About Asia Study

2009 Asian Project For Collaborative Derivation Of Reference Interval
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The 2009 Asian multicenter study for derivation of reference intervals (RIs) featured

(1) 3500 well-defined healthy volunteers were recruited from 7 East and Southeast Asian countries by participation of 63 labs (46 were from Japan)

(2) Targeting commonly tested 95 analytes: 32 standardized and 40 non-standardized analytes.

(3) Centralized measurement scheme was adopted to eliminate reagent-dependent variations.

(4) RIs for standardize analytes were made traceable to reference measurement procedures (RMP) for common use of the RIs

(5) The RIs for non-standardized analytes (hormones, tumor makers, etc.) were transferred to the local laboratory based on cross-checking of test results with the central lab.

INTRODUCTION
Background

The global standardization of major laboratory tests has been achieved by the efforts of IFCC and its member organizations. However, reference intervals (RIs) remain discordant between laboratories. This situation reflects insufficient number of subjects and inappropriate statistical procedure for derivation of reliable RIs.

In order to overcome the problem, the multicenter study for derivation of common RIs from a large number of healthy subjects was conducted in 2000 and 2005 in Asian cities by the IFCC Committee on Plasma Proteins (C-PP) targeting 32 commonly tested analytes including major serum proteins. Unexpectedly, it revealed a large inter-region variation for many analytes belonging to inflammatory markers, such as IgG, C3, and CRP.

Related papers
    [The 1st Asian Study]
  • Ichihara K, Itoh Y, Min WK, et al. Diagnostic and epidemiological implications of regional differences in serum concentrations of proteins observed in six Asian cities. Clin Chem Lab Med 2004; 42:800-9
    doi: 10.1515/CCLM.2004.133
    • [The 2nd Asian Study]
  • Ichihara K, Itoh Y, Lam CWK, et al. Sources of variation of commonly measured serum analytes among 6 Asian cities and consideration of common reference intervals. Clin Chem 2008; 54:356–65.
    doi: 10.1373/clinchem.2007.091843
Objectives

A large scale multi-center RI study was conducted with the following objectives in East and South-east Asian country, targeting 95 test items including CBC and those measured by immunoassays.
(1) To explore regional differences in RVs by centralized measurement scheme
(2) To derive universal RIs by ensuring traceability of reference values to the RMPs
(3) To transfer RIs of non-standardized analytes by cross-checking of test results between the central labs and local labs.

METHOD
Organization of the study
  • IFCC Science Division (IFCC-SD)
    • Committee on Plasma Protein (C-PP)
    • Committee on RI and Decision Limit (C-RIDL)
  • Asia-Pacific Federation of Clinical Biochemistry (APFCB)
  • Japan Society of Clinical Chemistry (JSCC)
  • Japan Society of Laboratory Medicine (JSLM)
Target Population and Sample Size

The study included 63 clinical laboratories from South Korea, China, Taiwan, Vietnam, Malaysia, Indonesia, and nationwide 7 areas in Japan. A total of 3541 healthy individuals aged 20-64 years (Japan 2082, others 1459) were recruited mostly from hospital workers based on the following inclusion/exclusion criteria.

Inclusion and exclusion criteria
Target analytes and measurements
  • Chemical assay (24)
    • Enzyme: AST, ALT, LD, ALP, GGT, CK, AMY, LIP
    • Lipid: TCho, TG, HDL-C, LDL-C
    • Electrolyte: Na, K, Cl, Ca, IP, Fe, UIBC
    • Others: TP, Alb, CRE, Urea, UA
  • Immunoturbidometry (18)
    • CRP, IgG, IgA, IgM, C3, C4, Tf, TTR, RBP, CysC, ASO, SAA, ApoA1, ApoB, ApoE, LP(a)PG1, PG2
  • Immunoassay (28)
    • Tumor markers: PSA, CEA, AFP, CA19-9, CA15-3, CA125, Ferritin
    • Endocrinology: FT4, FT3, TSH, Tg, FSH, LH, PRL, EPO, Cortisol, Estradiol, Progesterone, Testosterone, DHEA-S, PTH, Insulin, Adiponectin
    • Miscellaneous: IgE, VitB12, Folate, BoneALP, TRAP-5b
    • *Red colored items are standardized analysis

    All the specimens were sent to Tokyo at −80°C for collective centralized measurements. To exclude the influence of between-analyzer variation of test results.

Standardization of the assay

Universality (traceability to RMPs) of the RIs derived were ensured by recalibrating test results based on assigned values in SRMs/CRMs.

Statistical analyses
i) Sources of variation (SV) analysis and partitioning criterion
SVs were analyzed by 3-level nested ANOVA. The SVs considered were sex, region, age, and BMI. Variations of reference values due to each SV is expressed as a standard deviation (SD) between-region SD (SDreg), between-sex SD (SDsex), and between-age SD (SDage).

