Establishment of a new algorithm for the reference interval of relative change values and application evaluation

doi:10.3969/j.issn.1673-8640.2021.06.019

Abstract

Abstract:

Objective To establish and apply a new algorithm for the reference interval of relative change values（RCV）. Methods Based on the relationship between the relative change values（Δ_R） and the fluctuation（λ）,a related big datum model was established by Excel 2007,and the distribution characteristics of λ and Δ_R and the relationship with coefficient of variation（CV） were analyzed. Finally,the algorithm of RCV was established. RCV data in previous literature reports were recalculated using this algorithm and compared with traditional algorithms. Results λ was positively skewed,and its logarithm was center-symmetrically distributed. When CV≤9.5%,λ was approximately log-normally distributed. The shape of Δ_R distribution was the same as that of λ,and the position was shifted "1" to the left relative to λ. RCV could be derived from CV through this algorithm. Compared with traditional algorithms,when CV was larger,the difference between the 2 algorithms was significant. Conclusions This study establishes a new algorithm for RCV. Compared with traditional algorithms,this algorithm is more scientific and helpful for the clinical popularization and the application of RCV. This study analyzes the relationship between the fluctuation reference interval,RCV and CV through the algorithm,and these 3 factors could be converted to each other.

Key words: Reference change value, Coefficient of variation, Fluctuation, Reference interval

CLC Number:

R446.1

YUE Bo, LI Danjie, TANG Dahai, LIU Manjiao, HE Jialei, JIANG Mengjie, WEI Xiaoqiang. Establishment of a new algorithm for the reference interval of relative change values and application evaluation[J]. Laboratory Medicine, 2021, 36(6): 667-673.

Figures/Tables 8

References 20

[1]	HARRIS E K, YASAKA T. On the calculation of a "reference change" for comparing two consecutive measurements[J]. Clin Chem, 1983,29(1):25-30. DOI URL
[2]	FRASER C G, STEVENSON H P, KENNEDY IAN M G. Biological variation data are necessary prerequisites for Objective autoverification of clinical laboratory data[J]. Accreditation and Quality Assurance, 2002,7(11):455-460. DOI URL
[3]	PINEDA-TENOR D, LASERNA-MENDIETA E J, TIMÓN-ZAPATA J, et al. Biological variation and reference change values of common clinical chemistry and haematologic laboratory analytes in the elderly population[J]. Clin Chem Lab Med, 2013,51(4):851-862.
[4]	TÄGER T, SCHELL M, CEBOLA R, et al. Biological variation,reference change value(RCV) and minimal important difference(MID) of inspiratory muscle strength(PImax) in patients with stable chronic heart failure[J]. Clin Res Cardiol, 2015,104(10):822-830. DOI URL
[5]	FRASER C G, HARRIS E K. Generation and application of data on biological variation in clinical chemistry[J]. Crit Rev Clin Lab Sci, 1989,27(5):409-437. DOI URL
[6]	郭玮, 宋斌斌, 沈隽霏, 等. 基于实验室数据信息库建立丙氨酸转氨酶生物参考区间[J]. 中华医学杂志, 2015,95(32):2599-2602.
[7]	WALZ B, FIERZ W. The concept of reference change values(RCV). Will it supersede reference intervals?[J]. Ther Umsch, 2015,72(2):130-135. DOI URL
[8]	RØRAAS T, STØVE B, PETERSEN P H, et al. Biological variation:the effect of different distributions on estimated within-person variation and reference change values[J]. Clin Chem, 2016,62(5):725-736. DOI URL
[9]	PLEBANI M, LIPPI G. Biological variation and reference change values:an essential piece of the puzzle of laboratory testing[J]. Clin Chem Lab Med, 2012,50(2):189-190.
[10]	FRANKENSTEIN L, WU A H, HALLERMAYER K, et al. Biological variation and reference change value of high-sensitivity troponin T in healthy individuals during short and intermediate follow-up periods[J]. Clin Chem, 2011,57(7):1068-1071. DOI URL
[11]	KAWANO R, ICHIHARA K, WADA T. Derivation of level-specific reference change values(RCV) from a health screening database and optimization of their thresholds based on clinical utility[J]. Clin Chem Lab Med, 2016,54(9):1517-1529. DOI URL
[12]	FOKKEMA M R, HERRMANN Z, MUSKIET F A, et al. Reference change values for brain natriuretic peptides revisited[J]. Clin Chem, 2006,52(8):1602-1603. DOI URL
[13]	岳波, 刘曼娇, 唐大海, 等. 血细胞参数个性化参考区间的建立及验证[J]. 临床检验杂志, 2017,35(2):107-110.
[14]	岳波, 刘曼娇, 唐大海, 等. 常规体检生物化学项目波动性参考区间的建立与验证[J]. 临床检验杂志, 2018,36(6):418-421.
[15]	JONES G R D. Estimates of within-subject biological variation derived from pathology databases:an approach to allow assessment of the effects of age,sex,time between sample collections,and analyte concentration on reference change values[J]. Clin Chem, 2019,65(4):579-588. DOI URL
[16]	张利, 何瑶. 肿瘤标志物的参考变化值和参考变化因子比较[J]. 检验医学, 2019,34(11):991-993.
[17]	李小玲, 张玫, 黄亨建. 甲状腺功能检测参考变化值及质量规范的应用[J]. 国际检验医学杂志, 2015,36(4):506-507.
[18]	Clinical and Laboratory Standards Institute. Defining,establishing,and verifying reference intervals in the clinical laboratory[S]. EP28-A3c,CLSI, 2010 .
[19]	陈红燕, 裘海文. 检验结果参考变化值建立的探讨[J]. 检验医学, 2015,30(5):529-532.
[20]	陈政君, 张晨, 宋斌斌, 等. 常规生化检验项目生物学变异的研究[J]. 中华检验医学杂志, 2012,35(10):926-931.

