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Principles of Analysis > Principles of Analysis L1 > Flashcards

Principles of Analysis L1 Flashcards

1
Q

what is the international standard?

A

ISO15189

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2
Q

Definitive method

A

a method of exceptional scientific accuracy suitable for certification of reference material.

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3
Q

reference method

A

a method demonstrating small inaccuracies against definitive method.

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4
Q

routine method

A

method deemed sufficiently accurate for routine use against reference method and standard reference materials (SRM).

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5
Q

what is the definitive method for cholesterol

A

Isotope dilution, gas chromatography, mass spectrometry

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6
Q

what is the reference method for cholesterol

A

Abell-kendall method

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7
Q

what is the abell-kendall method

A

hydroylsis of cholesterol esters with alcoholic KOH

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8
Q

what is the routine method for cholesterol

A

enzymatic

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9
Q

what is the enzymatic method for cholesterol

A

cholesterol esters + cholesterol esterase -> free cholesterol

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10
Q

what is traceability

A

an unbroken chain of comparisons of measurements leading to a reference value

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11
Q

why are international biological standards established

A

to provide uniformity

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12
Q

primary standard

A

a substance of known chemical composition and high purity that can be accurately quantified and used for assigning values to materials and calibrating apparatus

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13
Q

standard reference material (SRM)

A

reference material issues by an institute whose values are certified by a reference method which establishes traceability

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14
Q

secondary standard

A

a commercially produced standard for routine use calibrated against a primary standard or reference material.

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15
Q

internal standard

A

A substance not normally present in the sample. Added to both standard and sample to correct for variation in conditions between different samples run – e.g. HPLC, GC, MS. The internal standard is also used to verify instrument response and retention time stability.

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16
Q

calibrator requirements

A
  • Prepared from pure substance
  • Stable and homogenous material
  • Matrix similar to assay matrix e.g. serum
  • No chemical interferences
  • If possible should be obtained commercially to minimise error
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17
Q

commercially available calibrators

A

have a concentration with a particular value

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18
Q

stated value calibrator

A

no certification

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19
Q

assigned value calibrator

A

given arbitrarily or derived using a non-reference method

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20
Q

certified value calibrator

A

certification of value by particular institute or body (what we would want)

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21
Q

standard reference method value

A

derived using a reference method (what we would want)

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22
Q

improving truness

A

decreasing systematic errors

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23
Q

improving accuracy

A

decreasing uncertainity, decreases random and systematic errors

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24
Q

improving precision

A

decreasing random errors

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25
Q

precision

A

how close together values are

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26
Q

trueness

A

how close to measuring true value

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27
Q

verification

A

confirmation, through provision of objective evidence, that the specified requirements have been fulfilled. Assay performing as expected to. Assays bought commercially check against performance characteristics.

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28
Q

validation

A

confirmation, through provision of objective evidence, that the requirements for a specific intended use or application have been fulfilled. In house assay unknown performance characteristics.

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29
Q

measurand

A

analyte of interest and how going to measure

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30
Q

trueness and precision

A

are independent of one another

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31
Q

how is trueness measured

A
  • Repeat analysis of multiple levels of certified reference materials. Results are compared with the assigned value
  • Recovery experiments
  • Comparison with results from “fresh” EQA material
  • Correlation with a current/accepted method using patient samples (comparability) not usually a measure of trueness, unless method is a reference method
32
Q

how can the degree of precision be measured?

A

quantifying the overall effect of all random errors

33
Q

two forms of precision

A
  • repeatability
  • intermediate precision
34
Q

how do you measure repeatability?

A
  • Minimum 20 results obtained from repeat analysis of IQC and patient samples on the same run
35
Q

how do you measure intermediate precision?

A
  • Minimum 20 results obtained from repeat analysis of IQC and patient samples from runs on different days
36
Q

coefficient of variation equation

A

CV=[SD/M]X100%

37
Q

advantages of CV

A

unitless, allows comparison between results from different analytes

38
Q

ideal CV

A

<5% and no wore than 10% except at low levels

39
Q

what is accuracy a combination of

A

trueness and precision

40
Q

how is accuracy measured

A

total error- estimate TE from estimate of bias from method comparison / EQA. estimate of precision from replication studies (intermediate precision)

41
Q

TE equation

A

TE = bias + 2SD (for a 95% CI)

42
Q

measurement of uncertainity

A

The uncertainty of measurement is a parameter associated with the result of a measurement, that characterises the dispersion of the values that could be reasonably attributed to the measurand. basic parameter is SD. Best estimate of the “true value” ± measurement uncertainty (2xSD from intermediate precision)

