Review of biological variation and its applications in interpretation of equine clinical pathology results.
Authors: Fernandes T, Robin Matthew, Freeman Kathleen P
Journal: Equine veterinary journal
Summary
Understanding how laboratory values naturally fluctuate within individual horses is essential for interpreting test results accurately, yet many practitioners rely solely on population-based reference ranges that may not reflect a particular animal's normal baseline. Fernandes, Robin and Freeman's comprehensive review examines biological variation—the physiological oscillation around each horse's homeostatic set point—and demonstrates how concepts such as reference change values (RCV), individualised reference intervals (iRI), and the Index of Individuality can transform clinical decision-making from subjective to evidence-based. By calculating intra-individual variation (CVI), group variation (CVG), and analytical variation (CVA), clinicians can determine whether a measured change in consecutive results represents genuine pathology or merely normal physiological fluctuation, which is particularly valuable when monitoring conditions over time or distinguishing disease from the grey zones that exist around conventional cut-off values. The review emphasises that indices of individuality help determine when a horse's own reference interval would be more diagnostically sensitive than population-derived ranges—a distinction that could substantially improve early disease detection and prognostic accuracy. For equine practitioners, this framework offers a practical pathway to strengthen the reliability of laboratory-based diagnosis and monitoring protocols, moving beyond the limitations of standardised reference intervals toward truly personalised clinical interpretation.
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Practical Takeaways
- •Use RCV to objectively assess whether consecutive lab results represent a real physiological change in your patient rather than normal variation, improving diagnostic confidence.
- •Calculate an individual horse's homeostatic setpoint (HSP) from baseline values when possible; this individualised approach may detect disease earlier than population reference ranges.
- •Understand that some measurands require population-based reference intervals while others benefit from individualised interpretation—consult biological variation data to select the appropriate approach for each test.
Key Findings
- •Biological variation encompasses individual variation (CVI), group variation (CVG), and analytical variation (CVA) as distinct components affecting laboratory result interpretation.
- •Reference change value (RCV) provides an objective, evidence-based method for determining the significance of consecutive laboratory results in individual horses.
- •Index of Individuality (II) determines whether population-based reference intervals or individualised reference intervals (iRI) are more appropriate for detecting significant changes in specific measurands.
- •Biological variation data can improve diagnostic accuracy of clinical laboratory testing and support or disprove empirically derived interpretation recommendations.