EndoCompass Project: Endocrine Laboratory Medicine

Abstract

Background

Endocrine science remains underrepresented in European Union research programmes despite the fundamental role of hormone health in human wellbeing. Analysis of the CORDIS database reveals a persistent gap between the societal impact of endocrine disorders and their research prioritization. At national funding level, endocrine societies report limited or little attention of national research funding towards endocrinology. The EndoCompass project – a joint initiative between the European Society of Endocrinology and the European Society of Paediatric Endocrinology, aimed to identify and promote strategic research priorities in endocrine science to address critical hormone-related health challenges.

Methods

Research priorities were established through comprehensive analysis of the EU CORDIS database covering the Horizon 2020 framework period (2014–2020). Expert analysis examined current challenges and opportunities in hormone measurements, focusing on analytical quality, method validation, and emerging technologies to ensure reliable research and clinical care.

Results

Research priorities encompass optimization of pre-analytical processes, standardization and harmonization of endocrine tests, development of personalized reference intervals and clinical decision limits considering diversity, biological variation and environmental factors, innovation in biomarker discovery and point-of-care testing, and implementation of sustainable laboratory practices. Special emphasis is placed on leveraging artificial intelligence and health economics while maintaining analytical quality.

Conclusions

This component of the EndoCompass project provides an evidence-based roadmap for advancing endocrine laboratory medicine. The findings support strategic investment in quality assurance and innovative technologies to enhance both research reliability and clinical outcomes, ultimately improving patient care in endocrine-related diseases.

Significance

The chapter underscores the critical importance of high-quality hormone analyses in endocrinology, emphasizing their role in ensuring reliable research conclusions and accurate clinical interpretations. It highlights the significance of advancements in Endocrine Laboratory Medicine for understanding hormonal interactions, early detection of disorders, and the development of effective treatments. The chapter advocates optimizing endocrine tests through standardization, personalized medicine, and innovative approaches like biomarker discovery and AI integration. Ultimately, these efforts aim to enhance patient care and advance medical science in the realm of endocrine-related diseases.

Introduction

Laboratory Medicine is a clinical science focused on the quantitative measurement or qualitative assessment of substances in biological fluids, such as blood or urine, for medical or research purposes. The results from these tests are crucial for diagnosing, staging, and monitoring diseases, as well as for screening and assessing health and fitness, and for conducting dependable research. Endocrine Laboratory Medicine specifically focuses on the diagnosis, screening, management, and research of disorders related to the endocrine system.

The quality of analyses in endocrinology is challenging but crucial. High-quality analyses ensure the reliability of research conclusions and interpretation of patient results in clinical care. The required quality of analytical and clinical characteristics of measurement methods is fundamental to making informed clinical decisions and advancing medical science [1].

Research in Endocrine Laboratory Medicine is vital for several reasons. First, it enhances our understanding of complex hormonal interactions and their impact on health. This knowledge is essential for developing well performing diagnostic tests and effective treatments. Second, advances in this field can lead to early detection of endocrine disorders, improving patient outcomes and reducing healthcare costs. Additionally, research can uncover new therapeutic targets and innovative treatment strategies. Overall, continued research in Endocrine Laboratory Medicine is fundamental to advancing medical science and improving patient care for endocrine-related diseases.

Current State of Endocrine Laboratory Medicine

Hormone analysis is inherently challenging due to their low concentrations, the heterogenic structure of peptides, and proteins and the complexity of biological matrices. In addition, steroid hormones can be structurally similar, and are frequently bound to proteins, which can complicate, and interfere with accurate measurement.

Various techniques are used to measure hormone concentrations, from bioassays to isotope dilution liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS). Each technique has its own advantages and disadvantages, and not all are suitable for measuring specific hormones in particular bodily fluids or mediums. Currently, the most commonly used techniques are immunoassays and ID-LC-MS/MS [1].

Immunoassays, which depend on antibodies binding to the hormone of interest, encounter challenges due to cross-reactivity and interferences resulting from the presence of other components in the sample. This is particularly problematic for structurally related steroid hormones. For example, testosterone immunoassays can give falsely high results due to cross-reactivity with other steroid hormones, such as dehydroepiandrosterone sulfate (DHEAS). LC-MS/MS is generally superior for steroid hormone analysis because it offers high specificity [2]. Other advantages of LC-MS/MS include the ability to measure multiple hormones in a single run, matrix independence, and the requirement of less sample volume. However, LC-MS/MS implementation requires highly skilled staff and expensive equipment.