43
Q

interference

A

The effect on the analytical measurement of a particular component by a second component

44
Q

analytic interference

A

 Cross-reactivity with other compounds e.g. similar structure / drugs etc
 Interference in methodology e.g. increase in absorbance due to lipaemia

45
Q

physiological interference

A

 Drugs e.g. prolactin increased by antipsychotics in vivo

46
Q

analytical specificity

A

Measure of a method to determine only the analyte of interest i.e. cross-reactivity e.g. cortisol and prednisolone have very similar structures. 27% cross-reactivity (siemens cortisol method)

47
Q

analytical sensitivity

A
  • Ability of a method to detect small concentrations
48
Q

limit of blank (LOB)

A

– Highest measurement result that is likely to be observed (with a stated probability) for a blank sample

49
Q

limit of detection (lod)

A

Lowest amount of analyte in a sample that can be detected with (stated) probability, although perhaps not quantified as an exact value

50
Q

limit of quantification (loq)

A

– Lowest amount of analyte in a sample that can be quantitatively determined with stated acceptable precision and trueness under stated experimental conditions

51
Q

functional sensitivity

A

Functional sensitivity is defined as the lowest concentration that can be measured with acceptable intermediate precision [CV] (less than or equal to 20%).

52
Q

measuring interval

A

The interval between the upper and lower concentration of analyte in the sample for which it has been demonstrated that the method has suitable levels of precision, accuracy and linearity

53
Q

what range is studied during verification/validation and how is this determined

A

Range between the LOQ and the highest concentration, this is determined by linearity.

54
Q

what is linearity and how is it usually performed?

A
  • An assessment of the difference between an individual’s measurements and that of a known standard over the full range of expected values. - Usually performed by comparing results from a series of dilutions of known standard across assay range
55
Q

reference intervals

A
  • If the concentration of a particular analyte is measured in samples from a normal healthy population (n>120) (required to be statistically significant) then a range of results is obtained
56
Q

reference intervals plotted as a frequency plot…

A

gaussian distribution is usually observed (normal/skewed). normal distribution – within 2SD 95% of results will fall, with 1SD 66.6% results will fall. Reference interval -2SD-+2SD. 1 in 20 or 5% be outside of normal reference interval may be normal for that individual and not problematic

57
Q

parametric method

A

 Assume Gaussian distribution of data or transformed (log) data. Determine reference limits (percentiles) as +/- 2SD from mean. Could work with 30 samples to be statistically significant but the distribution is assumed

58
Q

non-parametric method (normally used)

A

 Makes no assumption about type of distribution. Results ranked and cut-off taken at x% of values in each tail need 120 samples to be statistically significant

59
Q

target driven reference range

A

 e.g. cholesterol: reference range cannot be derived from “healthy” population
 JBS2 targets for treatment of hyperlipidaemia

60
Q

exclusion criteria (to establish healthy population)

A

diseases
risk factors
intake of pharmacological agents
physiological states

61
Q

possible subgrouping

A

age
gender
genetic factors
physiological factors

62
Q

results used to derive a reference range contain elements of

A

biological and analytical variation

63
Q

how is biological variation introduced

A

physiological factors, diet, fluid intake, exercise

64
Q

CV (total) equation

A

CV (total) = √ CV2analytical + CV2biological

65
Q

clinical/diagnostic sensitivity

A

The ability of a TEST to correctly identify those who HAVE the disease. a highly sensitive tests has few false negatives

66
Q

clinical/diagnostic specificity

A

The ability of a TEST to correctly identify those who do NOT HAVE the disease. a highly specific test will have few false positives.

67
Q

predictive value

A

measure of the ability of test to correctly assign individual to either disease or non-diseased group

68
Q

diagnostic efficiency

A

proportion of true results

69
Q

sensitivity equation

A

TP/(TP+FN)

70
Q

SPECIFICITY EQUATION

A

TN/(TN+FP)

71
Q

PPV EQUATION

A

PPV = TP (TP+FP)

72
Q

NPV EQUATION

A

NPV = TN (TN+FN)

73
Q

predictive values are affected by prevalence

A
  • As disease prevalence increases the PPV also increases
  • As disease prevalence decreases the NPV increases
74
Q

naturally binary results

A

pos/neg

75
Q

continuous variables

A

need cut-off values to be applied

76
Q
A

Principles of Analysis (8 decks)

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