Biogenic amines and their metabolites are central biochemical markers in the diagnosis and management of catecholamine-producing neuroendocrine tumors, including pheochromocytoma, paraganglioma, and neuroblastoma. Despite decades of clinical use, their wider implementation remains limited by substantial physiological variability, pre-analytical influences, and methodological heterogeneity across laboratories. The transition from colorimetric and immunoassay-based techniques to liquid chromatography-tandem mass spectrometry has markedly improved analytical sensitivity and specificity. The multiplexing capacity of modern mass spectrometric platforms has enabled comprehensive quantification of biogenic amine profiles, thereby increasing diagnostic sensitivity in tumor subtypes in which individual biomarkers exhibit limited performance. Increasing attention has been given to dopamine derived metabolites, especially 3-methoxytyramine, which is associated with MYCN-related tumor biology and unfavorable clinical outcomes in neuroblastoma and selected paraganglioma subtypes. However, the analytical complexity of mass spectrometric approaches, together with the absence of full metrological traceability, continues to limit inter-laboratory comparability. In this review, we critically evaluate the analytical evolution of biogenic amine testing, the principal pre-analytical and methodological determinants that influence the interpretation of results, and current efforts to improve harmonization. Particular emphasis is placed on the potential of biogenic amines as prognostic biomarkers and on the need to integrate expanded biogenic amine profiling into clinically robust, comparable diagnostic approaches that may advance precision oncology.

In hemostasis diagnostics, increasing analytical performance and test availability do not automatically translate into improved clinical outcomes. We propose value-based hemostasis diagnostics (VBHD) as a structured framework that links laboratory testing directly with patient-centered value and optimized resource utilization.

Personalised laboratory medicine has advanced through reference change values, personalised reference intervals and decision limits, multivariate reference models, and indication-aware interpretation. Yet these developments do not resolve a distinct problem: evidence of within-person change and evidence supporting the applicability of an interpretive system answer different clinical questions and may diverge. We propose a two-axis reporting framework that keeps these evidentiary objects separate. After confirming adequate measurement integrity and comparability, Axis D (deviation) represents evidence of meaningful deviation from the patient's own expected state, while Axis A (applicability) represents the evidentiary warrant for applying a reference system, decision limit, prediction rule, equation, or algorithm to that patient and setting. The distinctive proposition is the coupling rule: applicability determines whether an interpreter can support diagnostic closure of the question a change signal opens, so that in the High D/Low A state - change-applicability discordance - a meaningful patient-specific change should not be neutralised by reassurance from an interpreter whose applicability is weakly supported; instead, independent or better-applicable evidence should be considered in proportion to clinical risk. The motivation parallels precision dosing, where appropriateness depends on patient characteristics. This is not a new diagnostic score; it is a reporting and decision scaffold whose value should be tested and rejected if it fails to improve decision quality or net clinical benefit. Existing frameworks help clinicians choose, personalise, validate, and contextualise the interpreter; the two-axis framework addresses what to do when evidence about the patient and evidence about the interpreter disagree.

Familial hypercholesterolemia (FH) is a common genetic disorder causing elevated low-density lipoprotein cholesterol (LDL-c) concentrations from birth, resulting in a high risk of premature cardiovascular disease. Despite effective early treatment, FH remains underdiagnosed in children, highlighting the need for universal screening. This systematic review aims to evaluate the available evidence regarding suitable biomarkers for the purpose of universal screening for FH in childhood. The electronic databases Medline and Embase were systematically searched for studies comparing blood biomarkers in children with heterozygous FH and non-FH children. Of the 2,488 studies found, 35 were included. Although the data were constrained by considerable heterogeneity, LDL-c, total cholesterol (TC), and apolipoprotein B (ApoB) concentrations were consistently higher in children with FH across the included studies. Furthermore, increased non-high-density lipoprotein cholesterol (non-HDL-c), lathosterol, sitosterol and TC/HDL-c ratio, and a decreased squalene/TC ratio were found in children with FH. Only three screening studies combined biomarker (LDL-c, non-HDL-c and TC) and genetic testing simultaneously, revealing however limited sensitivity and specificity of these markers for FH screening in children. In this review, several biomarkers for FH screening in children were evaluated. As sensitivity and specificity data were generally not available or suboptimal, additional studies are needed to evaluate the screening performance of selected biomarkers in well-defined pediatric populations of suitable age and sex distribution, using valid analytical methods, and taking into account possible confounding factors. It is only through such studies that a well-considered selection of biomarkers can be made for the purpose of childhood screening for FH.