CV/%	F_C	CI_λ	RCV	CV/%	F_C	CI_λ	RCV
0.1	0.002 7	0.997~1.003	-0.003~0.003	29.1	0.945 5	0.388~2.574	-0.612~1.574
0.2	0.005 5	0.995~1.006	-0.005~0.006	29.2	0.950 0	0.387~2.586	-0.613~1.586
0.3	0.008 2	0.992~1.008	-0.008~0.008	29.3	0.954 4	0.385~2.597	-0.615~1.597
0.4	0.011 0	0.989~1.011	-0.011~0.011	29.4	0.958 9	0.383~2.609	-0.617~1.609
0.5	0.013 7	0.986~1.014	-0.014~0.014	29.5	0.963 4	0.382~2.621	-0.618~1.621
0.6	0.016 5	0.984~1.017	-0.016~0.017	29.6	0.968 0	0.380~2.633	-0.620~1.633
0.7	0.019 2	0.981~1.019	-0.019~0.019	29.7	0.972 5	0.378~2.645	-0.622~1.645
0.8	0.022 0	0.978~1.022	-0.022~0.022	29.8	0.977 1	0.376~2.657	-0.624~1.657
0.9	0.024 7	0.976~1.025	-0.024~0.025	29.9	0.981 6	0.375~2.669	-0.625~1.669
1.0	0.027 5	0.973~1.028	-0.027~0.028	30.0	0.986 2	0.373~2.681	-0.627~1.681

CV/%	F_C	CI_λ	RCV	CV/%	F_C	CI_λ	RCV
0.1	0.002 7	0.997~1.003	-0.003~0.003	29.1	0.945 5	0.388~2.574	-0.612~1.574
0.2	0.005 5	0.995~1.006	-0.005~0.006	29.2	0.950 0	0.387~2.586	-0.613~1.586
0.3	0.008 2	0.992~1.008	-0.008~0.008	29.3	0.954 4	0.385~2.597	-0.615~1.597
0.4	0.011 0	0.989~1.011	-0.011~0.011	29.4	0.958 9	0.383~2.609	-0.617~1.609
0.5	0.013 7	0.986~1.014	-0.014~0.014	29.5	0.963 4	0.382~2.621	-0.618~1.621
0.6	0.016 5	0.984~1.017	-0.016~0.017	29.6	0.968 0	0.380~2.633	-0.620~1.633
0.7	0.019 2	0.981~1.019	-0.019~0.019	29.7	0.972 5	0.378~2.645	-0.622~1.645
0.8	0.022 0	0.978~1.022	-0.022~0.022	29.8	0.977 1	0.376~2.657	-0.624~1.657
0.9	0.024 7	0.976~1.025	-0.024~0.025	29.9	0.981 6	0.375~2.669	-0.625~1.669
1.0	0.027 5	0.973~1.028	-0.027~0.028	30.0	0.986 2	0.373~2.681	-0.627~1.681

项目	CV_I	CV_A	CV_T	传统算法		新算法
项目	CV_I	CV_A	CV_T	RCV下限	RCV上限	RCV下限	RCV上限
甲胎蛋白	12.0	4.45	12.8	-35.5	35.5	-30.5	43.9
癌胚抗原	12.7	2.78	13.0	-36.0	36.0	-30.9	44.8
糖类抗原125	24.7	11.67	27.3	-75.7	75.7	-58.0	138.3
糖类抗原15-3	6.1	2.35	6.5	-18.1	18.1	-16.6	20.0
糖类抗原19-9	16.0	6.35	17.2	-47.7	47.7	-39.4	65.0
游离前列腺特异性抗原	18.1	3.12	18.4	-50.9	50.9	-41.6	71.3
总前列腺特异性抗原	18.1	3.13	18.4	-50.9	50.9	-41.6	71.3
促甲状腺激素	19.3	2.79	19.5	-54.1	54.1	-43.8	77.9
甲状腺素	4.9	3.61	6.1	-16.9	16.9	-15.6	18.4
三碘甲状腺原氨酸	6.9	4.23	8.1	-22.4	22.4	-20.3	25.4
游离甲状腺素	5.7	3.73	6.8	-18.9	18.9	-17.3	20.9
游离三碘甲状腺原氨酸	7.9	3.37	8.6	-23.8	23.8	-21.4	27.2

项目	CV_I	CV_A	CV_T	传统算法		新算法
项目	CV_I	CV_A	CV_T	RCV下限	RCV上限	RCV下限	RCV上限
甲胎蛋白	12.0	4.45	12.8	-35.5	35.5	-30.5	43.9
癌胚抗原	12.7	2.78	13.0	-36.0	36.0	-30.9	44.8
糖类抗原125	24.7	11.67	27.3	-75.7	75.7	-58.0	138.3
糖类抗原15-3	6.1	2.35	6.5	-18.1	18.1	-16.6	20.0
糖类抗原19-9	16.0	6.35	17.2	-47.7	47.7	-39.4	65.0
游离前列腺特异性抗原	18.1	3.12	18.4	-50.9	50.9	-41.6	71.3
总前列腺特异性抗原	18.1	3.13	18.4	-50.9	50.9	-41.6	71.3
促甲状腺激素	19.3	2.79	19.5	-54.1	54.1	-43.8	77.9
甲状腺素	4.9	3.61	6.1	-16.9	16.9	-15.6	18.4
三碘甲状腺原氨酸	6.9	4.23	8.1	-22.4	22.4	-20.3	25.4
游离甲状腺素	5.7	3.73	6.8	-18.9	18.9	-17.3	20.9
游离三碘甲状腺原氨酸	7.9	3.37	8.6	-23.8	23.8	-21.4	27.2