For peptide hormones and proteins, immunoassays are still the most frequently used method, though LC-MS/MS methods are being developed. As peptides and proteins are large molecular weight compounds, antibodies raised for the use in immunoassays can be more specific and multiple antigens allow the use of an immunometric (sandwich) principle. Immunoassays for these hormones therefore suffer less from cross-reactivity. However, discrepancies can still occur, such as with common protein variants that are detected by some immunoassays but not by LC-MS/MS.

The choice of technique, immunoassay or LC-MS/MS, depends on the specific requirements of a research study and the patient population and expertise of the laboratory [1]. The inherent difficulties in measuring hormones highlight the importance of selecting the appropriate method and ensuring rigorous quality control to obtain accurate and reliable results.

Laboratories can use hormone assay kits produced by manufacturers or develop their own measurement methods. Manufacturers often suggest that performing hormone analyses is straightforward: simply buy the kit, read the manual, and perform the analyses. These kits come with internal quality control samples, implying guaranteed quality. However, this does not ensure high-quality measurements. Especially, when hormone measurement methods (kits, assays, reagents, tests) are intended to be used with a specific medical purpose, it is defined as an in vitro medical device (IVD). Clinical laboratories develop and maintain a quality management system according to ISO15189 (the international standard that specifies requirements for quality and competence in medical laboratories) to ensure the quality and competence necessary for the use of IVDs in patient care. Each new assay used in a laboratory should undergo on-site verification, a common practice in ISO15189 accredited diagnostic laboratories, which should also apply to analyses for scientific studies. In-house developed IVDs (IH-IVD) should be extensively validated. Some of the key challenges and future research directions in Endocrine Laboratory Medicine are described below.

Key Challenges

Pre-Analysis

In addition to the actual technical analysis of the hormone, the appropriate collection and handling of the specimen is of utmost importance for correct subsequent analysis and interpretation of the results. For instance, many hormones such as cortisol and testosterone have a diurnal rhythm and the time of sample collection is relevant for the obtained measurement result and interpretation compared to reference interval (RI) and/or clinical decision limit (CDL). The hormone concentration may also depend on the fasting state. Dietary constituents, including dietary supplements, may affect physiological systems and complicate interpretation of hormone measurements, for instance, catecholamine-rich food on normetanephrine and 3-methoxytyramine in urine [3], salt intake before measurement of renin and aldosterone [4] or in general the effect of food intake such as in the case for the bone marker carboxy-terminal telopeptide of type I collagen (CTX-I) or hormones regulating food intake and satiety, such as ghrelin and leptin [5, 6]. Many medications including oral contraceptives influence physiological systems and thereby have an effect on measurement results [7]. Sometimes these effects are desired, such as in dynamic testing but the clinical protocol of these dynamic tests may not be standardized as such to guarantee unambiguous result interpretation. Also the patient posture before and during sample collection may be of importance. This is the case for renin and aldosterone [8]. Obviously, the type of specimen (blood, saliva, urine) has a profound influence on expected hormone levels and also specimen collection anatomical site may be of importance. Notably, a sample collected by venipuncture of the median cubital vein in the arm or specifically from a particular endocrine gland may be crucial for the measurement result and interpretation. This is for instance the case for peripheral venous sampling for ACTH compared to inferior petrosal sinus sampling for measurement of ACTH but also for PTH in case of transplanted parathyroid tissue.

Hormones may have limited stability following specimen collection, transport, and storage. These are often temperature-, time-, and matrix dependent [1]. Proper measures may be necessary to restrain the degradation by for instance timely processing, immediate temperature control, or/and the use of antioxidants or protease inhibitors in collection tubes.

