Dr Bill Bartlett Blood Sciences,
Ninewells Hospital & Medical School,
NHS Tayside,
Scotland, UK. [email protected]
www.biologicalvariation.com
Biological variation affects the clinical utility of reference values.
An understanding of the nature of biological variation will:-
enable production of relevant reference values
enable effective application of clinical laboratory measurements
We should consider additionally qualifying reference values by description of associated indices of biological variation.
Sodium 140 mmol/L Potassium 4.0 mmol/L Urea 4.2 mmol/L Creatinine 95 µmol/L
25 Year old Male Patient attending a GP surgery: -
(133 –147) (3.5 – 5.0) (2.5 – 7.5) (50 – 120)
1 WEEK LATER
Sodium 138 mmol/L Potassium 4.2 mmol/L Urea 4.8 mmol/L Creatinine 110 µmol/L
Should I be concerned? Point of reference needed
Should I be concerned? Is this different Point of reference needed
An appreciation of analytical uncertainty in measurements.
An understanding of biological variation in the measured parameter
Points of reference (Context specific)
An understanding of the contextual significance of the measured value.
Grasbeck & Saris 1969 Introduced the term “reference value”: The mode of generation of such values is known with
respect to: -
Selection of subjects
Assessment of state of health
Population characteristics, age, sex,
Specimen collection and storage
Analytical technique and performance characteristics
Data handling techniques.
1. The Concept of Reference Values. 1987;25:337-342
2. The selection of Individuals for the Production of reference values. 1987;25:639-644
3. Preparation of individuals and collection of specimens for the production of reference intervals. 1988;26:593-598
4. Control of analytical variability in the production of reference values. 1991;29:531-535
5. Statistical treatment of collected reference limits. 1987;25:645-656
6. Presentation of observed values related to reference values. 1987;25:657-662
J Clin Chem Clin Biochem
Health associated reference values
Subject based reference values
Population based reference values
Univariate
Multivariate
Time Specified
FOCUS of IFCC Documents
Builds on IFCC work
Specifically states, for the “apriori” approach, that the literature should be searched to identify known sources of biological variation: - Exclusion criteria
Partitioning criteria
Effects of biological variation on the analyte dictate criteria for subject selection and preparation.
1. Define the purpose for which they are to be used.
2. Only meaningful and transferable if defined for the population or individual in terms of: - Inclusion and exclusion criteria
Intake of food & drugs
Physiological and environmental conditions
Specimen collection criteria
Performance characteristics of the analytical method
The statistical methods used for estimation of the limits
Utility depends upon Knowledge of Biological Variation
Analytical variance. CVa
Within Subject biological variance. CVi
Between Subject biological variance. CVg
s2Total = s2
Analytical + s2
Individual + s2Group
CVTotal = CVa + CVi + CVg
Analytical
CVa
Within Subject
CVi
* *
* *
* * Subject 1
* *
* *
* *
* *
* *
* *
* *
* * Subject 2
* *
* *
* *
Between Subject
Variance
* *
* *
* * Subject 3
* *
* *
* *
* *
Potassium Alkaline Phosphatase
LRL = Lower reference limit URL = Upper reference limit
X
Highly unusual result for the individual, but inside population reference interval
Reference Range
Ratio of Within to Between subject variances.
Index of Individuality (II) = [CVa2 + CVi
2]1/2 /CVg
≈CVi / CVg (close approximation if CVa <= CVi )
Population Ref Intervals: -
Index <0.6 = Marked individuality
Index >1.4 = Little individuality
Implications for the use of population based ref intervals?
Flagging significance of change?
Potassium
Index of individuality = 0.86 Alkaline Phosphatase
Index of individuality = 0.25
LRL = Lower reference limit URL = Upper reference limit
CVI = 4.8, CVG = 5.6 CVI = 6.4, CVG = 24.8
The majority of analytes demonstrate marked individuality
Need for greater stratification of reference values.
Issues with the data set
Urinary Free Noradrenaline. mol/mmol creatinine Index of individuality
N MEAN CVa CVi CVg CVi / CVg [CVa
2 + CVi2]1/2 /CVg
MIXED SEX 13 20.2 6.3 19.5 28.0 0.69 0.73
FEMALE 6 22.9 5.8 19.5 8.4 2.32 2.42
MALE 6 15.7 7.3 20.1 8.7 2.32 2.45
Where individuality is marked the individual is the best point of reference.
Difference > than combined analytical and biological variation: -
RCV = 2½ * Z * (CVA2
+ CVI2) ½
The Z score determines the level of significance of the change: -
e.g. 1 tailed 95% = 1.65
99% = 2.33
eGFR > 60 in a 30 year old white female: Changing renal function?
Sex Stratified Ref Range
RCV Flag
Reference State: -
The notion of reference state can be used to facilitate transferability of reference value data.
Qualification for Reference Status: -
• 20-30 years old • Ideal body mass • Fasted for 10 hours • No medication • Consuming <45g of
alcohol per day • Smokes <12 cigarettes
per day • No apparent illness
I’m normal ! I’m a Clinical Chemist
Biological Rhythms (time) -
Homeostasis
Age
Sex
Stage of development
Ethnicity
State of well being
Stimuli
Socioeconomic impacts
All provide criteria for stratification of reference values
Characterisation and understanding of biological variation enables a valid assessment of the significance of a laboratory result.
Meta data are required to enable valid selection and application of data.
