Biological variation

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Biological variation
Biological variation

• Biological variation
• Introduction
• Estimation (ANOVA application)
• Index-of-individuality
• Comparison of a result with a reference interval
  ("Grey-zone")
• Reference change value (RCV)

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Biological variation
Biological variation

• Reference interval and biological variation
• Reference interval encompasses
• pre-analytical imprecision
• analytical imprecision
• within-subject biological variation
• between-subject biological variation
• Usefulness of reference intervals

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Estimation of biological variation
(ANOVA-application)
Biological variation

• Approaches
• One overall analysis using nested ANOVA based on
  dedicated software (SAS, SPSS, BMDP etc.).
• Stepwise approach with computation of variances
  at each level.
• General requirement Repeated measurements at
  each level, i.e. at least duplicates, in order to
  resolve the variance components.
• a time period.
• Inspection of data on biological variation
• Generally, ANOVA is robust towards moderate
  deviations from normality, but it is sensitive
  towards outliers.
• Occurrence of outliers
• Within subgroups or one subgroup versus the bulk
  of the rest of subgroups
• Within-subject variation
• Homogeneity/heterogeneity
• Within- between subject biological variation
• Example Creatinine

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Analytical biological variation
Biological variation

• Estimation of biological variation
• Remark
• Consider the importance of analytical
  imprecision.
• Inter (?B-S)/intra (?W-S) -individual biological
  variation
• Analytical variation (?A)
• Total dispersion of a single measurement of
  individuals
• ?T2 ?B-S2 (?W-S2 ?A2) ?B-S2 ?T, W-S2
• Index of individuality (Ii) (see also later)
• ?T,W-S/?B-S ?W-S/?B-S
• Ignoring pre-analytical variation
• Components of variation-ANOVA
• Between (B-S)- and within-individual(W-S)
  biological variation
• Inclusive analytical variation (sT,W-S)

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Analytical within biological variation
Biological variation

• Analytical variation can be minimized by
  collecting and running the samples within one
  run.
• Shortcut computational principles
• Duplicate sets of measurements
• SD Sd2/2n0.5
• for n duplicate measurements,
• where d is the difference between pairs of
  measurements.
• Examples
• Measurements of duplicate samples to derive the
  SDA

CochranBartlett ANOVA
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Index-of-individuality (II)
Biological variation

• Index-of-individuality (II)
• CVW-S/CVB-S
• is called
• "Index-of-individuality"
• Ratio between within- and between-subject
  variation
• Often, the analytical variation is included, to
  give
• II (CVW-S2 CVA2)½/CVB-S
• Harris EK Clin Chem 1974201535-42
• Examples

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Index-of-individuality (II)
Biological variation

• II CVW-S/CVB-S
• If II lt 0.6
• high degree of individuality
• reference ranges of limited utility (better use
  RCV!)
• If II gt 1.4
• low degree of individuality
• reference ranges are more useful
• Most analytes have II lt 1.4 !!
• Examples

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Comparison of a result with a reference-interval
Biological variation

• The "grey-zone"
• Example 
• 2 measurement results for serum glucose
• (1) 88 mg/100 ml
• (2) 109 mg/100 ml
• with a reference-interval 60 - 100 mg/100 ml.
• Question Is result (1) actually inside, result
  (2) outside the reference-interval?
• Data CVa 2 CVi 6.1
• CVtot SQRT(CVa2 CVi2) SQRT(2 2 6.1
  6.1) 6.4
• Transform CVtot into stot 6.4 mg/100 ml (at 100
  mg/100 ml)
• Calculate the grey-zone around the limit of 100
  mg/100 ml with 95 (90) probability (Note
  one-sided)
• 1.65 (1.29) ? stot or 1.65 (1.29) ? 6.4 mg/100
  ml 10.6 (8.3) mg/100 ml.
• Grey zone at 95 89.4 - 110.6 mg/100 ml
• Grey zone at 90 91.7 - 108.3 mg/100 ml. 

• The power concept will be explained later. It is
  important for
• Sample size method comparison
• Limit of detection (LOD)
• IQC

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Biological variation
"Grey zone" for results at reference limits
P 95 Biology, only 1.65 CVW-S
P 95 Total 1.65 UA2CVW-S2 UA Analytical
uncertainty (see "Goals")
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Biological variation

• Reference Change Value (RCV), or Medically
  significant difference (Dmed)
• 95 interval for difference between two
  samplings and measurements
• Dmed 1.96 2 (CV2W-S CV2Anal)½
• The RCV is particular important for analytes with
  high CVB-S.
• ?med for the creatinine clearance
• C ml plasma cleared per min per standard body
  surface
• Ucr concentration of creatinine in urine
  (mg/ml)
• Pcr concentration of creatinine in plasma
  (mg/ml)
• V volume urine flow in ml per min
• A body surface in m2
• For
• Ucr 1 mg/ml
• Pcr 0.01mg/ml

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?med for the creatinine clearance
Biological variation

• Calculation
• CVi 15 or at C 92 ml/min/1.73 m2 , si
  13.8 ml/min/1.73 m2 ()
• stot SQRT2.62 13.82 14 ml/min/1.73m2
•  
• Thus Dmed 1.96 SQRT2 14 38.9
  ml/min/1.73 m2
•  
• in other words a decrease in creatinine clearance
  of 42 is to consider medically significant.
• () Tietz Textbook of Clinical Chemistry 2nd Ed,
  Burtis CA, Ashwood ER, eds. WB Saunders Company,
  Philadelphia, 1994 p 1536.
• Note If we also take the CVa for V into account,
  f.e. 5, then
•  

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Notes
Notes