Precision along the Clinically Relevant Measurement Range and Interferences

An important quality feature of a measurement method is imprecision, which is the variation in results of replicate measurements on the same or similar specimens and usually expressed as a standard deviation or coefficient of variation (CV). The development of measurement methods and techniques with low analytical variation is important for correct clinical interpretation of measurement results, as the measurement uncertainty has an influence on how the measurement result can be interpreted when compared to CDLs or RIs or between consecutive obtained specimens for the monitoring of disease and health status. Indeed, to conclude that there is a significant difference between the results of two consecutive specimens, the biological variation of the substance within the person (CVw), as well as the analytical variation (CVa) contributes to the difference. It is only when both biological variation and the analytical variation is exceeded, the critical value, or reference change value (RCV = 2^1/2 *Z*(CVa² + CVw²)^1/2) that the difference between the results of consecutive samples is unlikely due to random variation [9].

A thorough understanding of biological variation is therefore important, as well as the effort to reduce analytical variation in measurement methods. When such an improvement on analytical variation is established, especially reducing the lower limit of quantitation, it often provides greater insight into the physiology and pathology of disease.

Whether a measurement method is suitable for its clinical use also depends on possible analytical endogenous and exogenous interferences and cross-reactants present in the specimens of the clinically relevant patient population. To be able to measure the hormone of interest correctly, the measurement method must be selected carefully. In children suspected of having enzyme deficiencies in steroidogenesis, precursor steroids often accumulate and measurement methods must be selected or developed that do not suffer from cross-reactivity with such compounds [10]. Also, when medication is given, these should not cross-react in hormone measurement methods. Think about the interference of pegvisomant in growth hormone assays, prednisone in cortisol immunoassays, TRIAC in thyroid hormone immunoassays and insulin analogs in insulin immunoassays [11–14]. LC-MS/MS methods can be a solution in at least some of these cases [15].

Standardization and Harmonization

It is crucial to be able to measure results with a minimum of bias and consistently over time, with different reagents, in different endocrine laboratories around the world to compare results from research studies over time (across generations of people) and for sharing common RIs or CDLs and professional guidelines around the world. Clinical laboratories can no longer work in isolation because of the globalization of health. Standardization and harmonization offer the possibility to make laboratory test results more comparable. Standardization refers to the process of achieving agreement between hormone tests by establishing traceability to a recognized standard reference material through a high-order primary reference material (RM) and/or reference material procedure (RMP); it concerns mainly inert hormones such as steroids. Harmonization aims to make a test more comparable irrespective of an analytical procedure mainly because no RMP nor RM is available; it concerns compounds, which are not uniformly described (heterogenous structures, isoforms such as growth hormone or thyrotropin) [16]. Much effort has been put into standardization and harmonization of hormone assays by for instance working groups of the IFCC (International Federation of Clinical Chemistry); yet, it takes a lot of time before such projects are finalized.

Reference Intervals, Clinical Decision Limits, Diagnostic Sensitivity, and Specificity

The establishment of RIs and CDLs is essential for interpreting hormone measurement results. RIs support the medical decision-making process for assessing health or diagnosing and treating disease by describing the average condition of a healthy population, whereas CDLs represent a threshold or cut-off value at which results are clinically actionable [17].

RIs describe the range in which the central 95% of concentrations of apparently healthy individuals are found [18]. Establishing RIs involves selecting reference individuals based on criteria to exclude those who are not considered healthy. Exclusion criteria may both be applied before the collection of samples (a priori), as well as after the collection of samples (a posteriori) [19]. This process is challenging due to the relative nature of health and lack of definition.

Lifestyle, for example, may have a significant impact on the usefulness of RIs based on healthy or, at least, “non-diseased” individuals. Criteria for a priori exclusion or partitioning may be deviations in body mass index (BMI) (i.e., overweight/obese or underweight), active smoking status, moderate to heavy alcohol consumption, substance abuse, environmental exposures, chronic stress, mental health conditions, and irregular sleep patterns.

CDLs are chosen based on the diagnostic accuracy of a test, which includes its sensitivity (ability to correctly identify diseased individuals) and specificity (ability to correctly identify non-diseased individuals) [20]. Knowing the diagnostic accuracy is crucial for clinicians, as false-positive and false-negative results can have significant consequences for the physical and emotional wellbeing of patients. To establish diagnostic sensitivity and specificity and choosing the CDLs is challenging as well. It depends on the chosen population (diseased and non-diseased), the analytical quality of the laboratory test, and the existence of a gold standard for the definition of diseased versus non-diseased patients, which is often lacking [20].

