aim of this paper is to describe a special quality assurance system consisting of three different EQA schemes to monitor the harmonization of INR results in Norway. Methods The EQA scheme for hospital laboratories uses commutable control materials and evaluates participant performance and the equivalence of hospital MPs. The EQA scheme for primary healthcare laboratories uses non-commutable control materials and evaluates participant performance. A third EQA scheme for selected primary healthcare laboratories uses native patient split samples and evaluates the equivalence between POC and hospital MPs. Results The relationship between the three EQA schemes is presented. The split sample EQA scheme provides a link between the hospital scheme and the scheme for primary healthcare. Results from 2017 to 2022 are presented for all three schemes. When aberrant EQA results occur Noklus takes actions to be able to have a sustainable equivalence between INR results. Conclusions All three EQA schemes are important for monitoring the harmonization of INR results in Norway. This quality assurance system, including help and guidance of the participants, will reduce the risk of harm to patients due to non-equivalence of results from different MPs.

Objectives An external quality control program distributes same control samples to various laboratories and evaluates results obtained with a common criterion. The aim of this work is to summarize the evolution of various types of external programs, to point out the progresses ant to preclude practical consequences of the participant laboratories. Content The material consists on a brief revision of the different types of external programs that have been used for the last forty years. The method is the critical analysis of the strong and weak points of each program model, from the light of our experience. External quality assessment (EQA) programs were initiated at half the XX century, evidencing big discrepancies among laboratory results. EQA were developed in various countries and some mechanisms to harmonize them were proposed: to establish common performance specifications derived from biological variation, to use EQS as educational tool. Since the 2000 important advances were seen: to focus EQA to assure the adequate clinical use of laboratory tests, to use commutable controls, to harmonize the different EQA models, to promote a forum for co-operation and exchange of knowledge on quality-related matters for EQA organizers. Summary and Outlook To participate in an EQA with commutable-reference method assigned values controls allows to know the real inaccuracy of results and their impact on patient’ samples. To participate in a EQA with non commutable controls allows to know whether the individual laboratory performance agrees with that from other laboratories using same analytical method.

Resumen Objectivos Un programa de control externo distribuye las mismas muestras control entre varios laboratorios y evalúa los resultados obtenidos con un criterio común. El objetivo de este trabajo es resumir la evolución de los programas externos, poner de manifiesto los progresos conseguidos y deducir consecuencias prácticas para el laboratorio participante. Métodos El material es una breve revisión de los diferentes tipos de programas externos utilizados a lo largo de cuarenta años. El método es el análisis crítico de las ventajas e inconvenientes de cada modelo, a la luz de nuestra experiencia. Resultados A mitad del siglo XX se iniciaron los programas EQA, detectándose gran discrepancia entre resultados emitidos por distintos laboratorios. Se desarrollaron EQA en muchos países y se propusieron mecanismos para armonizarlos, como: establecer especificaciones derivadas de la variación biológica, promover el uso de métodos analíticos homogéneos, usar el EQA como herramienta educacional. A partir del 2000 se hacen importantes avances: asegurar el adecuado uso clínico de las pruebas del laboratorio, utilizar material control conmutable con el espécimen humano, armonizar los distintos modelos de EQA, promover una organización de cooperación entre organizadores de programas EQA. Conclusiones Participar en un EQA con controles conmutables y valores asignados por método de referencia certificado permite conocer la inexactitud real de los resultados y el impacto en las muestras de pacientes. Si se participa en programas con controles no conmutables solo se conoce si la prestación del laboratorio es similar a la de otros usuarios del mismo método analítico.

Using laboratory test results for diagnosis and monitoring requires a reliable reference to which the results can be compared. Currently, most reference data is derived from the population, and patients in this context are considered members of a population group rather than individuals. However, such reference data has limitations when used as the reference for an individual. A patient's test results preferably should be compared with their own, individualized reference intervals (RI), i.e. a personalized RI (prRI).The prRI is based on the homeostatic model and can be calculated using an individual's previous test results obtained in a steady-state situation and estimates of analytical (CV

Lot-to-lot verification is an important laboratory activity that is performed to monitor the consistency of analytical performance over time. In this opinion paper, the concept, clinical impact, challenges and potential solutions for lot-to-lot verification are exained.

