This document discusses biological variation in clinical measurements. It aims to identify the nature of biological variation, appreciate its significance, and understand how to determine and apply indices of biological variation. Biological variation refers to components of variance in biochemical measurements determined by a subject's physiology. The sources, quantification, and practical applications of biological variation data are explored. Understanding biological variation is fundamental to developing reference data and interpreting clinical measurements over time.

1. Biological VariationBiological Variation
Dr WA BartlettDr WA Bartlett
Biochemical MedicineBiochemical Medicine
Ninewells Hospital & Medical SchoolNinewells Hospital & Medical School
DundeeDundee
ScotlandScotland

2. ObjectivesObjectives
Identification the nature of biologicalIdentification the nature of biological
variation.variation.
Appreciation of the significance ofAppreciation of the significance of
biological variation in clinicalbiological variation in clinical
measurements.measurements.
Attain insight into the determination andAttain insight into the determination and
application of indices of biologicalapplication of indices of biological
variation.variation.

3. Identification the nature ofIdentification the nature of
biological variation.biological variation.
What is meant by the termWhat is meant by the term
biological variation in the contextbiological variation in the context
of clinical biochemistry?of clinical biochemistry?
A component of the variance inA component of the variance in
biochemical measurementsbiochemical measurements
determined by the physiology ofdetermined by the physiology of
the subjects observed.the subjects observed.

4. Components of Variance inComponents of Variance in
Clinical ChemistryClinical Chemistry
MeasurementsMeasurements
Analytical variance.Analytical variance.
Within Subject biological variance.Within Subject biological variance.
Between Subject biological variance.Between Subject biological variance.

5. Biological VariationBiological Variation
All clinical chemistry measurementsAll clinical chemistry measurements
change with time.change with time.
Knowledge of temporal changes useful inKnowledge of temporal changes useful in
diagnosis and interpretation.diagnosis and interpretation.
Rate of change may be useful in prognosis.Rate of change may be useful in prognosis.
Understanding of the sources of biologicalUnderstanding of the sources of biological
variation in non-diseased subjects isvariation in non-diseased subjects is
fundamental to the development offundamental to the development of
reference data.reference data.

6. Sources of BiologicalSources of Biological
VariationVariation
Biological Rhythms (time)Biological Rhythms (time)
HomeostasisHomeostasis
AgeAge
SexSex
EthnicityEthnicity
PathologyPathology
StimuliStimuli

7. Practical significance ofPractical significance of
biological variation.biological variation.
What is the significance of this result?What is the significance of this result?
Is the performance of the analyticalIs the performance of the analytical
method appropriate (imprecision,method appropriate (imprecision,
accuracy)?accuracy)?
When should I measure it again?When should I measure it again?
Has this result changed significantly overHas this result changed significantly over
time?time?
Changes in variability be used as a tool?Changes in variability be used as a tool?

8. Models of Biological VariationModels of Biological Variation
Assume values represent randomAssume values represent random
fluctuation around a homeostatic settingfluctuation around a homeostatic setting
point.point.
More general model allows correlationMore general model allows correlation
between successive results. (between successive results. (Time seriesTime series
and non-decayed biological variationand non-decayed biological variation))

9. Quantifying BiologicalQuantifying Biological
VariationVariation
How are you going to quantify biologicalHow are you going to quantify biological
variation?variation?
You have to dissect out theYou have to dissect out the
components of variance:components of variance: --
σσ22
totaltotal == σσ22
AnalyticalAnalytical ++ σσ22
IndividualIndividual ++ σσ22
GroupGroup

10. Quantifying BiologicalQuantifying Biological
VariationVariation
σ2
Analytical=
σ2
Individual=
σ2
Group =
Average variance of replicate assaysAverage variance of replicate assays
within run analytical variancewithin run analytical variance
Average biological within subjectAverage biological within subject
variance.variance.
Average Variance around theAverage Variance around the
homeostatic setting pointhomeostatic setting point
Variance of true means among subjects.Variance of true means among subjects.
Variance in homeostatic setting pointsVariance in homeostatic setting points