When determining specific RIs and CDLs, it is essential to consider which groups require them. Commonly, age and sex are used for partitioning. However, age-based partitioning is not always ideal. For instance, for children or women, the Tanner stage or menopausal status might be more relevant than age. You can find more details about partitioning in the section on diversity and inclusion. In summary, establishing RIs and CDLs for endocrine diseases is challenging and requires carefully designed studies to obtain valid and useful estimates.

Fit for Purpose

The quality of hormone tests varies a lot. In general, there is a difference between immunoassays, which are prone to cross-reactivity and more specific LC-MS/MS methods [1]. In addition to the cross-reactivity problem, immunoassays may suffer from interference from other components in the sample (the matrix). An immunoassay can therefore perform well in relatively healthy male subjects but perform different or even poorly in a specific patient or study group. Using such methods may lead to incorrect conclusions [21–23].

Steroid hormones in serum are mostly bound to proteins like sex hormone binding globulin (SHBG), vitamin D binding protein (VDP), and cortisol binding globulin (CBG, transcortin), with only a small percentage circulating freely. Most laboratories measure the total hormone concentration (bound + unbound), requiring extraction from binding proteins. Automated immunoassays often have fixed extraction times and reagent constituents, which can cause issues with samples having abnormal binding protein levels, such as those from pregnant women, women on oral contraceptives, ICU patients, and those with liver disease [24, 25]. This can lead to inaccurate results and incorrect conclusions. For example, a Dutch study found that serum testosterone levels measured by radioimmunoassay decreased after three cycles of oral contraceptive use. However, reanalysis using LC-MS/MS showed no change, indicating the initial conclusion was incorrect due to SHBG interference [21]. Similarly, thyroid hormones are mostly measured as free hormones, theoretically independent of binding protein changes. However, free thyroxine (fT4) immunoassays still struggle with serum matrix differences, such as increased thyroxine binding globulin (TBG) concentrations or TBG deficiency [26, 27].

Peptide hormone immunoassays suffer less from cross-reactivity due to the possibility of using immunometric (sandwich) assays. Method comparisons between peptide immunoassays and LC-MS/MS generally show good agreement, but this can vary. Protein variants can cause discrepancies between immunoassays and LC-MS/MS. For instance, a common IGF1 variant detected by immunoassays shows falsely low concentrations in LC-MS/MS [28]. As more LC-MS/MS methods are being developed, more such discrepancies may be discovered. Depending on the hormone and the question to be answered this can be an advantage or disadvantage. For instance, insulin immunoassays are fast and relatively cheap and the cross-reactivity with insulin analogs can sometimes be of use, but qualifying and quantifying insulin analogs may be an advantage as well [15, 29].

It is a challenge to have reliable, accurate, and economical tests for hormone measurements in all types of populations, healthy and non-healthy. This is, however, highly important because unreliable tests will give unreliable results, which will lead to unreliable conclusions.

IVDR

Regulation (EU) 2017/746 on in vitro diagnostic medical devices (IVDR) applies since May 2022. This law aims to regulate market access of industrially manufactured IVDs [30]. This law also defines conditions for the use of IH-IVDs. Through this legislation, the European Union hopes to improve patient safety by setting high standards of quality and safety concerning IVDs [30]. While the intentions are laudable, many criticisms and threats have been pointed out, as it is currently believed that 17% of IVDs produced by manufacturers could disappear from the European market due to difficulties of certification.

To better understand the situation, it is required to understand the new principles of the IVDR. Previously, the CE marking was based on a self-declaration of conformity by IVD manufacturers whereas under the IVDR, the CE-IVD marking is released after conformity assessment by a notified body. Additionally, IVD manufacturers are now required to provide a system of post-marketing surveillance, as it is already the case for pharmaceutical drugs. To gain access to the market, manufacturers must now provide evidence on scientific validity, analytical performance, and clinical performance. The level of evidence required for clinical performance follows a risk-based approach. In endocrinology, most of the devices will be in the low to middle risk class (named class B and C). In this risk-based approach, the amount of evidence is the same regardless of the prevalence of the disease. As a result, current manufactured IVDs for rare/orphan diseases might disappear from the market because clinical performance studies and certification by the notified body impose high costs c and may not be considered economically viable.

