Biological Variation

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Biological Variation

• Dr WA Bartlett
• Biochemical Medicine
• Ninewells Hospital Medical School
• Dundee
• Scotland

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Objectives

• Identification the nature of biological
  variation.
• Appreciation of the significance of biological
  variation in clinical measurements.
• Attain insight into the determination and
  application of indices of biological variation.

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Identification the nature of biological variation.

• What is meant by the term biological variation in
  the context of clinical biochemistry?
• A component of the variance in biochemical
  measurements determined by the physiology of the
  subjects observed.

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Components of Variance in Clinical Chemistry
Measurements

• Analytical variance.
• Within Subject biological variance.
• Between Subject biological variance.

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Biological Variation

• All clinical chemistry measurements change with
  time.
• Knowledge of temporal changes useful in
  diagnosis and interpretation.
• Rate of change may be useful in prognosis.
• Understanding of the sources of biological
  variation in non-diseased subjects is fundamental
  to the development of reference data.

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Sources of Biological Variation

• Biological Rhythms (time)
• Homeostasis
• Age
• Sex
• Ethnicity
• Pathology
• Stimuli

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Practical significance of biological variation.

• What is the significance of this result?
• Is the performance of the analytical method
  appropriate (imprecision, accuracy)?
• When should I measure it again?
• Has this result changed significantly over time?
• Changes in variability be used as a tool?

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Models of Biological Variation

• Assume values represent random fluctuation around
  a homeostatic setting point.
• More general model allows correlation between
  successive results. (Time series and non-decayed
  biological variation)

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Quantifying Biological Variation

• How are you going to quantify biological
  variation?

• You have to dissect out the components of
  variance -
• s2total s2Analytical s2Individual s2Group

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Quantifying Biological Variation

• s2Analytical
• s2Individual
• s2Group

Average variance of replicate assays within run
analytical variance
Average biological within subject
variance. Average Variance around the
homeostatic setting point
Variance of true means among subjects. Variance
in homeostatic setting points
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Quantifying Biological Variation

• How do you do the experiment?
• Subjects How many?
• Collect specimens Number? Frequency?
• Analyse specimens Minimise s2Analytical ?
• Analyse data Outliers? Statistics?
• Apply results of analysis.

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Quantifying Biological Variation

• Estimates of biological variation are similar
  regardless of -
• Number of subjects
• Time scale of study (Short v Long?)
• Geography
• A lot of information can be obtained from small
  studies.

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Within Subject Variation (CVI,) for Serum Sodium
and Urea No. of Time Sexb 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
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Collection of Specimens.

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

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Analysis of Specimens

• Need to minimise analytical imprecision.
• Ideal -
• Single lots of reagents and calibrants.
• Single analyst and analytical system.
• Single or very small number of batches.

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Preferred Protocol Cotlove et al

• Healthy subjects.
• Specimens taken at set time intervals.
• Specimens processed stored frozen.
• When ALL specimens are available -
• Analysis of all samples in a single run.
• Simultaneous replicate analysis.
• Quality control to monitor drift

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Preferred Protocol Cotlove et al

• Advantage -
• Minimisation of s2Analytical
• Disadvantages -
• Limits the number of specimens and subjects that
  can be studied.
• Analyte must be stable on storage.

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Other Protocols Costongs et al

• Collection and storage as before.
• Singleton assay of all samples in a single run.
• Duplicate assay of QC or patient pool to
  estimate s2Analytical

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Other Protocols Costongs et al

• Disadvantages -
• True estimate of s2Analytical ?
• Integrity of QC materials
• Viral infections of pools
• Vial to vial variability in QC

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Other Protocols Costongs/Moses et al

• Samples assayed once or in duplicate on the day
  of collection
• Disadvantage -
• s2individual confounded by between batch
  variance.
• Advantage -
• Useful if analyte is unstable.

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Analysis of Data

• 2 Stages
• Identification of outliers
• Nested analysis of variance

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Applications of BV Data

• Setting of analytical goals.
• Evaluating the significance of change in serial
  results.
• Assessing the utility of reference intervals.
• Assessing number of specimens required to
  estimate homeostatic set points.

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Applications of BV Data

• Assessment of reporting strategies.
• Selecting the best specimen.
• Comparing utility of available tests.

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Setting of analytical goals.

• Accepted analytical goal for imprecision -
• CVGoal ½ CVI
• therefore -
• CVAnalytical CVGoal
• ¼ of the s2Individual if achieved.
• (Harris. Am J Clin Pathol 197972274)

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Utility of Analytical Goals

• Assessment of methods and equipment.
• Should be addressed in early stages of method
  development.
• Index of Fiduciality -
• CVAnalytical /CVGoal
• If lt1 analytical goal met
• (Fraser Clin Chem 198834995)

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Evaluating the significance of change in serial
results.