11. Analytical
Variance
Within Subject
Variance
* *
* *
* * Subject 1
* *
* *
* *
* *
* *
* *
* *
* * Subject 2
* *
* *
* *
Between Subject
Variance
* *
* *
* * Subject 3
* *
* *
* *
* *

12. Quantifying BiologicalQuantifying Biological
VariationVariation
How do you do the experiment?How do you do the experiment?
 SubjectsSubjects How many?How many?
 Collect specimensCollect specimens Number? Frequency?Number? Frequency?
 Analyse specimensAnalyse specimens MinimiseMinimise σσ22
AnalyticalAnalytical ??
 Analyse dataAnalyse data Outliers? Statistics?Outliers? Statistics?
 Apply results of analysis.Apply results of analysis.

13. Quantifying BiologicalQuantifying Biological
VariationVariation
Estimates of biological variation areEstimates of biological variation are
similar regardless of: -similar regardless of: -
Number of subjectsNumber of subjects
Time scale of study (Short v Long?)Time scale of study (Short v Long?)
GeographyGeography
A lot of information can be obtainedA lot of information can be obtained
from small studies.from small studies.

14. Within Subject Variation (CVWithin Subject Variation (CVII,%) for Serum Sodium and Urea,%) for Serum Sodium and Urea
No. ofNo. of TimeTime SexSexbb
statusstatus NaNa++
UreaUrea
subjectssubjects
1111 0.5 h0.5 h mm HH 0.60.6 2.22.2
1111 8 h8 h mm HH 0.50.5 6.06.0
6262 1 d1 d HH 0.60.6 4.84.8
1111 2 weeks2 weeks mm HH 0.70.7 12.312.3
1010 4 weeks4 weeks mm HH 0.90.9 14.314.3
1414 8 weeks8 weeks FF HH 0.50.5 11.311.3
111111 15 weeks15 weeks mm HH 0.60.6 15.715.7
3737 22 weeks22 weeks mm HH 0.50.5 11.111.1
274274 6 months6 months -- HH 0.50.5 11.211.2
1515 40 weeks40 weeks -- HH 0.70.7 13.913.9
99 2 d2 d -- RFRF 0.80.8 6.56.5
1515 6 weeks6 weeks FF HPHP 0.80.8 14.514.5
1616 8 weeks8 weeks mm DMDM 0.80.8 13.013.0

15. Collection of Specimens.Collection of Specimens.
 Conditions should minimise pre-analyticalConditions should minimise pre-analytical
variables.variables.
Healthy subjects.Healthy subjects.
Usual life styles.Usual life styles.
No drugs (alcohol, smoking?).No drugs (alcohol, smoking?).
Phlebotomy by same person.Phlebotomy by same person.
Same time of day at regular intervals.Same time of day at regular intervals.
Set protocol for sample transport, processing &Set protocol for sample transport, processing &
storage.storage.

16. Analysis of SpecimensAnalysis of Specimens
Need to minimise analytical imprecision.Need to minimise analytical imprecision.
Ideal : -Ideal : -
Single lots of reagents and calibrants.Single lots of reagents and calibrants.
Single analyst and analytical system.Single analyst and analytical system.
Single or very small number ofSingle or very small number of
batches.batches.

17. Preferred Protocol:Preferred Protocol: CotloveCotlove et alet al
Healthy subjects.Healthy subjects.
Specimens taken at set time intervals.Specimens taken at set time intervals.
Specimens processed & stored frozen.Specimens processed & stored frozen.
When ALL specimens are available: -When ALL specimens are available: -
Analysis of all samples in a single run.Analysis of all samples in a single run.
Simultaneous replicate analysis.Simultaneous replicate analysis.
Quality control to monitor driftQuality control to monitor drift

18. Preferred Protocol:Preferred Protocol: CotloveCotlove et alet al
Advantage: -Advantage: -
Minimisation ofMinimisation of σσ22
AnalyticalAnalytical
Disadvantages: -Disadvantages: -
Limits the number of specimens and subjectsLimits the number of specimens and subjects
that can be studied.that can be studied.
Analyte must be stable on storage.Analyte must be stable on storage.