While IH-IVDs could fill the gap left by manufacturers who produce CE marked IVDs (CE-IVD), many concerns have also been raised [31]. Indeed, it takes a considerable investment to fulfil the requirements of the IVDR for IH-IVDs that may limit the willingness of laboratory to develop them. Particularly, Article 5.5 mentions the requirement of no equivalence to CE-IVDs, placing laboratories in a vulnerable position compared with industrial manufacturers and raising questions regarding the sustainability of IH-IVDs. Additionally, many uncertainties remain also regarding the use of CE-IVDs outside of the intended purpose claimed by the manufacturer, the so-called minor and major modifications [32]. On the other hand, the post-market surveillance is globally accepted as an added value to the previous requirements. Indeed, by forcing manufacturers to continuously improve their devices, some well-known interference may finally be taken into consideration by the manufacturers to improve their IVDs. The interference of macroprolactin in the prolactin measurement could be one of the first devices to benefit from this provision [33]. In the study by vanstapel et al. [34], the task force on European regulatory affairs and working group accreditation and the International Organisation for Standardisation/European Committee for Standardisation (ISO/CEN) standards from the EFLM discusses appropriate interpretation of the ISO15189 to cover IVDR requirements.

As the previous regulation was outdated, the IVDR was mandatory. However, many specificities of the laboratory medicine were under-considered when the law was written. Mainstream devices such as thyroid evaluation, which are highly economically viable and well characterized should not be impacted although the lack of notified bodies might postpone their certification. However, innovative tests, devices for rare/orphan conditions, tests sold in small numbers, and personalized medicine might be affected or even disappear [35]. Several calls for action have been published by the European Federation of Laboratory Medicine (EFLM) to avoid shortening such devices and clarify the use of IH-IVDs New actions from the European Union to face these challenges are awaited.

Future Research Directions

Optimization of Current Endocrine Laboratory Medicine

Standardization and Harmonization

The development of the LC-MS/MS technique in endocrine laboratories enables steroid assays to be standardized. Research studies must be performed using standardized assays. International work is underway to ensure the deployment and monitoring of these steps, which are essential for improving the comparability of results. The IFCC and EFLM are working to ensure that results are increasingly comparable, particularly in endocrinology. For instance, the committee for the standardization of the thyroid function tests (C-STFT) has demonstrated that harmonization of TSH and standardization of FT4 is possible [36–38]. Work has to be done before implementation can take place. The same effort is needed to standardize or harmonize the measurements of other hormones as well.

Dynamic Testing

Dynamic endocrine function tests are commonly used in the diagnosis and follow-up of endocrine disorders. However, there is considerable variation in the way these tests are performed between hospitals and laboratories. This is exemplified by the ACTH stimulation test. Differences exist in (1) patient preparation (e.g., whether or not to discontinue oral contraceptives before a ACTH stimulation test), (2) test performance (e.g., administration of ACTH intramuscularly or intravenously), and (3) analytical methods used or assay standardization (measurement of serum cortisol by LC-MS/MS or immunoassay). However, the interpretation of dynamic tests is often based on rigid cut-off values that do not take into account all the variables mentioned above and are often based on varying pre-analytical conditions and outdated analytical methods [39].

The variability in pre-analytical and analytical performance of dynamic tests means that dynamic test results are not interchangeable between health institutions. This can lead to misinterpretation and delays in diagnosis and treatment when patients are referred to other institutions. As a result, dynamic tests are repeated, resulting in increased workload, additional costs and, not least, inconvenience and stress.

Future research strategies should focus on improving the quality of dynamic testing and the interchangeability of test results by aligning procedures at the pre-analytical level, at the analytical level, and finally at the post-analytical level (i.e., redefined RIs or CDLs) [39, 40]. Given the lack of a gold standard for several endocrine disorders and the relatively small number of patients, a concerted effort is needed to establish optimal decision limits for dynamic testing. This can only be achieved by aligning the pre-analytical and analytical work-up, which will require a great deal of support from laboratory professionals, physicians, and IVD manufacturers.

