Definitions and major prerequisites of direct and indirect approaches for estimating reference limits

Area of Science:

• Clinical Chemistry
• Laboratory Medicine
• Biostatistics

Background:

• Reference intervals are essential for interpreting laboratory test results.
• Current definitions for indirect methods of establishing reference intervals lack consensus.
• Indirect methods are gaining popularity, necessitating standardized approaches.

Purpose of the Study:

• To propose a general definition for indirect reference interval models.
• To highlight the need for partitioning strategies in indirect methods to reduce false classifications.
• To advocate for the future use of indirect models with large datasets.

Main Methods:

• Review and synthesis of existing indirect reference interval models.
• Development of a generalized definition encompassing current indirect approaches.
• Discussion of partitioning strategies for indirect methods.

Main Results:

• A comprehensive definition for indirect reference interval estimation is provided.
• Indirect methods offer greater flexibility for implementing partitioning strategies compared to direct methods.
• The study underscores the importance of quality assurance in both pre-analytical and analytical phases.

Conclusions:

• The proposed definition unifies existing indirect reference interval methodologies.
• Indirect models, particularly with large datasets, are poised to dominate future reference interval estimation.
• Robust quality assurance is paramount regardless of the chosen reference interval approach.