19. Other Protocols:Other Protocols: CostongsCostongs et alet al
 Collection and storage as before.Collection and storage as before.
 Singleton assay of all samples in a singleSingleton assay of all samples in a single
run.run.
 Duplicate assay of QC or patient pool toDuplicate assay of QC or patient pool to
estimateestimate σσ22
AnalyticalAnalytical

20. Other Protocols:Other Protocols: CostongsCostongs et alet al
Disadvantages: -Disadvantages: -
 True estimate ofTrue estimate of σσ22
AnalyticalAnalytical ??
Integrity of QC materialsIntegrity of QC materials
 Viral infections of poolsViral infections of pools
Vial to vial variability in QCVial to vial variability in QC

21. Other Protocols:Other Protocols: Costongs/MosesCostongs/Moses et alet al
Samples assayed once or in duplicate onSamples assayed once or in duplicate on
the day of collectionthe day of collection
Disadvantage: -Disadvantage: -
σσ22
individualindividual confounded by between batchconfounded by between batch
variance.variance.
Advantage: -Advantage: -
Useful if analyte is unstableUseful if analyte is unstable..

22. Analysis of DataAnalysis of Data
2 Stages2 Stages
– Identification of outliersIdentification of outliers
– Nested analysis of varianceNested analysis of variance

23. Analytical
Variance
Within Subject
Variance
* *
* *
* * Subject 1
* *
* *
* *
* *
* *
* *
* *
* * Subject 2
* *
* *
* *
Between Subject
Variance
* *
* *
* * Subject 3
* *
* *
* *
* *

24. Applications of BV DataApplications of BV Data
Setting of analytical goals.Setting of analytical goals.
Evaluating the significance of change inEvaluating the significance of change in
serial results.serial results.
Assessing the utility of referenceAssessing the utility of reference
intervals.intervals.
Assessing number of specimens requiredAssessing number of specimens required
to estimate homeostatic set points.to estimate homeostatic set points.

25. Applications of BV DataApplications of BV Data
Assessment of reporting strategies.Assessment of reporting strategies.
Selecting the best specimen.Selecting the best specimen.
Comparing utility of available tests.Comparing utility of available tests.

26. Setting of analytical goals.Setting of analytical goals.
Accepted analytical goal for imprecision: -Accepted analytical goal for imprecision: -
CVCVGoalGoal = ½ CV= ½ CVII
therefore: -
CVCVAnalyticalAnalytical = CV= CVGoalGoal
== ¼ of the¼ of the σσ22
Individual if achieved.Individual if achieved.
(Harris. Am J Clin Pathol 1979:72;274)

27. Utility of Analytical GoalsUtility of Analytical Goals
Assessment of methods and equipment.Assessment of methods and equipment.
Should be addressed in early stages ofShould be addressed in early stages of
method development.method development.
Index of Fiduciality: -Index of Fiduciality: -
CVCVAnalyticalAnalytical /CV/CVGoalGoal
If <1 analytical goal metIf <1 analytical goal met
(Fraser Clin Chem 1988:34;995)(Fraser Clin Chem 1988:34;995)

28. Evaluating the significanceEvaluating the significance
of change in serial results.of change in serial results.
 Critical Difference or Reference Change valueCritical Difference or Reference Change value
indicates the value by which 2 serial resultsindicates the value by which 2 serial results
must differ to be considered statisticallymust differ to be considered statistically
significant: -significant: -
CD = 2CD = 2½½
* Z * (CV* Z * (CVAA
22
+ CV+ CVII
22
))½½
Probabilty = 95% Z = 1.96Probabilty = 95% Z = 1.96
Probability = 99% Z = 2.58Probability = 99% Z = 2.58
 Only valid if the variance ofOnly valid if the variance of σσ22
IndividualIndividual isis
homogenous.homogenous.
(Costongs J Clin Chem Clin Biochem 1985;23:7-16)(Costongs J Clin Chem Clin Biochem 1985;23:7-16)

