Dr Bill BartlettDr Bill BartlettJoint Clinical DirectorJoint Clinical DirectorDiagnostics GroupDiagnostics GroupBiochemical MedicineBiochemical MedicineNinewells Hospital & Medical Ninewells Hospital & Medical SchoolSchoolNHS TaysideNHS TaysideScotland UKScotland UK

Bill.Bartlett@nhs.netBill.Bartlett@nhs.net

• DiagnosisDiagnosis• PrognosisPrognosis• Monitoring Monitoring • ScreeningScreening• Assessment Assessment of Riskof Risk

The metrology An understanding of its relativity to a

point of reference Unusual Change

Biological Rhythms (time)Biological Rhythms (time) HomeostasisHomeostasis Age Age SexSex EthnicityEthnicity PathologyPathology Response to StimuliResponse to Stimuli

eGFR > 60 in a 30 year old white female: Changing renal function?

Grasbeck & Saris 1969Grasbeck & Saris 1969Introduced the term “reference value”:Introduced the term “reference value”:

The mode of generation of such values is known The mode of generation of such values is known with respect to: -with respect to: -

Selection of subjectsSelection of subjects Assessment of state of healthAssessment of state of health Population characteristics, age, sex,Population characteristics, age, sex, Specimen collection and storageSpecimen collection and storage Analytical technique and performance Analytical technique and performance

characteristicscharacteristics Data handling techniques. Data handling techniques.

1.1. The Concept of Reference Values. The Concept of Reference Values. 1987;25:337-1987;25:337-342342

2.2. The selection of Individuals for the The selection of Individuals for the Production of reference values. Production of reference values. 1987;25:639-6441987;25:639-644

3.3. Preparation of individuals and collection Preparation of individuals and collection of specimens for the production of of specimens for the production of reference intervals. reference intervals. 1988;26:593-5981988;26:593-598

4.4. Control of analytical variability in the Control of analytical variability in the production of reference values. production of reference values. 1991;29:531-5351991;29:531-535

5.5. Statistical treatment of collected Statistical treatment of collected reference limits. reference limits. 1987;25:645-6561987;25:645-656

6.6. Presentation of observed values related Presentation of observed values related to reference values. to reference values. 1987;25:657-6621987;25:657-662

J Clin Chem Clin Biochem J Clin Chem Clin Biochem

This looks nice so far , but

what is the use of biological

variation data?

Analytical variance (CVAnalytical variance (CVAA ). ).

Within Subject biological variance Within Subject biological variance

(CV(CVII ). ).

Between Subject biological variance Between Subject biological variance

(CV(CVGG ).. )..

Total Total = =

Analytical Analytical ++ Individual Individual + +

GroupGroup

Setting of analytical goals (CVSetting of analytical goals (CVgoalgoal).). Quality specifications for : Quality specifications for :

total allowable error (TEtotal allowable error (TEAA))

Bias (BBias (BAA ) ) Evaluating the significance of change in Evaluating the significance of change in

serial results (RCV).serial results (RCV). Assessing the utility of reference intervals Assessing the utility of reference intervals

(Index of Individuality).(Index of Individuality). Assessing number of specimens required to Assessing number of specimens required to

estimate homeostatic set points.estimate homeostatic set points. Choice of specimen type.Choice of specimen type. Timing of specimens.Timing of specimens.

These These fundamental datafundamental data have many have many applications that under-pin our practice.applications that under-pin our practice.

We need to have We need to have confidenceconfidence in the data in the data and understand its limitations.and understand its limitations.

Should we not have Should we not have standardsstandards for for their production and their production and

characterisation?characterisation?

www.biologicalvariation.com

Generation and Application of data on Biological Variation in Clinical Chemistry: -Fraser CG, Harris EK. Crit Rev Clin Lab Sci 1989:27,(5), 409-435.Optimal Conditions Precision.

Purpose of study Experimental Design Characterisation of the methods Data analysis Confidence limits

What are the potential What are the potential impacts of error in the impacts of error in the data?data?