Personalized Medicine in Endocrine Laboratory Medicine

Diversity and Inclusion

To improve the validity of RIs and CDLs and to optimize the diagnostic accuracy of a test, it is necessary to define the criteria for the selection of the apparently healthy population. Sex and age are the two most commonly used criteria for partitioning [19]. However, many more possible and relevant partitioning factors can be thought of, such as, but not limited to, ethnic background, gender, stage of menstrual cycle, pregnancy stage, Tanner stage (puberty), and geographic location. The definition of healthy and diseased populations is difficult, as described earlier, and in addition, it has been based on homogeneous populations or through expert consensus, which has resulted in the underrepresentation of specific populations, including women, children, youth, and the elderly, racialized and ethnic groups, and sexual and gender minorities, all of whom are often excluded in clinical research [41]. The underrepresentation and thereby limited generalizability in terms of findings leads to potentially lower diagnostic test accuracy in these specific populations and to ineffective or harmful treatments for underrepresented groups. When endocrine laboratory medicine becomes more inclusive, this will positively affect the endocrine research outcomes of all types of studies and thereby the generalizability of the conclusions drawn.

Biological Variation and Impact of Environment and Lifestyle

Many hormones exhibit biological variation within individuals. Hormone levels can change over the years, particularly during phases of rapid physiological development, such as the neonatal period (e.g., thyroid hormones), puberty (e.g., gonadal hormones), and menopause (e.g., estradiol, prolactin). Hormones can also vary cyclically, such as during the menstrual cycle (e.g., estradiol, LH, FSH, progesterone), across seasons (e.g., 25-hydroxy vitamin D), or throughout the day (e.g., testosterone, cortisol). Some hormones are secreted in pulses (e.g., growth hormone). Additionally, hormones show random variation around homeostatic set points (within-subject biological variation), which differ between individuals (between-subject biological variation). New devices such as a well-tolerated belt including a catheter inserted into subcutaneous fat for microdialysis sampling every 20 min for later analysis by LC-MS/MS can help assessing this biological variation [42].

Understanding and applying data on all components of biological variation is crucial for accurately interpreting results. Besides biological variation, environmental and lifestyle factors also impact hormone concentrations. Environmental influences, including climate change, pollution, dietary changes, and chemical exposure, can affect the endocrine system, such as thyroid function and disease [43]. Diets high or low in fat, protein, or carbohydrates can for instance influence insulin sensitivity. Whole plant diets, iodine intake, other specific diets, and intermittent fasting can also affect hormone levels. For example, dietary phosphate can impact FGF23 concentrations [44]. Sleep duration and jet lag can influence hormone levels and rhythms, such as cortisol and melatonin. While our understanding of these influences is still evolving, it is essential to consider them when interpreting hormone concentrations.

Biomarker Discovery

The quest for better diagnostic tests continues, and there are already many published candidate biomarkers that may be of use for the investigation of endocrine-related disease. Many of these potential markers have not been fully developed, and there is a pressing need to translate some of these promising tests from a research setting into working clinical tests that could be provided in routine hospital laboratories. This is not a trivial exercise and requires active collaboration between endocrinologists and laboratory specialists using well-characterized laboratory methods and patient groups.

One such initiative, which is bearing fruit, is the expanding use of salivary cortisone for the investigation of adrenal insufficiency [45, 46]. Test results from saliva samples taken upon waking have been shown to correlate closely with the short ACTH stimulation test and could reduce the need for the short ACTH stimulation test in up to 70% of cases. Because samples can be collected in the patient’s home and sent to the laboratory this could reduce the number of clinic appointments and also be more convenient for the patient. Late night salivary cortisol is already well established for the investigation of Cushing’s syndrome [47], but salivary cortisone may also be useful for replacing serum cortisol measurement after the overnight dexamethasone suppression test [48].

The need for improved testing to diagnose hyperaldosteronism has been discussed for many years. Current screening tests are not sensitive enough and the confirmatory tests are not much better. Recent work has focused on the use of steroid profiles including aldosterone precursors as well as the hybrid steroids, 18-oxocortisol and 18-hydroxycortisol, especially when used in conjunction with machine learning to improve data interpretation [49, 50]. The hybrid steroids show great promise in detecting unilateral KCNJ5 tumors and may improve the diagnostic pathway. Several groups are actively developing these methods for routine clinical use.

While recently LC-MS/MS improved the quality of especially steroid hormone analysis in research and diagnostics, future research possibilities may be further advanced by high-resolution mass spectrometry (HRMS) as it allows detection of analytes to the nearest 0.001 atomic mass units. By integrating HRMS with other analytical techniques, researchers can gain deeper insights into the molecular mechanisms underlying endocrine diseases, ultimately enhancing patient care and outcomes. These and other initiatives in endocrine biomarker discovery are needed to improve screening, diagnosis, treatment, and follow-up of (potential) patients with endocrine diseases.