29. Multipliers for (CVMultipliers for (CVAA
22
+ CV+ CVII
22
)) ½½
to Obtain Criticalto Obtain Critical
Difference at Different Levels of ProbabilityDifference at Different Levels of Probability
MultiplierMultiplier 3.643.64 2.772.77 2.332.33 1.811.81 1.471.47 1.191.19 0.950.95
(2(2 ½½
* Z)* Z)
Probability ofProbability of 0.010.01 0.050.05 0.100.10 0.200.20 0.300.30 0.400.40 0.500.50
false alarmfalse alarm
ProbabilityProbability 99%99% 95%95% 90%90% 80%80% 70%70% 60%60% 50%50%

30. Significance of Change?Significance of Change?
63 year old patient: Cholesterol 1 = 6.60 mmol/L63 year old patient: Cholesterol 1 = 6.60 mmol/L
Cholesterol 2 = 5.82 mmol/LCholesterol 2 = 5.82 mmol/L
Significant change ?Significant change ?
Cva = 1.6% CVCva = 1.6% CVII = 6.0%= 6.0%
RCV = 2RCV = 2½½
* Z * (CV* Z * (CVAA
22
+ CV+ CVII
22
))½½
95%RCV = 1.414 * 1.96 * (1.695%RCV = 1.414 * 1.96 * (1.6 ½½
+ 6.60+ 6.60 ½½
)) ½½
= 17.2%= 17.2%
99%RCV =99%RCV = 1.414 * 2.58 * (1.61.414 * 2.58 * (1.6 ½½
+ 6.60+ 6.60 ½½
)) ½½
= 22.6%= 22.6%
Actual Change = ((6.60 – 5.82)/6.60)*100= 11.8%

31. Dispersion =Z* (SDDispersion =Z* (SD22
AA + SD+ SD22
II))
Dispersion of first result = resultDispersion of first result = result ± 1.96 SD± 1.96 SD : -: -
95% level 6.6095% level 6.60 = 5.80 –7.40= 5.80 –7.40
99% level 6.60 = 5.54 – 7.6699% level 6.60 = 5.54 – 7.66
Dispersion of 2 resultDispersion of 2 result
95% level = 5.82 = 5.11 – 6.5395% level = 5.82 = 5.11 – 6.53
99% level = 5.82 = 4.89 – 6.7599% level = 5.82 = 4.89 – 6.75
Overlap: therefore neither significantly or highlyOverlap: therefore neither significantly or highly
significantly differentsignificantly different
Can use the formula to ascertain the probability thatCan use the formula to ascertain the probability that
change is significant. Calculate Z using the (((6.6-change is significant. Calculate Z using the (((6.6-
5.82)/6.6)*100%) as RCV and look up in tables. 82% in5.82)/6.6)*100%) as RCV and look up in tables. 82% in
this case.this case.

32. USE of RCVUSE of RCV
Handbooks reports, 95% and 99%
probabilities that change is significant.
(> or >> * or **)
Delta checking, exemption reporting.
– 95% auto validate, 99% refer for clinical
validation or renanalysis.

33. Index of HeterogeneityIndex of Heterogeneity
 Measure of the heterogeneity of varianceMeasure of the heterogeneity of variance withinwithin
the study population: -the study population: -
ratio of the observed CV of the set of subjectsratio of the observed CV of the set of subjects
variancesvariances (SD(SDA+IA+I
22
)) to theto the theoreticaltheoretical CV ( / 2/n-1)CV ( / 2/n-1)
for the set.for the set.
 The ratio should =1The ratio should =1 (1SD = 1/ /2n )(1SD = 1/ /2n )
 Large ratio = more heterogeneity.Large ratio = more heterogeneity.
(Costongs J Clin Chem Clin Biochem 1985;23:7-16)(Costongs J Clin Chem Clin Biochem 1985;23:7-16)

34. Assessing the utility ofAssessing the utility of
reference intervalsreference intervals..
 Utility of population based reference data?Utility of population based reference data?
 Ratio of Within to Between subject variances.Ratio of Within to Between subject variances.
Index of Individuality = CVIndex of Individuality = CVII / CV/ CVGG
Population Ref Intervals: -Population Ref Intervals: -
IndexIndex <<0.6 = Limited in Value0.6 = Limited in Value
IndexIndex >>1.4 = Applicable1.4 = Applicable