• Critical Difference or Reference Change value
  indicates the value by which 2 serial results
  must differ to be considered statistically
  significant -
• CD 2½ Z (CVA2 CVI2)½
• Probabilty 95 Z 1.96
• Probability 99 Z 2.58
• Only valid if the variance of s2Individual is
  homogenous.
• (Costongs J Clin Chem Clin Biochem
  1985237-16)

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Multipliers for (CVA2 CVI2) ½ to Obtain
Critical Difference at Different Levels of
Probability Multiplier 3.64 2.77 2.33 1.81 1.47
1.19 0.95 (2 ½ Z) Probability
of 0.01 0.05 0.10 0.20 0.30 0.40 0.50 false
alarm Probability 99 95 90 80 70 60 50
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Significance of Change? 63 year old patient
Cholesterol 1 6.60 mmol/L
Cholesterol 2 5.82 mmol/L Significant change ?
Cva 1.6 CVI 6.0 RCV 2½ Z
(CVA2 CVI2)½ 95RCV 1.414 1.96 (1.6 ½
6.60 ½) ½ 17.2 99RCV 1.414 2.58 (1.6 ½
6.60 ½) ½ 22.6
Actual Change ((6.60 5.82)/6.60)100 11.8
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Dispersion Z (SD2A SD2I) Dispersion of
first result result 1.96 SD - 95 level
6.60 5.80 7.40 99 level 6.60 5.54
7.66 Dispersion of 2 result 95 level 5.82
5.11 6.53 99 level 5.82 4.89
6.75 Overlap therefore neither significantly or
highly significantly different Can use the
formula to ascertain the probability that change
is significant. Calculate Z using the
(((6.6-5.82)/6.6)100) as RCV and look up in
tables. 82 in this case.
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USE of RCV

• Handbooks reports, 95 and 99 probabilities
  that change is significant.
• (gt or gtgt or )
• Delta checking, exemption reporting.
• 95 auto validate, 99 refer for clinical
  validation or renanalysis.

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Index of Heterogeneity

• Measure of the heterogeneity of variance within
  the study population -
• ratio of the observed CV of the set of subjects
  variances (SDAI2) to the theoretical CV ( /
  2/n-1) for the set.
• The ratio should 1 (1SD 1/ /2n )
• Large ratio more heterogeneity.
• (Costongs J Clin Chem Clin Biochem 1985237-16)

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Assessing the utility of reference intervals.

• Utility of population based reference data?
• Ratio of Within to Between subject variances.
• Index of Individuality CVI / CVG
• Population Ref Intervals -
• Index lt0.6 Limited in Value
• Index gt1.4 Applicable

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Biological Variation Utility of Reference
Intervals
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Number of specimens required to estimate
homeostatic set points.

• n ( Z. CVA I/D)
• where -
• Z number of Standard deviates for a stated
  probablity (e.g. 1.96 for 95).
• D desired closeness homeostatic set point.

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Number of specimens required to estimate
homeostatic set points -

• Cholesterol testing
• How many samples (n) required to estimate set
  point within 5 given -
• CVI 4.9 CVA 3 (Recommended)
• Substitute equation -
• n ( Z. CVA I/D)
• n 1.96(32 4.92)½/52 5.07

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RCV at 95 and Number. of Specimens Required to
Assess the Homeostatic Set Point at Different
Levels of Imprecision CVA CVI RCVa
Number of () () () specimensb
2.0 4.7 14.1 4 3.0 4.7 15.4
5 4.0 4.7 17.1 6 5.0 4.7 19.0
7 6.0 4.7 21.1 9 7.0 4.7 23.4
11 8.0 4.7 25.7 13 9.0 4.7 28.1
16 10.0 4.7 30.6 19 15.0 4.7 43.5
38 20.0 4.7 56.9 65 aRCV (p lt0.05) 2.77
(CVA 2 CVI2)½, assuming no statistical evidence
of heterogenity bNumber mean result is within
?5of homeostatic set point1.962 x (CVA2 CVI2)
½/25.
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Assessment of reporting strategies

• Results may be reported in different formats
• e.g. 24h Urinary creatinine output -
• CVI for concentration 23.8
• CVI for output per collection 13.0
• CD for concentration 66.0
• CD for output 36.2

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Selecting best Specimen.

• e.g early morning urines for albumin versus 24h
  collections.
• Random hormone measurements versus timed
  measurements.

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Comparing Available Tests

• Creatinine v Creatinine Clearance
• FT4 v TSH in replacement situations
• FT4 v Total T4

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Reference Intervals

• Dr WA Bartlett
• Birmingham Heartlands Solihull NHS Trust
  (Teaching)

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WHO Definition of Health

• "a state of complete physical, mental and social
  well-being and not merely the absence of disease
  or infirmity"

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Grasbeck 1981 -

• "Health is characterized by a minimum of
  subjective feelings and objective signs of
  disease, assessed in relation to the social
  situation of the subject and the purpose of the
  medical activity, and is in the absolute sense an
  unattainable ideal state
• Thus, health is a goal-oriented concept more
  than a "state" mentioned in the WHO definition

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IFCC Definition of Health

• health is said to be a relative and not an
  absolute state, it being conceptually different
  in different countries, in the same country at
  different times and in the same individual at
  different ages