Analytical performance specifications (APS) for measurands describe the minimum analytical quality requirements for their measurement. These APS are used to monitor and contain the systematic (trueness/ bias) and random errors (precision/ imprecision) of a laboratory measurement to ensure the results are “fit for purpose” in informing clinical decisions about managing a patient’s health condition. In this review, we highlighted the wide variation in the setting of APS, using different levels of evidence, as recommended by the Milan Consensus, and approaches. The setting of a priori defined outcome-based APS for HbA1c remains challenging. Promising indirect alternatives seek to link the clinical utility of HbA1c and APS by defining statistical confidence for interpreting the laboratory values, or through simulation of clinical performance at varying levels of analytical performance. APS defined based on biological variation estimates in healthy individuals using the current formulae are unachievable by nearly all routine laboratory methods for HbA1c testing. On the other hand, the APS employed in external quality assurance programs have been progressively tightened, and greatly facilitate the improved quality of HbA1c testing. Laboratories should select the APS that fits their intended clinical use and should document the data and rationale underpinning those selections. Where possible common APS should be adopted across a region or country to facilitate the movement of patients and patient data across health care facilities.

Objectives The diagnosis and monitoring of bleeding and thrombotic disorders depend on correct haemostatic measurements. The availability of high-quality biological variation (BV) data is important in this context. Many studies have reported BV data for these measurands, but results are varied. The present study aims to deliver global within-subject (CVI) and between-subject (CVG) BV estimates for haemostasis measurands by meta-analyses of eligible studies, by assessment with the Biological Variation Data Critical Appraisal Checklist (BIVAC). Methods Relevant BV studies were graded by the BIVAC. Weighted estimates for CVI and CVG were obtained via meta-analysis of the BV data derived from BIVAC-compliant studies (graded A–C; whereby A represents optimal study design) performed in healthy adults. Results In 26 studies BV data were reported for 35 haemostasis measurands. For 9 measurands, only one eligible publication was identified and meta-analysis could not be performed. 74% of the publications were graded as BIVAC C. The CVI and CVG varied extensively between the haemostasis measurands. The highest estimates were observed for PAI-1 antigen (CVI 48.6%; CVG 59.8%) and activity (CVI 34.9%; CVG 90.2%), while the lowest were observed for activated protein C resistance ratio (CVI 1.5%; CVG 4.5%). Conclusions This study provides updated BV estimates of CVI and CVG with 95% confidence intervals for a wide range of haemostasis measurands. These estimates can be used to form the basis for analytical performance specifications for haemostasis tests used in the diagnostic work-up required in bleeding- and thrombosis events and for risk assessment.

Examples of photoluminescence (PL) are being reported with increasing frequency in a wide range of organisms from diverse ecosystems. However, the chemical basis of this PL remains poorly defined, and our understanding of its potential ecological function is still superficial. Amongst mammals, recent analyses have identified free-base porphyrins as the compounds responsible for the reddish ultraviolet-induced photoluminescence (UV-PL) observed in the pelage of springhares and hedgehogs. However, the localization of the pigments within the hair largely remains to be determined. Here we use photoluminescence multispectral imaging emission and excitation spectroscopy to detect, map and characterize porphyrinic compounds in skin appendages in situ. We also document new cases of mammalian UV-PL caused by free-base porphyrins in distantly related species. Spatial distribution of the UV-PL is strongly suggestive of an endogenous origin of the porphyrinic compounds. We argue that reddish UV-PL is predominantly observed in crepuscular and nocturnal mammals because porphyrins are photodegradable. Consequently, this phenomenon may not have a specific function in intra- or interspecific communication but rather represents a byproduct of potentially widespread physiological processes.Co-first authors: Séverine Toussaint and Jasper Ponstein

Objectives Trace elements (TrEL) are nutritionally essential components in maintaining health and preventing diseases. There is a lack of reliable biological variation (BV) data for TrELs, required for the diagnosis and monitoring of TrEL disturbances. In this study, we aimed to provide updated within- and between-subject BV estimates for zinc (Zn), copper (Cu) and selenium (Se). Methods Weekly serum samples were drawn from 68 healthy subjects (36 females and 32 males) for 10 weeks and stored at −80 °C prior to analysis. Serum Zn, Cu and Se levels were measured using inductively-coupled plasma mass spectrometry (ICP-MS). Outlier and variance homogeneity analyses were performed followed by CV-ANOVA (Røraas method) to determine BV and analytical variation estimates with 95% CI and the associated reference change values (RCV) for all subjects, males and females. Results Significant differences in mean concentrations between males and females were observed, with absolute and relative (%) differences for Zn at 0.5 μmol/L (3.5%), Cu 2.0 μmol/L (14.1%) and Se 0.06 μmol/L (6.0%). The within-subject BV (CVI [95% CI]) estimates were 8.8% (8.2–9.3), 7.8% (7.3–8.3) and 7.7% (7.2–8.2) for Zn, Cu and Se, respectively. Within-subject biological variation (CVI) estimates derived for male and female subgroups were similar for all three TrELs. Marked individuality was observed for Cu and Se. Conclusions The data of this study provides updated BV estimates for serum Zn, Cu and Se derived from a stringent protocol and state of the art methodologies. Furthermore, Cu and Se display marked individuality, highlighting that population based reference limits should not be used in the monitoring of patients.

