Biological variation and reference change values of serum Mac‐2–binding protein glycosylation isomer (M2BPGi)

Abstract Background Limited data are available with regard to biological variations of the Mac‐2–binding protein glycosylation isomer (M2BPGi), a liver fibrosis biomarker. Methods Long‐term biological variation of M2BPGi was investigated using longitudinally measured M2BPGi test results from healthy Korean adult subjects. One‐way analysis of variance (ANOVA) tests were used to calculate the reference change value (RCV) of M2BPGi based on biological variation estimates. Furthermore, asymmetric RCV was calculated according to a recent publication of the European Federation of Clinical Chemistry and Laboratory Medicine Working Group on Biological Variation and Task Group for the Biological Variation Database (EFLM TG‐BVD). Results A total of 363 test results from 174 Korean subjects undergoing general health checkups were requested from 13 local clinics and hospitals during a 38‐month period. The within‐subjects biological variation (CVI), between‐subject biological variation (CVG), analytical variation (CVA), RCV, and individuality index (II) values for serum M2BPGi were 23.3%, 30.0%, 4.3%, 65.6%, and 0.78, respectively. Asymmetric RCV calculated using formulae by a recent EFLM TG‐BVD publication ranged from −41.9 to 72.0%. Desirable analytical performance specifications for M2BPGi derived from biological variation were as follows: imprecision 11.6%, bias 9.6%, and total allowable error 28.7%. Conclusions RCV based on biological estimates may be helpful for evaluating and interpreting serial M2BPGi measurements by physicians and in clinical laboratories.

test result verification as a quality improvement effort by laboratories. 2,3 Furthermore, in clinical practice for bone turnover markers as an example, RCVs based on biological variation are used as the term of least significant change for patient management in the treatment and monitoring of osteoporosis under clinical practice guidelines. 4,5 Meanwhile, Wisteria floribunda agglutinin-positive Mac-2binding protein (WFA + M2BP; Mac-2-binding protein glycosylation isomer, M2BPGi), has recently been introduced to clinical laboratories as a non-invasive surrogate marker for liver fibrosis in chronic liver diseases such as viral hepatitis, nonalcoholic fatty liver disease, and hepatocellular carcinomas. 6,7 Serial measurements of M2BPGi can be used to estimate the progression and prognosis of liver fibrosis and predict hepatocellular carcinomas. 7,8 Studies focused on its variation with regard to clinical implications of M2BPGi are still ongoing. 7,8 Considering that the observed variation in M2BPGi results in an individual in a steady-state is affected by the CV I and CV A , not only by disease progression or regression, having knowledge on RCVs is helpful for clinical laboratories in terms of quality improvement as well as for physicians to understand the analytical aspects of the M2BPGi test and interpret results for patient management. Furthermore, analytical performance specifications based on biological variation data can improve the quality of clinical laboratory practices. However, information on RCVs for M2BPGi based on biological variation is limited. Therefore, we investigated biological variation and RCV of M2BPGi in Korean patients. We also evaluated analytical performance specifications to improve quality in clinical laboratories using calculated biological variation estimates.

| Study populations
We retrospectively reviewed data obtained through the laboratory in- M2BPGi test results showed 1+ or 2+ at least once during a follow-up in order to assess biological variation in subjects assumed to be relatively healthy. The M2BPGi test as a liver fibrosis biomarker in Green Cross Laboratories was installed and available for two test orders by physicians; one for diagnostic and monitoring purposes for patients with suspected liver fibrosis, and the other code is for relatively healthy subjects visiting health promotion centers throughout Korea. The results of this study were based on data from the latter. All data were anonymized prior to statistical analysis. This study was conducted according to the guidelines outlined in the Declaration of Helsinki, and all procedures involving human subjects were approved by the Institutional Review Board of Green Cross Laboratories (GCL-2021-1025-01).

| Statistical analysis
We used a one-way analysis of variance (ANOVA) model for data analysis to investigate the CV I and between-subject biological variation (CV G ). 9,10 CV A was obtained from the internal quality control program of the laboratory (4.3%). 9,10 The individuality index (II) was calculated as follows 2 : II = CV I /CV G . The RCV for M2BPGi were calculated using the following equations: where CV Ln = (ln (1+CV 2 )) 1/2 and Z = 1.64 (probability level 95%). 11 Analytical performance specifications for M2BPGi measurement derived from biological variation data were investigated using the following calculations. For optimal performance specifi- Intraindividual changes of M2BPGi during a follow-up to allow visual inspection are shown in Figure 1. Biological variation estimates of CV A , CV I , CV G , II, and RCV for M2BPGi using data for all subjects and analytical performance specifications for M2BPGi measurement derived from biological variation data are presented in Table 2. Asymmetric RCV calculated using formulae by a recent EFLM TG-BVD publication ranged from −41.9% to 72.0%. Desirable analytical performance specifications for M2BPGi derived from biological variation were as follows: imprecision 11.6%, bias 9.6%, and TEa 28.7%.

| DISCUSS ION
In this study, we investigated the long-term biological variation and

ACK N OWLED G M ENT
The authors thank Ms. Yeon Woo Jo at Green Cross Laboratories for her administrative support.

CO N FLI C T O F I NTE R E S T
All the authors declare that there is no conflict of interests.

AUTH O R CO NTR I B UTI O N S
This work was performed as a collaboration among all the authors. All the authors accept responsibility for the entire content of this submitted manuscript and approve its submission. All authors contributed to manuscript preparation; R. Choi, G. Chun, U. Asymmetric RCV, % ‡ −41.9-72.0 Note: Variance components calculated from the 363 M2BPGi test results from 174 total subjects. † 95% confidence interval. The 95% confidence interval of CV A could not be determined because CV A was calculated using data from an internal quality control program not using replicated test results of clinical specimens. Therefore, the 95% confidence interval of CV I derived from the subtraction of CV A from CV T could not be calculated. ‡ Asymmetric RCV was calculated according to a recent publication of the European Federation of Clinical Chemistry and Laboratory Medicine Working Group on Biological Variation and Task Group for the Biological Variation Database. CV A , analytical coefficient of variation; CV I , within subject biological variation; CV G , between-subject biological variation; CV T , total variation; II, individuality index; RCV, reference change value; TEa, total allowable error. data analysis; R. Choi, and G. Chun designed the study; R. Choi, S.G. Lee and E. H. Lee had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All authors read and approved the final manuscript.

DATA AVA I L A B I L I T Y S TAT E M E N T
The data that support the findings of this study are available from the corresponding authors upon reasonable request.