Dr Bill Bartlett · Multivariate Time Specified ... interpretation of laboratory data. ... will:- enable production of relevant reference values enable effective application of clinical

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


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


Full Circle?

1 WEEK LATER


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