Highlights • Test selection/ evaluation needs a priori defined performance specifications. • At low prevalence, minimal sensitivity is required to achieve NPV of 60%-95%. • At high prevalence, relatively low clinical sensitivity can achieve a desired PPV. • NPV-PPV trade-offs should be weighed based on prevalence, sensitivity, specificity. • A spreadsheet tool is provided for determining these a priori considerations., Objectives Several guidelines for the evaluation of laboratory tests for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection have recommended establishing an a priori definition of minimum clinical performance specifications before test selection and method evaluation. Methods Using positive (PPV) and negative predictive values (NPV), we constructed a spreadsheet tool for determining the minimum clinical specificity (conditional on NPV or PPV, sensitivity and prevalence) and minimum clinical sensitivity (conditional on NPV or PPV, specificity and prevalence) of tests. Results At a prevalence of 1%, there are no minimum sensitivity requirements to achieve a desired NPV of 60%-95% for a given clinical specificity above 20%. It is not possible to achieve 60–95% PPV even with 100% clinical sensitivity, except when the clinical specificity is near 100%. The opposite trend is seen in high prevalence settings (60%), where a relatively low minimum clinical sensitivity is required to achieve a desired PPV for a given clinical specificity, and a higher minimum clinical specificity is required to achieve a desired NPV for a given clinical sensitivity. Discussion The selection of laboratory tests and the testing strategy for SARS-CoV-2 involves delicate trade-offs between NPV and PPV based on prevalence and clinical sensitivity and clinical specificity. Practitioners and health authorities should carefully consider the clinical scenarios under which the test result will be used and select the most appropriate testing strategy that fulfils the a priori defined clinical performance specification.

Background Many studies have assessed the biological variation (BV) of cardiac-specific troponins (cTn), reporting widely varying within-subject BV (CVI) estimates. The aim of this study was to provide meta-analysis-derived BV estimates for troponin I (cTnI) and troponin T (cTnT) for different sampling intervals and states of health. Methods Relevant studies were identified by a systematic literature search. Studies were classified according to their methodological quality by the Biological Variation Data Critical Appraisal Checklist (BIVAC). Meta-analyses of BIVAC-compliant studies were performed after stratification by cTn isoform, exclusion of results below the limit of detection, states of health, and sampling interval to deliver reference change values (RCV), index of individuality (II) and analytical performance specifications (APS) for these settings. Results Sixteen and 15 studies were identified for cTnI and cTnT, respectively, out of which 6 received a BIVAC grade A. Five studies had applied contemporary cTnI assays, but none contemporary cTnT. High-sensitivity (hs-) cTnI and cTnT delivered similar estimates in all settings. Long-term CVI estimates (15.1; 11.3%) derived from healthy individuals were higher than short-term (4.3%; 5.3%) for hs-cTnI and hs-cTnT, respectively, although confidence intervals overlapped. Estimates derived from diseased subjects were similar to estimates in healthy individuals for all settings. Conclusions This study provides robust estimates for hs-cTnI and hs-cTnT applicable for different clinical settings and states of health, allowing for the use of RCV both to aid in the diagnosis of myocardial injury and for prognosis. BV-based APS appear too strict for some currently available technologies.

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.