Biological Variation DatabaseBiological Variation Databasewww.westgard.com/biodatabase1.htm

CVCVI I == 5.3% CV5.3% CVG G = 14.2%= 14.2%

DesirableCVA < 0.5 x CVI

BA< 0.25 x (CVI2 + CVG2)0.5

Tea < 1.65 x 0.5 x CVI. + 0.25 x (CVI2 + CVG

2)0.5

OptimumCVA < 0.25 x CVI

BA< 0.125 x (CVI2 + CVG2)0.5

Tea < 1.65 x 0.5 x CVI. + 0.125 x (CVI2 + CVG

2)0.5

Minimum

CVA < 0.75 x CVI

BA< 0.0.345 x (CVI2 + CVG2)0.5

Tea < 1.65 x 0.5 x CVI. + 0.375 x (CVI2 + CVG

2)0.5

www.westgard.com/biodatabase1.htm

n = [n = [Z * (CVZ * (CVAA2 2

++ CVCVII22)/D] )/D] 22

D = % of closeness requiredD = % of closeness required

Biological variation data simulator. WWW.biologicalvariation.com

CVCVII = 5.3 % CV = 5.3 % CVG G = 14.2% = 14.2% CVCVAA =2.7% =2.7%

CVCVII = 5.3 % CV = 5.3 % CVG G = 14.2%= 14.2%

Index of individuality = 0.4

Biological Variation Serum Creatinine: Average within subject (CVI) = 4.1%Gowans & Fraser. Ann Clin Biochem 1988:25:259-263

Quantity

Units Group Mean CVI CVGIndex of Individuality

Serum Creatinine

µmol/L Male (7) 83.9 3.4 6.8 0.54 Fraser

µmol/L Female (8)

71.4 4.9 11.8

0.41 Fraser

µmol/L**

Whole (15)

83.9 4.1 14.1

0.29 Fraser

µmol/L ? ? 5.3 14.2

0.4 BioV Site

µmol/L****

N= 20Male (7)Female(13)

77 4.7 14.4

0.33 Reinhard et al

* Jaffe* Jaffe

**** EnzymaticEnzymatic

MM FFGG

MM FFGG

CVCVGG =14.1 =14.1

CVCVGG =4.1 =4.1

Creatinine µmol/LCreatinine µmol/L

Probability (%)Probability (%)

Starting Creatinine

96 µmol/L

Creatinine µmol/LCreatinine µmol/L

Probability (%)Probability (%)

Starting Creatinine

96 µmol/L

Upper Reference Limits: -Upper Reference Limits: - Male = 106 µmol/LMale = 106 µmol/L Female = 80 µmol/LFemale = 80 µmol/L

RCV larger for men than for women.RCV larger for men than for women.

If True: -If True: -• Clinically important as disease progression Clinically important as disease progression

needs to be monitored and appropriate needs to be monitored and appropriate actions taken (e.g. Acute on Chronic Kidney actions taken (e.g. Acute on Chronic Kidney failure).failure).

• Tighter analytical performance Tighter analytical performance characteristics to be applied for females.characteristics to be applied for females.

• Impact will be greater on eGFRImpact will be greater on eGFR

% Change at % % Change at % ProbabilityProbability

CVCVII 95%95% 99%99%

Rise in Rise in CreatinineCreatinine

4.34.3 10.3%10.3% 14.6%14.6%

5.35.3 12.6%12.6% 17.8%17.8%

Fall in eGFRFall in eGFR 4.34.3 12.8%12.8% 15.4%15.4%

6.86.8 16.0%16.0% 22.6%22.6%

Assumes a CVA = 1%

"% Probability that %Rise in Serum Creatinine is Significant

0

5

10

15

20

25

50 55 60 65 70 75 80 85 90 95 100

% R

ise

in C

rea

tin

ine

% Probability that %Rise in Creatinine is Significant

"% Probability that % Fall in eGFR is Significant

0.0

5.0

10.0

15.0

20.0

25.0

50 55 60 65 70 75 80 85 90 95 100

% F

all

in e

GF

R

% Probability that % Fall in eGFR is Significant

Significance of Fall in eGFR at CKD Classification Boundaries

0

5

10

15

20

25

65 70 75 80 85 90 95 100

% Probability that Fall is Significant

Fa

ll in

eG

FR

in m

L/m

in/1

.73

m2 90 mL

60 mL

45 mL

30 mL

15 mL

4 mL/min/1.73m2

Use eGFR for initial classification of CKD stage.

