Reference intervals in value-based laboratory medicine: a shift from single-point measurements to metabolic...

Area of Science:

• Clinical chemistry
• Laboratory medicine
• Biostatistics

Background:

• Accurate laboratory data interpretation relies on reliable reference data.
• Conventional reference data estimation using single-sample measurements may be insufficient due to biological variations.
• Analyte concentrations are affected by random and systematic variations, impacting patient result interpretation.

Purpose of the Study:

• To propose a paradigm shift in estimating reference intervals.
• To incorporate metabolic dynamics into reference interval estimation.
• To enhance the clinical value of laboratory data for decision-making.

Main Methods:

• Review of current practices in reference data estimation.
• Discussion of incorporating longitudinal and dynamic data.
• Identification of suitable statistical models for metabolic dynamics.

Main Results:

• Current models based on single-sample distributions have limitations.
• Incorporating metabolic changes can provide more reliable reference intervals.
• A transition to dynamic models is recommended for improved clinical utility.

Conclusions:

• A shift towards models reflecting metabolic dynamics is essential for accurate laboratory data interpretation.
• This approach will enhance clinical decision-making and patient care.
• Further research into dynamic reference interval models is warranted.