Objectives Numerous biological variation (BV) studies have been performed over the years, but the quality of these studies vary. The objectives of this study were to perform a systematic review and critical appraisal of BV studies on glycosylated albumin and to deliver updated BV estimates for glucose and HbA1c, including recently published high-quality studies such as the European Biological Variation study (EuBIVAS). Methods Systematic literature searches were performed to identify BV studies. Nine publications not included in a previous review were identified; four for glycosylated albumin, three for glucose, and three for HbA1c. Relevant studies were appraised by the Biological Variation Data Critical Appraisal Checklist (BIVAC). Global BV estimates were derived by meta-analysis of BIVAC-compliant studies in healthy subjects with similar study design. Results One study received BIVAC grade A, 2B, and 6C. In most cases, the C-grade was associated with deficiencies in statistical analysis. BV estimates for glycosylated albumin were: CVI=1.4% (1.2–2.1) and CVG=5.7% (4.7–10.6), whereas estimates for HbA1c, CVI=1.2% (0.3–2.5), CVG=5.4% (3.3–7.3), and glucose, CVI=5.0% (4.1–12.0), CVG=8.1% (2.7–10.8) did not differ from previously published global estimates. Conclusions The critical appraisal and rating of BV studies according to their methodological quality, followed by a meta-analysis, generate robust, and reliable BV estimates. This study delivers updated and evidence-based BV estimates for glycosylated albumin, glucose and HbA1c.

Background It is not clear if point-of-care (POC) testing for hemoglobin A1c (HbA1c) is associated with glycemic control in type 2 diabetes. Methods In this cross-sectional study, we linked general practitioner (GP) data on 22,778 Norwegian type 2 diabetes patients to data from the Norwegian Organization for Quality Improvement of Laboratory Examinations. We used general and generalized linear mixed models to investigate if GP offices’ availability (yes/no) and analytical quality of HbA1c POC testing (average yearly “trueness score”, 0–4), as well as frequency of participation in HbA1c external quality assurance (EQA) surveys, were associated with patients’ HbA1c levels during 2014–2017. Results Twenty-eight out of 393 GP offices (7%) did not perform HbA1c POC testing. After adjusting for confounders, their patients had on average 0.15% higher HbA1c levels (95% confidence interval (0.04–0.27) (1.7 mmol/mol [0.5–2.9]). GP offices participating in one or two yearly HbA1c EQA surveys, rather than the maximum of four, had patients with on average 0.17% higher HbA1c levels (0.06, 0.28) (1.8 mmol/mol [0.6, 3.1]). For each unit increase in the GP offices’ HbA1c POC analytical trueness score, the patients’ HbA1c levels were lower by 0.04% HbA1c (−0.09, −0.001) (−0.5 mmol/mol [−1.0, −0.01]). Conclusions Novel use of validated patient data in combination with laboratory EQA data showed that patients consulting GPs in offices that perform HbA1c POC testing, participate in HbA1c EQA surveys, and maintain good analytical quality have lower HbA1c levels. Accurate HbA1c POC results, available during consultations, may improve diabetes care.

Uncertainty is an inseparable part of all kinds of measurements performed in clinical laboratories. Accreditation standards including the ISO/IEC 17025:2017 and ISO 15189:2012 require that laboratories have routines for calculating the measurement uncertainty of reported results. Various guidelines such as CLSI EP29, Nordest 537, and ISO 20914:2019 have proposed methods for this purpose. However, due to the conceived complexity of the proposed calculation methods, these guidelines have not been generally and effectively applied in clinical laboratories. High workload and measurand heterogeneity favor a pragmatic utilitarian approach. The purpose of this paper is to describe such an approach, including its advantages and disadvantages. Measurement uncertainty should include the most influential factors affecting patients' test results. Since patients' samples for the same measurand can be analyzed in one laboratory or several laboratories using different measuring systems, the measurement uncertainty should be calculated using results obtained from analyzing the same internal quality control material if commutable or patients pooled/split samples.

IntroductionTo study the relationship between education level and vascular complications in individuals with type 2 diabetes in Norway.Research design and methodsMultiregional population-based cross-sectional study of individuals with type 2 diabetes in primary care. Data were extracted from electronic medical records in the period 2012–2014. Information on education level was obtained from Statistics Norway. Using multivariable multilevel regression analyses on imputed data we analyzed the association between education level and vascular complications. We adjusted for age, sex, HbA1c, low-density lipoprotein cholesterol, systolic blood pressure, smoking and diabetes duration. Results are presented as ORs and 95% CIs.ResultsOf 8192 individuals with type 2 diabetes included, 34.0% had completed compulsory education, 49.0% upper secondary education and 16.9% higher education. The prevalence of vascular complications in the three education groups was: coronary heart disease 25.9%, 23.0% and 16.9%; stroke 9.6%, 7.4% and 6.6%; chronic kidney disease (estimated glomerular filtration rate 2) 23.9%, 16.8% and 12.6%; and retinopathy 13.9%, 11.5% and 11.7%, respectively. Higher education was associated with lower odds for coronary heart disease (OR 0.59; 95% CI 0.49 to 0.71) and chronic kidney disease (OR 0.75; 95% CI 0.60 to 0.93) compared with compulsory education when adjusting for age, sex, HbA1c, low-density lipoprotein cholesterol, systolic blood pressure, smoking and diabetes duration.ConclusionsIn a country with equal access to healthcare, high education level was associated with lower odds for coronary heart disease and chronic kidney disease in individuals with type 2 diabetes.