Use creatinine to follow patients with RCV indicator flag? More Precise?

Difficulty is that there is a suggestion that creatinine CVI is variable in disease. Therefore which CVI?

State of HealthState of Health CVCVII Number Number of of

SubjectsSubjects

Length of Length of Studies Studies (days)(days)

Number Number Samples/Samples/SubSub

Healthy Median?Healthy Median? 4.34.3

CRFCRF 5.35.3 1717 2121 88

Type 1 DMType 1 DM 5.95.9 2727 5656 88

Impaired renal Impaired renal functionfunction

6.96.9 99 22 1111

Type 1 DMType 1 DM 6.56.5 1111 5656 88

Post renal Post renal transplanttransplant

11.511.5 4141 9090 88

Acute MIAcute MI 13.413.4 2020 44 19.519.5

CKD childrenCKD children 13.013.0 5454 540540 99Ricos et al Ann Clin Biochem 2007;44: 343-352

The LiteratureThe Literature

• 319 Constituents: 319 Constituents: • 90 entries based on 1 Paper90 entries based on 1 Paper

ISSUESISSUES Non-complex Non-complex vv

complex molecules.complex molecules. Improved assay Improved assay

specificity.specificity. CreatinineCreatinine PTHPTH

Longish history of evolving assay systems with differing analytical performance characteristics and specificities.

1970s – C-Terminal RIALate 80s – Sandwich IRMA Assay1990 – 98 Nichols IRMA assays dominateLate 1990s – variety of “intact” sandwich assays on a number of different analytical platforms.2004 – Bioactive PTH assay

Adapted from M Scott Focus 2010

Much evidence in the literature indicating that assays react to varying extents with the variety of PTH fragments present in Serum.

M Scott Focus 2010

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 an important BV qualifier?

Ankrah Tet Ankrah Tet et alet al. Ann Clin Biochem . Ann Clin Biochem 2008;45:167-1692008;45:167-169

PTH = Nichols Advantage PTH = Nichols Advantage 4 Males 6 Females4 Males 6 Females““Normals”Normals”

Gardham et al . Clin J Am Soc Nephrol Gardham et al . Clin J Am Soc Nephrol ePress May 24ePress May 24thth 2010 2010

Abbot Architect Intact PTHAbbot Architect Intact PTHImmunotopics Inc. Biointact PTH 1-84Immunotopics Inc. Biointact PTH 1-8412 “Normals” 22 Haemodialysis patients12 “Normals” 22 Haemodialysis patients

Subjects

n Assay PTHng/L

CVI CVG CVA RCV (%)

N-Set*

“Normal”

10

Nichols 51.7 25.9 23.8 5.0 72.3

27

“Normal”

12

Abbott 51.9 19.2 3.5 54.0

15

ImmunotopicsBio-intact 1-84

27.5 23.8 4.2 67.0

22

Dialysis 22

Abbott 303.0

25.6 3.6 72.0

26

ImmunotopicsBio-intact 1-84

131.0

30.2 6.3 86.0

37* Number of Specimens Required to estimate homeostatic point within 10% with a probability of 95%

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 (CVWithin Subject Variation (CVII,%) for Serum ,%) for Serum

Sodium and UreaSodium and Urea No. ofNo. of TimeTime SexSex statusstatus NaNa++ UreaUrea subjectssubjects

