Biomarker

Biomarkers can come from blood, urine, saliva, tissue, images, physiology, or digital sensors. Examples include a molecule concentration, a blood-pressure reading, a DEXA measurement, or a heart-rate pattern. The label describes the role of a measurement, not its quality or importance.

A useful biomarker needs a clearly defined method, unit, reference context, and intended purpose. Analytical validity asks whether the measurement is accurate and repeatable. Clinical interpretation asks what it means for a particular question and population. A test can perform well analytically while still having limited meaning outside its intended context.

Reference intervals, decision thresholds, and personal baselines are different comparison tools. Biological variation, collection timing, preparation, specimen handling, devices, and laboratory methods can all influence values. One marker rarely captures a complex system, which is why panels and repeated measurements require careful attention to dependence and context.

Biomarkers may be diagnostic, prognostic, monitoring, susceptibility-related, or used for another defined purpose. Performance in one role does not automatically establish performance in another. The intended use and population are therefore as important as the name of the measurement.

Measurement performance is often described using concepts such as sensitivity, specificity, precision, and reproducibility. These address different questions: detecting a defined state, excluding it, repeating a value, or obtaining comparable results across conditions. One strong property does not imply all the others.

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