A study on reference interval transference via linear regression

Runqing Mu; Ke Yun; Xiaoou Yu; Shitong Cheng; Ming Ma; Xin Zhang; Shuo Wang; Min Zhao; Hong Shang

doi:10.1515/cclm-2019-0055

Artikel

A study on reference interval transference via linear regression

Runqing Mu , Ke Yun , Xiaoou Yu , Shitong Cheng , Ming Ma , Xin Zhang , Shuo Wang , Min Zhao und Hong Shang

Veröffentlicht/Copyright: 27. Juli 2019

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Aus der Zeitschrift Clinical Chemistry and Laboratory Medicine (CCLM) Band 58 Heft 1

Abstract

Background

Reference intervals (RIs) transference can expand the applicability of established RIs. However, the study on transference methodology is insufficient, and RIs validation based on small samples cannot adequately identify transferred risk under complex situations. This study aimed to find appropriate conditions to ensure the effect of transference.

Methods

We established the RIs of Roche and Beckman systems for 27 analytes based on 681 healthy individuals. Roche RIs were converted into the Beckman RIs using linear regression (least squares method) which is divided into two methods – Method_ref (500 test numbers with relatively narrow data range) and Method_ep (80 test numbers with relatively wide data range). Taking the RIs established by Beckman results as standard, we assessed the accuracy, precision and trueness of transferred results under various conditions.

Results

A total of 29.6% and 48.1% of analytes were consistent between the two systems for the lower and upper reference limits, respectively. The concordance rates between transferred and measured RIs for Method_ref were up to 74.1% and 92.6%, which were better than Method_ep (44.4% and 59.3%). The CV of transferred reference limits decreased gradually with increasing test number under the same data range. For most analytes, excluding some electrolyte tests, we could obtain accurate results when r > 0.800 and the test number was sufficient regardless of the regression equation types.

Conclusions

Transferability of RIs is affected by many factors, such as correlation, test number, regression equation type, and quality requirement. To reduce the risk of transference, it is very important to select right method with reasonable conditions.

Keywords: least squares method; linear regression; reference intervals; transference

Corresponding authors: Min Zhao, MD, PhD and Prof. Hong Shang (Laboratory Director), MD, PhD, Department of Laboratory Medicine, The First Hospital of China Medical University, National Clinical Research Center for Laboratory Medicine, 155 Nanjing Street North, Heping District, Shenyang, Liaoning 110001, P.R. China, Phone/Fax: +86-24-83282678

Acknowledgments

We thank the participants for their cooperation and sample contributions. We are grateful to all the staff members for taking part in this study. This study was supported by National Health Commission of the People’s Republic of China. This study was technical supported by Roche Diagnostics Ltd. and Beckman coulter Inc.

Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: This study was supported by National Key Technologies R&D Program of China (2012BAI37B01) provided by the Ministry of Science and Technology of the People’s Republic of China, and Laboratory Medicine Innovation Unit (2019RU017) provided by Chinese Academy of Medical Sciences.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

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Received: 2019-01-15

Accepted: 2019-07-03

Published Online: 2019-07-27

Published in Print: 2019-12-18

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Artikel in diesem Heft

https://doi.org/10.1515/cclm-2019-0055

Schlagwörter für diesen Artikel

least squares method; linear regression; reference intervals; transference