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A study on reference interval transference via linear regression.

Runqing Mu1, Ke Yun1, Xiaoou Yu1

  • 1Department of Laboratory Medicine, The First Hospital of China Medical University, National Clinical Research Center for Laboratory Medicine, Shenyang, Liaoning, P.R. China.

Clinical Chemistry and Laboratory Medicine
|July 29, 2019
PubMed
Summary
This summary is machine-generated.

Reference intervals (RIs) transference is feasible but requires careful method selection. Optimizing conditions like correlation and sample size ensures accurate transference between laboratory systems, reducing clinical risks.

Keywords:
least squares methodlinear regressionreference intervalstransference

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Area of Science:

  • Clinical Chemistry
  • Laboratory Medicine
  • Reference Interval Validation

Background:

  • Reference intervals (RIs) transference can extend the use of established RIs.
  • Current transference methodologies and validation using small samples are insufficient for complex scenarios.
  • This study investigates optimal conditions for effective RI transference.

Purpose of the Study:

  • To identify appropriate conditions for ensuring successful reference interval transference between laboratory systems.
  • To evaluate the accuracy, precision, and trueness of transferred RIs under various conditions.
  • To provide guidance on selecting suitable transference methods and parameters.

Main Methods:

  • Established RIs for 27 analytes using Roche and Beckman systems (n=681 healthy individuals).
  • Converted Roche RIs to Beckman RIs via linear regression (least squares method) using two approaches: Methodref (500 samples, narrow range) and Methodep (80 samples, wide range).
  • Assessed transferred RI accuracy, precision, and trueness against Beckman-established RIs.

Main Results:

  • Analyte consistency between systems varied (29.6% lower limit, 48.1% upper limit).
  • Methodref showed higher concordance rates (74.1%-92.6%) compared to Methodep (44.4%-59.3%).
  • Accuracy improved with increasing sample size (CV decreased) and strong correlation (r > 0.800) for most analytes.

Conclusions:

  • Reference interval transference is influenced by correlation, sample size, regression method, and quality requirements.
  • Selecting the appropriate method and optimizing conditions are crucial for minimizing transference risks.
  • Careful consideration of these factors ensures reliable RI transference between different laboratory systems.