For many measurands, physicians depend on population-based reference intervals (popRI), when assessing laboratory test results. The availability of personalized reference intervals (prRI) may provide a means to improve the interpretation of laboratory test results for an individual. prRI can be calculated using estimates of biological and analytical variation and previous test results obtained in a steady-state situation. In this study, we aim to outline statistical approaches and considerations required when establishing and implementing prRI in clinical practice. Data quality assessment, including analysis for outliers and trends, is required prior to using previous test results to estimate the homeostatic set point. To calculate the prRI limits, two different statistical models based on ‘prediction intervals’ can be applied. The first model utilizes estimates of ‘within-person biological variation’ which are based on an individual’s own data. This model requires a minimum of five previous test results to generate the prRI. The second model is based on estimates of ‘within-subject biological variation’, which represents an average estimate for a population and can be found, for most measurands, in the EFLM Biological Variation Database. This model can be applied also when there are lower numbers of previous test results available. The prRI offers physicians the opportunity to improve interpretation of individuals’ test results, though studies are required to demonstrate if using prRI leads to better clinical outcomes. We recommend that both popRIs and prRIs are included in laboratory reports to aid in evaluating laboratory test results in the follow-up of patients.

Biological variation (BV) data have many applications in laboratory medicine. However, these depend on the availability of relevant and robust BV data fit for purpose. BV data can be obtained through different study designs, both by experimental studies and studies utilizing previously analysed routine results derived from laboratory databases. The different BV applications include using BV data for setting analytical performance specifications, to calculate reference change values, to define the index of individuality and to establish personalized reference intervals. In this review, major achievements in the area of BV from last decade will be presented and discussed. These range from new models and approaches to derive BV data, the delivery of high-quality BV data by the highly powered European Biological Variation Study (EuBIVAS), the Biological Variation Data Critical Appraisal Checklist (BIVAC) and other standards for deriving and reporting BV data, the EFLM Biological Variation Database and new applications of BV data including personalized reference intervals and measurement uncertainty.

Purpose: The ‘Outcomes & Multi-morbidity in Type 2 Diabetes’ (OMIT) is an observational registry-based cohort of Norwegian patients with type 2 diabetes (T2D) established to study high-risk groups often omitted from randomised clinical trials. Participants: The OMIT cohort includes 57 572 patients with T2D identified via linkage of Norwegian Diabetes Register for Adults and the Rogaland-Oslo-Salten-Akershus-Hordaland study, both offering data on clinical patient characteristics and drug prescriptions. Subsequently these data are further linked to the Norwegian Prescription Database for dispensed medications, the Norwegian Population Register for data on death and migration, Statistics Norway for data on socioeconomic factors and ethnicity and the Norwegian Directorate of Health for data on the general practices and clinical procedures involved in the care of cohort patients. OMIT offers large samples for key high-risk patient groups: (1) young-onset diabetes (T2D at age 75 years) (n=15 540), (3) non-Western ethnic minorities (n=9000) and (4) low socioeconomic status (n=20 500). Findings to date: On average, patient age and diabetes duration is 67.4±13.2 and 12.3±8.3 years, respectively, and mean HbA1c for the whole cohort through the study period is 7.6%±1.5% (59.4±16.3mmol/mol), mean body mass index (BMI) and blood pressure is 30.2±5.9 kg/m2 and 135±16.1/78±9.8mm Hg, respectively. Prevalence of retinopathy, coronary heart disease and stroke is 10.1%, 21% and 6.7%, respectively. Future plans: The OMIT cohort features 5784 subjects with T2D in 2006, a number that has grown to 57 527 in 2019 and is expected to grow further via repeated linkages performed every third to fifth year. At the next wave of data collection, additional linkages to Norwegian Patient Registry and Norwegian Cause of Death Registry for data on registered diagnoses and causes of death, respectively, will be performed. The first phase of linkages was funded by the University of Oslo. Currently, senior researchers and one postdoctoral position (Western Norway University of Applied Sciences (HVL), Norway) are funded by their home institutions The cohort is also funded by The Norwegian Diabetes Association (Diabetesforbundet) and the Norwegian Research Fund for General Practice (Allmennmedisinsk forskningsfond), with the latter also funding one PhD-student (University of Oslo (UiO), Norway).