35. Biological Variation &Utility of ReferenceBiological Variation &Utility of Reference
IntervalsIntervals

36. Number of specimensNumber of specimens
required to estimaterequired to estimate
homeostatic set pointshomeostatic set points..
n = ( Z. CVn = ( Z. CVA+A+ II/D)/D)
where: -where: -
Z =Z = number of Standard deviates for anumber of Standard deviates for a
stated probablity (e.g. 1.96 for 95%).stated probablity (e.g. 1.96 for 95%).
D =D = desired % closeness homeostatic setdesired % closeness homeostatic set
point.point.

37. Number of specimens required toNumber of specimens required to
estimate homeostatic set pointsestimate homeostatic set points: -: -
Cholesterol testingCholesterol testing
How many samples (n) required toHow many samples (n) required to
estimate set point within ±5% given: -estimate set point within ±5% given: -
CVCVII = 4.9%= 4.9% CVCVAA = 3% (Recommended)= 3% (Recommended)
Substitute equationSubstitute equation: -: -
n = ( Z. CVn = ( Z. CVA+A+ II/D)/D)
n =n =[1.96·(3[1.96·(322
+ 4.9+ 4.922
))½½
/5]/5]22
= 5.07= 5.07

38. RCV at 95% and Number. of Specimens RequiredRCV at 95% and Number. of Specimens Required
to Assess the Homeostatic Set Point at Different Levels of Imprecisionto Assess the Homeostatic Set Point at Different Levels of Imprecision
CVCVAA CVCVII RCVRCVaa
Number ofNumber of
(%)(%) (%)(%) (%)(%) specimensspecimensbb
2.02.0 4.74.7 14.114.1 44
3.03.0 4.74.7 15.415.4 55
4.04.0 4.74.7 17.117.1 66
5.05.0 4.74.7 19.019.0 77
6.06.0 4.74.7 21.121.1 99
7.07.0 4.74.7 23.423.4 1111
8.08.0 4.74.7 25.725.7 1313
9.09.0 4.74.7 28.128.1 1616
10.010.0 4.74.7 30.630.6 1919
15.015.0 4.74.7 43.543.5 3838
20.020.0 4.74.7 56.956.9 6565
aa
RCV (pRCV (p <<0.05) = 2.77 (CV0.05) = 2.77 (CVAA
22
+ CV+ CVII
22
))½½
, assuming no statistical evidence of heterogenity, assuming no statistical evidence of heterogenity
bb
Number = mean result is withinNumber = mean result is within ±±5%of homeostatic set point1.965%of homeostatic set point1.9622
x (CVx (CVAA
22
+ CV+ CVII
22
)) ½½
/25./25.

39. Assessment of reportingAssessment of reporting
strategiesstrategies
Results may be reported in differentResults may be reported in different
formatsformats
e.g. 24h Urinary creatinine output: -e.g. 24h Urinary creatinine output: -
CVCVII for concentration = 23.8%for concentration = 23.8%
CVCVII for output per collection = 13.0%for output per collection = 13.0%
CD for concentration = 66.0%CD for concentration = 66.0%
CD for output = 36.2%CD for output = 36.2%

40. Selecting best Specimen.Selecting best Specimen.
e.g early morning urines for albumine.g early morning urines for albumin
versus 24h collections.versus 24h collections.
Random hormone measurements versusRandom hormone measurements versus
timed measurements.timed measurements.

41. Comparing Available TestsComparing Available Tests
Creatinine v Creatinine ClearanceCreatinine v Creatinine Clearance
FT4 v TSH in replacement situationsFT4 v TSH in replacement situations
FT4 v Total T4FT4 v Total T4

42. Reference IntervalsReference Intervals
Dr WA BartlettDr WA Bartlett
Birmingham Heartlands & SolihullBirmingham Heartlands & Solihull
NHS Trust (Teaching)NHS Trust (Teaching)