The magnitude of each SD relative to between-individual SD (SDindiv) was computed as the SD ratio (SDR) as shown in the figure:

An SDR of ≥ 0.3 was regarded as significant, requiring partition of reference values by the factor. In the above computation

ii) Derivation of reference intervals
The RIs were derived parametrically by use of modified Box-Cox transformation, which invariably succeeds in transforming reference value distribution into Gaussian unless there are a lot of values below a detectable limit.
iii) Latent Abnormal Values Exclusion (LAVE) Method
It is necessary to secondarily exclude inappropriate individuals who did not follow the request of fasting or avoidance of strenuous exercise, and who had latent abnormal results due to metabolic syndrome, DM, or anemia. LAVE method was applied by setting the following 13 analytes as reference test items to judge appropriateness of the reference individual: Alb, Glb, UA, Glu, AST, ALT, LD, GGT, CK, TG, HDL-C, LDL-C, and CRP.
In short, the initial RIs were derived analyte by analyte independently of the results of the others. From the second iteration, the RIs for the above exclusion criteria analytes obtained at the previous cycle of iteration were used to exclude individuals who had abnormal results in analytes other than the one being evaluated. In applying the exclusion criteria, the RIs were extended on both ends by 5% of the interval, or (upper limit–lower limit) × 0.05. Therefore, when the test results are normally distributed, results outside of the mean ± 2.16 SD (total of 3% on two tails) are regarded as abnormal. This adjustment was made to avoid excluding too many individuals unnecessarily. The computation was continued until the RIs of all the analytes became stable.
Related papers
  • Ichihara K, Kawai T. Determination of reference intervals for 13 plasma proteins based on IFCC international reference preparation (CRM470) and NCCLS proposed guideline (C28-P,1992): trial to select reference individuals by results of screening tests and application of maximal likelihood method. J Clin Lab Anal 1996; 10:110-7
    doi: 10.1002/(SICI)1098-2825(1996)10:2<110::AID-JCLA9>3.0.CO;2-G
  • Ichihara K, Boyd J. An appraisal of statistical procedures used in derivation of reference intervals. Clin Chem Lab Med 2010;48:1537–1551.
    doi: 10.1515/CCLM.2010.319
  • Ichihara K. Statistical considerations for harmonization of the global multicenter study on reference values. Clin Chim Acta 2014; 432: 108–118.
    doi: 10.1016/j.cca.2014.01.025
Results
Regionality of laboratory tests
Reference values were partitioned by regions (7 regions within and 7 cites outside Japan) for each sex. Regional differences (SDRreg≥0.3) were observed for urea, HDL-C, IgG, C3, etc among the standardized analytes.
Among the non-standardized analytes, regionality was observed in PTH, folate, CA19-9, and adiponectin.
The table below summarizes regional differences observed. Please no regionality was observed within Japan.
Between-sex and between-age differences
SDRs for sex and age-group were computed from reference values based on 3-level nested ANOVA by setting region, sex and age as SVs. When SDR ≥ 0.3 was considered as practically significant association of a given SV on test results, the following analytes showed significant sex and/or age-related changes.
■ Standardize analytes
SDRsex was significant for 19 analytes: Alb Urea, UA, CRE, Na, Ca, TG, HDL-C, AST, ALT, ALP, GGT, CK, IgM, TTR, Tf, testosterone, estradiol, progesterone.
SDRage was significant for 16 analytes: Alb, urea, Na, Ca, TC, TG, LDL-C, AST, ALT, LD, ALP, GGT, IgM, testosterone, estradiol, progesterone
[List of assay methods and assay imprecision near the mid-nomal range for standard analytes.pdf]
■ Non-standardize analytes
SDRsex was significant for 17 analytes: CysC, Fe, UIBC, ApoA1,RBP, ferritin, sTf-R, CEA, CA12-5, PSA, DHEA-S, PRL, LH, FSH, FT3, adiponectin, boneALP
SDRage was significant for 15 analytes: CysC, IP, ApoB, RBP, AFP, CA125, PG1, PG2, DHEA-S, FSH, LH, insulin, PRL, boneALP, TRAP-5b
[List of assay methods and assay imprecision near the mid-nomal range for non-standard analytes.pdf]
Derivation of RIs
RIs were derived from reference values by use of the LAVE method in three ways: male plus female, male only, and female only. For analytes with apparent regionality, RIs were partitioned, if relevant, based on SDRreg. Please note that LAVE procedure led to approximately 13% reduction in data size (n=3314→2880). The effect of LAVE procedure was prominent only for analytes known to be related to the metabolic syndrome such as TG, AST, ALT, GGT, and CRP. For these five analytes, individuals consuming ethanol >40 g/day and those with BMI >26 kg/m2 were excluded before deriving RIs.
Derivation of age-specific RIs
Age-specific RIs for every decade of age for each sex were derived both from data of the entire regions and from data limited to Japan.
[List of age-related RIs.pdf]
Related papers
  • Ichihara K, Ceriotti F, Tam TH, et al. The Asian project for collaborative derivation of reference intervals: (1) strategy and major results of standardized analytes. Clin Chem Lab Med 2013; 51:1429–42.
    doi: 10.1515/cclm-2012-0421
  • Ichihara K, Ceriotti F, Mori K, et al. The Asian project for collaborative derivation of reference intervals: (2) results of non-standardized analytes and transference of reference intervals to the participating laboratories on the basis of cross-comparison of test results. Clin Chem Lab Med 2013; 51:1443–57.
    doi: 10.1515/cclm-2012-0422
  • Wang X, Ichihara K, Xu G. et al. Call for the use of a common equation for glomerular filtration rate estimation in East and South-east Asia. Clin Biochem 2014; 47:1214–19.
    doi: 10.1016/j.clinbiochem.2014.05.058
  • Shimizu Y, Ichihara K. Sources of variation analysis and derivation of reference intervals for ALP, LDH, and amylase isozymes using sera from the Asian multicenter study on reference values. Clin Chim Acta 2015; 446: 64–72.
    doi: 10.1016/j.cca.2015.03.034