This should include indices of biological variation
Only meaningful and transferable if defined for the population or individual in terms of: -
Inclusion and exclusion criteria
Intake of food & drugs
Physiological and environmental conditions
Specimen collection criteria
Performance characteristics of the analytical method
The statistical methods used for estimation of the limits
Less tight homeostatic control with age?
Fraser 2001
Analyte Younger CVi Older CVi
Sodium 0.7 0.9
Potassium 5.4 4.6
Chloride 1.2 1.2
Urea 13.9 10.3
Creatinine 4.1 4.3
Calcium 2.1 1.6
Cholesterol 4.9 5.8
Proteins 3.1 2.6
Albumin 2.2 2.6
Age 4 to 18 years
38 analytes: age partitioning required for 6
Creatinine, LDH, AST, ALP, Phosphate, Urate
14 showed marked differences from Westgard adult data
ACE Conc (U/L)
Genotype n Assay 1* Assay 2*
All 159 47 12-82 35 7-62
D/D 47 59 30-89 44 16-71
D/I 73 45 16-75 34 10-57
I/I 39 35 8-62 25 7-44
Genotype corrected reference intervals: SACE *mean +/- 1.96 SD. D = deletion, I = Insertion.
3. State of health defined.
WHO Defn: - “ a state of complete physical mental and social well being and not merely the absence of disease or infirmity”
Disease is a state of health.
Conceptually different in different countries.
The term “Reference” should be accompanied or preceded by a word qualifying the state of health. E.g diabetic, hospitalised diabetic, ambulatory diabetic, Healthy laboratory worker?
66 quantities 34 diseases with 45 references.
“For the majority of quantities studied CVI of same order as diseased. “
Disease specific RCVs may be necessary in some cases.
ISSUES
Non-complex v complex molecules.
Improved assay specificity.
HbA1c
PTH
Creatinine
Study Year Subjects (M:F)
State of Health
Frequency of Sampling
Number of
Samples
Method
1 1985 10(6:4) Healthy 7 D 11 - 27 IE
2 1989 8(?) Diabetic 3-4 D 6 Endosmosis
3 1993 73(?) Diabetic 1 M & 3 M 4 Affin Chrom
4 1994 29 (?) Diabetic 3 M & 12 M ? HPLC IE
5 1998 12(7:5) Healthy 15 D 10 HPLC IE
6 2000 11(0:11) Healthy 7 D 5 HPLC IE
7 2000 47(?) Diabetic 6 M 4 - 7 Imm Turbid
8 2002 45 (45:0) Diabetic 7 D 12 HPLC Affin
9 2010 38(24:14)a Diabetic 1 Y 5 HPLC IE
Study CVI CVG
Analytical
Goal
Desirable
TEA(%)
Bias
Target RCV
N for Homeostatic
Setting point
1 H 1.8 0.9 4.8 1
2D 7.3 10.8 3.6 5.8 2.8 22.6 10
3D 4.2 & 7.1 2.1 & 3.5 13.0 & 22.5 3 & 10
4D 2.4 1.2 7.4 1
5H 1.9 6.8 0.8 3.3 1.8 5.7
6H <0.7 < 0.35 2.9 1
7D
7.9,5.4, 3.9
3.3
3.8,2.7, 1.8 1.4 0.8
24.3,16.7, 11.8 12,6,3
8D 1.7b 0.8
9D 4.8 4.8 14.9 4
H = Healthy D = Diabetic
• C-Terminal RIA
1970’s
• Development of IRMA assays
1980’s
• Nichols institute Ruled the world
• Range of other intact assays with antibodies against a variety of epitopes
1990’s
• Bioactive PTH Assays with n-terminal specific antibodies
2004
PTH Assays through time
If clearance of fragments is not identical in all patients and non diseased patients the apparent biological variation will vary and be assay specific.
Assay specificity is an important BV qualifier
Historical data may not be always applicable.
Data in chronic stable disease “often can be considered constant over time and geography”
“Same order of magnitude in disease and health”
Within Subject Variation (CVI,%) for Serum Sodium and Urea No. of Time Sex status Na+ Urea
subjects
11 0.5 h m H 0.6 2.2
11 8 h m H 0.5 6.0
62 1 d H 0.6 4.8
11 2 weeks m H 0.7 12.3
10 4 weeks m H 0.9 14.3
14 8 weeks F H 0.5 11.3
111 15 weeks m H 0.6 15.7
37 22 weeks m H 0.5 11.1
274 6 months - H 0.5 11.2
15 40 weeks - H 0.7 13.9
9 2 d - RF 0.8 6.5
15 6 weeks F HP 0.8 14.5
16 8 weeks m DM 0.8 13.0
Fraser 2001
Sodium 140 mmol/L Potassium 4.0 mmol/L Urea 4.2 mmol/L Creatinine 95 µmol/L
Full Circle?
1 WEEK LATER
Sodium 138 mmol/L Potassium 4.2 mmol/L Urea 4.8 mmol/L Creatinine 110 µmol/L
Knowledge of biological variation within and between subjects provides a fundamental point of reference to enable interpretation of laboratory data.
Biological variation affects the clinical utility of reference values.
An understanding of the nature of biological variation will:-
enable production of relevant reference values
enable effective application of clinical laboratory measurements
We should consider additionally qualifying reference values by description of associated indices of biological variation.
Biological variation data are reference data