Point-of-Care Testing

Point-of-care testing empowers patients to take greater control of their own health. This approach allows individuals to manage their health more effectively. For research studies, point-of-care testing is ideal as it enables measurements to be taken under various conditions and in diverse locations. Point-of-care testing includes home testing, wearable devices, and remote patient monitoring [51, 52].

In endocrinology, home testing is well-known, particularly for diabetes patients and diabetes research. Glucose levels can be monitored using point-of-care devices or wearable devices that measure glucose in real time in the interstitial fluid, providing feedback for insulin management. Recent studies have explored measuring cortisol with wearable devices, offering new insights into 24-h continuous subcutaneous cortisol levels [53].

Wearable devices can integrate with laboratory information systems (LIS) and electronic health records (EHR) for seamless data sharing. While patients can sometimes interpret their own results (such as with pregnancy tests), in other situations, support is needed from healthcare providers to develop insights and make evidence-based decisions. To handle large datasets, artificial intelligence (AI) and machine learning can be utilized. However, for reliable interpretation and conclusions, it is crucial to consider pre-analytical, analytical, and post-analytical factors before fully relying on these technologies [54].

Sustainability

In the last decade, the concept of sustainability has gained significant momentum across the healthcare system, including clinical and scientific research laboratories [55]. In response to the growing demand for services, laboratories are increasingly focused on reducing their deleterious environmental impact, promoting resource efficiency, and ensuring long-term ecological balance without compromising the productivity and clinical excellence [56]. Recently, EFLM released “EFLM Guidelines for Green & Sustainable Medical Laboratories” and self-assessment checklist, to promote and encourage environmental stewardship within the laboratory community.

Key Principles of Green Laboratories are the following: energy efficiency, water conservation, waste reduction, green chemistry, and sustainable procurement [57, 58].

Adopting sustainable and green laboratory practices yields numerous economic and intangible benefits:

• 1.Environmental impact: green laboratories play a vital role in reducing greenhouse gas emissions and conserving natural resources by minimizing energy, water, hazardous chemicals, and material usage. This aligns laboratories with broader environmental sustainability goals.
• 2.Economic advantages: implementing energy- and resource-efficient practices, along with waste reduction strategies, often results in significant long-term cost savings. These measures enhance operational efficiency while reducing expenditures on energy, materials, and waste disposal.
• 3.Improved safety: reduced use of hazardous materials combined with better waste management protocols creates a safer working environment for researchers and staff.
• 4.Enhanced reputation: a visible commitment to sustainability enhances the institution’s reputation among stakeholders and demonstrates leadership in addressing global environmental challenges.

Transition to a green laboratory may involve additional costs for energy-efficient equipment, infrastructure modifications, and staff training [59, 60]. However, the long-term benefits outweigh these initial investments. Successful implementation also requires a cultural shift among laboratory personnel, changing mindset, emphasizing awareness, and accountability for sustainable practice [59].

Sustainability in laboratories is a moral responsibility but also a practical necessity in the face of global environmental challenges. Green laboratories represent the future, blending innovation with ecological stewardship. By adopting sustainable practices, laboratories can significantly contribute to the reduction of environmental footprint, toward the zero pollution and toxic-free environment, while maintaining high-quality research and healthcare services.

Artificial Intelligence

Artificial intelligence (AI) and machine learning (ML) can significantly enhance the capabilities of endocrine laboratories. The advantages and possibilities have been discussed in a separate chapter about AI. The additional value and future directions for endocrine laboratory medicine is that AI or ML could lead to algorithms that improve the understanding of the endocrine disease, the diagnosis, the screening or treatment of patients. An example is a machine learning-based model that leads to optimization of the newborn screening for congenital hypothyroidism by incorporating amino acids and acylcarnitines in the current newborn screening [61]. Also screening for Cushing’s syndrome, diagnosis and follow-up of adrenal tumors or diagnosis of PCOS are examples that could be improved by using machine learning in future studies [62].