Objectives Thyroid biomarkers are fundamental for the diagnosis of thyroid disorders and for the monitoring and treatment of patients with these diseases. The knowledge of biological variation (BV) is important to define analytical performance specifications (APS) and reference change values (RCV). The aim of this study was to deliver BV estimates for thyroid stimulating hormone (TSH), free thyroxine (FT4), free triiodothyronine (FT3), thyroglobulin (TG), and calcitonin (CT). Methods Analyses were performed on serum samples obtained from the European Biological Variation Study population (91 healthy individuals from six European laboratories; 21–69 years) on the Roche Cobas e801 at the San Raffaele Hospital (Milan, Italy). All samples from each individual were evaluated in duplicate within a single run. The BV estimates with 95% CIs were obtained by CV-ANOVA, after analysis of variance homogeneity and outliers. Results The within-subject (CV I ) BV estimates were for TSH 17.7%, FT3 5.0%, FT4 4.8%, TG 10.3, and CT 13.0%, all significantly lower than those reported in the literature. No significant differences were observed for BV estimates between men and women. Conclusions The availability of updated, in the case of CT not previously published, BV estimates for thyroid markers based on the large scale EuBIVAS study allows for refined APS and associated RCV applicable in the diagnosis and management of thyroid and related diseases.

Background: Porphyria cutanea tarda (PCT) is a skin disorder caused by a defect in the liver enzyme uroporphyrinogen decarboxylase and is associated with hepatitis C virus infection, high alcohol intake, smoking and iron overload. Data on the long-term morbidity of PCT is lacking. Methods: We conducted a nationwide matched cohort study over a 24-year period. The study sample included 534 persons aged 18-67 years with a biochemically confirmed PCT diagnosis and a sample of 21,360 persons randomly selected from the working age population, matched on age, sex and educational attainment. We investigated if persons with sporadic and familial PCT had an increased risk of long-term sick leave (LTSL) or disability pension. We further assessed risk before (pre-PCT), during (during-PCT) and after (post-PCT) the typical period of first onset to diagnosis, treatment and remission. Results: Overall, persons with PCT had a 40% increased risk (hazard ratio [HR]=1.4, 95% confidence interval [CI]=1.3, 1.5) of LTSL and a 50% increased risk (HR=1.5, CI=1.3, 1.7) of disability pension. Risk of disability pension was increased pre-PCT (HR=1.3, CI: 1.3 (1.0, 1.6), during-PCT (HR: 1.5, CI: 1.0, 2.2) and post-PCT (HR=2.0, CI: 1.5, 2.6). For LTSL, risk was increased pre-PCT (HR=1.3, CI: 1.1, 1.4) and during-PCT (HR=1.5, CI: 1.1, 2.1), but not post-PCT. Risk was greatest in persons with sporadic than familial PCT. Diagnostic reasons for disability pension that were increased compared to matched controls were PCT or skin disease in 11 of 199 cases (PCT: n=7, incident rate ratios [IRR]=49.2, CI=38.8, 62.4; diseases of the skin & subcutaneous tissue, n=4, IRR=4.2, CI=1.6, 11.0). The vast majority of diagnostic reasons for accessing disability pension were related to comorbidities, PCT susceptibility factors and more general health issues such as: malignant neoplasms (n=12, IRR=2.4, CI=1.4, 4.2), substance and alcohol dependence (n=7, IRR=5.0, CI=2.5, 10.1), neurotic and mood – disorders (n=21, IRR=1.7, CI=1.1, 2.6), and diseases of the musculoskeletal system & connective tissue (n=71, IRR=2.5, CI=1.9, 3.2).Conclusions: Persons with PCT have an increased risk of LTSL and disability pension indicating significant morbidity in this patient group. Appropriate long-term follow-up and monitoring for relapses and co-morbid diseases are recommended.