1111 0.5 h0.5 h mm HH 0.60.6 2.22.21111 8 h8 h mm HH 0.50.5 6.06.06262 1 d1 d HH 0.60.6 4.84.81111 2 weeks2 weeks mm HH 0.70.7 12.312.31010 4 weeks4 weeks mm HH 0.90.9 14.314.31414 8 weeks8 weeks FF HH 0.50.5 11.311.3111111 15 weeks15 weeks mm HH 0.60.6 15.715.73737 22 weeks22 weeks mm HH 0.50.5 11.111.1274274 6 months6 months -- HH 0.50.5 11.211.21515 40 weeks40 weeks -- HH 0.70.7 13.913.999 2 d2 d -- RFRF 0.80.8 6.56.51515 6 weeks6 weeks FF HPHP 0.80.8 14.514.51616 8 weeks8 weeks mm DMDM 0.80.8 13.013.0

Fraser 2001

66 quantities 34 disease with 45 references.66 quantities 34 disease with 45 references. ““For the majority of quantities studied CVFor the majority of quantities studied CVII of of

same order same order as diseased. “as diseased. “ Disease specific RCVs Disease specific RCVs may be necessary in may be necessary in

some cases.some cases. Effect of variability in variability not Effect of variability in variability not

quantitatively studied.quantitatively studied. ““Heterogeneity in study designs and Heterogeneity in study designs and

methods compiled”methods compiled”

“Blood samples were taken at weekly intervals from 10 healthy subjects (4 men and 6 women, median age 21 years, range 19–27 years; mean body mass index 21.3, range 19.0–25.9) for six weeks at the same time of the day (between 12:30 and 14:30 h),”

I’m I’m healthy healthy and and normal !normal !I’m a I’m a biochemisbiochemist!t!

• Need to assess on a case by case basis. Need to assess on a case by case basis. • Questions around Questions around uncertaintyuncertainty. .

• What are the implications for their application?What are the implications for their application?• Can the impact of uncertainty be quantified and Can the impact of uncertainty be quantified and

reduced where necessary.reduced where necessary.• Accepted standard Accepted standard needed for their production.needed for their production.• Critical appraisal checklist Critical appraisal checklist required to enable veracity required to enable veracity

of existing and new publications.of existing and new publications.• Meta-analysis of dataMeta-analysis of data

Questions to be addressed by the EFCC biological Questions to be addressed by the EFCC biological Variation Working groupVariation Working group

1.1. Define the purpose for which they are to Define the purpose for which they are to be used.be used.

2.2. Only meaningful and transferable if Only meaningful and transferable if defined for the population or individual in defined for the population or individual in terms of: -terms of: -

Inclusion and exclusion criteriaInclusion and exclusion criteria Intake of food & drugsIntake of food & drugs Physiological and environmental conditionsPhysiological and environmental conditions Specimen collection criteriaSpecimen collection criteria Performance characteristics of the analytical methodPerformance characteristics of the analytical method The statistical methods used for estimation of the limitsThe statistical methods used for estimation of the limits

3.3. State of health defined.State of health defined. WHO Defn: -WHO Defn: -

“ “ a state of complete physical mental and social a state of complete physical mental and social well being and not merely the absence of disease well being and not merely the absence of disease or infirmity”or infirmity”

Disease is a state of health.Disease is a state of health. Conceptually different in different countries.Conceptually different in different countries.

The term “Reference” should be accompanied or The term “Reference” should be accompanied or preceded by a word qualifying the state of health. preceded by a word qualifying the state of health. E.g diabetic, hospitalised diabetic, ambulatory E.g diabetic, hospitalised diabetic, ambulatory diabetic, Healthy laboratory worker?diabetic, Healthy laboratory worker?

The reference change value: a The reference change value: a proposal to interpret laboratory proposal to interpret laboratory reports in serial testing based on reports in serial testing based on biological variation.biological variation.C. RICO´ et al Scand J Clin Lab Invest 2004; 64: 175 – 184

“The RCV data in this study are presented as a The RCV data in this study are presented as a point of departure for a widely applicable point of departure for a widely applicable objective guide to interpret changes in serial objective guide to interpret changes in serial results.”results.”

HL7 recognised conceptRequests for additional flags pending

Fit for Purpose?

Kinoull Hill, Perth Scotland. Ruth Bartlett