Health Economics

Healthcare systems around the word are evolving due to various factors, including advancements in medical technology and knowledge, which provide new healthcare services and increasing access to them. Changes in health policies address specific diseases and demographic shifts, while new organizational structures and complex financing mechanisms are being developed. However, access to healthcare and increased patient choice are increasingly being considered against the backdrop of financial sustainability. A more sustainable healthcare system is needed that benefits both patients and providers.

Value-based healthcare is a model that focuses on delivering high-quality care, improving patient outcomes, and reducing costs [63]. Key aspects include patient-centered care, quality over quantity, care coordination, preventive care, and cost efficiency. While value-based healthcare focuses on optimizing outcomes and costs, value-based payment models encourage reimbursement based on the value of care provided rather than the volume of services rendered. This perspective can be a strategic theme for financial sustainability in laboratory medicine [54].

It is essential to develop an agenda to promote value-based healthcare and value-based reimbursement in laboratory medicine within an integrated framework. To achieve this, several steps need to be taken. Health outcomes based on the principles of evidence-based laboratory medicine should be defined. The diagnostic accuracy of tests and key outcomes in downstream patient management should be linked and total costs should be considered. For instance, more accurate technologies like LC-MS/MS may have higher initial costs but can reduce overall healthcare costs by preventing over-treatment and misdiagnosis through more accurate diagnostics of hormones, thereby improving the quality of results in endocrine research and diagnostics.

Conclusion

Research in Endocrine Laboratory Medicine is crucial for several reasons. First, it deepens our understanding of complex hormonal interactions and their effects on health, which is essential for developing accurate diagnostic tests and effective treatments. Second, advancements in this field can lead to the early detection of endocrine disorders, improving patient outcomes and reducing healthcare costs. Additionally, research can identify new therapeutic targets and innovative treatment strategies.

Overall, ongoing research in Endocrine Laboratory Medicine is fundamental to advancing medical science and enhancing patient care for endocrine-related diseases. Endocrine laboratory medicine can be optimized by focusing on pre-analysis, dynamic testing and standardization and harmonization of endocrine tests and new technologies. Emphasis should be placed on personalized medicine, considering diversity and inclusion, biological variation, and the impact of environment and lifestyle. Further innovation is needed in biomarker discovery and point-of-care testing. Sustainability and green lab practices should be prioritized, and the use of artificial intelligence and health economics can be leveraged. All these efforts aim to improve the quality of research and diagnostics, ultimately enhancing our knowledge and the health of patients with endocrine diseases.

Research Priorities

Taking into account the above-mentioned current status and challenges encountered in the field of endocrine laboratory medicine, the following topics should be the research priorities for the next 10 years:

• Optimization of the pre-analysis, analysis, and post-analysis of current hormone tests and endocrine dynamic tests with a special emphasis on harmonization and standardization and considering IVDR.

• Personalization of hormone test interpretation by establishing reference intervals and critical decision limits for a variety of factors such as age, gender, ethnic background, stage of menstrual cycle, pregnancy stage, Tanner stage, geographic location, and other biological variations, environmental and lifestyle factors.

• Discovery of new biomarkers, new analytical techniques, tools such as wearable devices and/or artificial intelligence to improve the diagnosis, treatment, follow-up, screening, or understanding of endocrine disorders.

• Future-proof endocrine laboratory medicine by improving sustainability and applying value-based healthcare.

Conflict of Interest Statement

None declared.

Funding Sources

None declared.

Author Contributions

Annemieke Heijboer (investigation [equal], methodology [equal], project administration [equal], writing – original draft [equal], writing – review and editing [equal]). Aurelie Ladang (investigation [equal], writing – original draft [equal]). Tomris Ozben (investigation [equal], writing – original draft [equal]). Sanja Stankovic (investigation [equal], writing – original draft [equal]). Jacquelien Hillebrand (investigation [equal], writing – original draft [equal], writing – review and editing [equal]), Brian Keevil (investigation [equal], writing – original draft [equal]). Antonius van Herwaarden (investigation [equal], writing – original draft [equal], writing – review and editing [equal]). Eleanor Davies (writing – review and editing [equal]). Jonathan Mertens (writing – review and editing [equal]), and Véronique Raverot (investigation [equal], writing – original draft [equal], writing – review and editing [equal]).

Funding Statement

None declared.