Un tentativo di utilizzare il Controllo di Qualità Inter Laboratorio (Allargato) per definire e misurare la Qualità delle prestazioni Analitiche; in questo caso nell'ambito dello Screening del Sangue Occulto nelle Feci

1. Il Controllo di Qualità Allargato
per la stima della Qualità
nel Laboratorio Clinico
Un esperimento relativo allo screening
maurizio piu
8 giugno 2015
Un esperimento relativo allo screening
regionale del Sangue Occulto nelle Feci

2. Perché scegliere l’ERRORE TOTALE
QC Design
The Meaning and Application of
Total Error
James O. Westgard
https://www.westgard.com/essay111.htm

3. The intended use of total error is to describe the
maximum error that might occur in a test result
obtained from a measurement procedure. In
method validation studies, it provides a measure
of quality that can be compared to the intended
analytical quality of a test, which can be
described in terms of an allowable total errordescribed in terms of an allowable total error
(TEa). TEa is an analytical quality requirement
that sets a limit for both the imprecision
(random error) and bias (systematic error) that
are tolerable in a single measurement or single
test result.

4. L'uso previsto per l’Errore Totale è di
ottenuto
da un procedimento di misura. In studi di
validazione del metodo, fornisce una misura
della qualità che può essere paragonata alla
, e che può, e che può
essere
. Il TEa è un requisito di
qualità analitica che
(errore casuale)
(errore sistematico)
.

5. A second use has developed over time. Peer-
comparison programs often calculate the total
error on the basis of the SD observed on internal
QC materials and the bias on the basis of the
lab’s mean versus some overall mean for a
method subgroup or the mean from the total
peer group. This estimate of total error is
intended to be predictive of the variationintended to be predictive of the variation
expected in the test results delivered to the
physician users and patient consumers. In this
context, total error might be thought of as a
precursor of today’s measurement uncertainty,
but estimated by a top-down approach rather
than the bottom-up estimate recommended by
ISO/GUM

6. Un secondo utilizzo si è sviluppato
successivamente. Programmi peer-
comparison (CQA) spesso calcolano l'errore
totale sulla base dellla SD osservata su
materiali di controllo interno e il bias sulla
base della media del laboratorio vs. la media
per un metodo sottogruppo o la media del
peer-group totale.peer-group totale.
.
In questo contesto
.

7. In short, total error is a quality characteristic
whereas precision and accuracy are performance
characteristics that contribute to the quality of a
test result. Different combinations of precision
and accuracy can produce the same quality for aand accuracy can produce the same quality for a
test result, thus it is better to set goals for the
allowable total error, rather than set individual
goals for the allowable SD and the allowable
bias

8. In breve,
mentre la precisione e l’esattezza
sono caratteristiche di prestazione che
contribuiscono alla qualità di un risultato
analitico.analitico.
, quindi
, invece di impostare obiettivi
individuali per SD e bias ammissibili

9. L’ERRORE TOTALE analitico
TE = Bias + Z*SD
Errore totale (ET)=|Bias%|+1.65*CV%
Dove:
è la stima dell’Errore Sistematico
è la stima dell’Errore Casuale
è il coefficiente (moltiplicatore) che rappresenta
l’intervallo di confidenza desiderato

10. James O. Westgard, PhD, and Sten A. Westgard, MS - SEP.1.2013 - Clinical Laboratory News-AACC
Total Analytic Error: From Concept to Application
Today clinical laboratories have come under increased
pressure to implement quality systems and new risk
management guidelines for quality control in order to
ensure timely and accurate delivery of test results.
However,
. In simple terms, the question that. In simple terms, the question that
laboratory professionals should be asking is:
As laboratories attempt to
answer this basic question, other questions quickly
become

11. . Other tools,
such as Sigma metrics, method decision charts, Sigma
statistical quality control (SQC) selection graphs, andstatistical quality control (SQC) selection graphs, and
charts of operating specifications are also useful. In this
article, we review the concept of TAE, including its
estimation and application in managing the analytical
quality of laboratory testing processes.

12. In , Westgard, Carey, and Wold
(1).
.
This practice originated in conventional analyticThis practice originated in conventional analytic
laboratories in which replicate measurements were
usually made to reduce the effects of imprecision, which
left bias as the primary consideration for assessing the
quality of a test result. As we know, however,
. Therefore,
.

13. This difference in clinical laboratory practice prompted
introduction of the . In short, the authors
recommended that
).
Because terminology and abbreviations sometimeBecause terminology and abbreviations sometime
complicate discussions of this concept and because the
Food and Drug Administration (FDA) favors TAE and ATE,
these terms will be used in the rest of this discussion.
Furthermore, these abbreviations will likely become part
of the standard lexicon in clinical laboratories.

14. Total Analytic Error =
Allowable Total Error =

15. <
Semplicemente…
<

16. In order to put the concept into practice, the authors
recommended that laboratories
and the
. Accordingly, using a multiple of the. Accordingly, using a multiple of the
standard deviation (SD) or coefficient of variation (CV),
(or for a one-
sided estimate) for a 95% confidence interval or limit of
the possible analytic error (Figure 1).

17. 1-sided
The graph shows a representation of total analytic error or total error using
the terminology of the original paper: random error (RE), systematic error
(SE), total analytic error (TAE or TE), bias (inaccuracy), and SD (standard
deviation).

18. Given that
, its practical value depends on a
comparison to the quality required for the
intended use of a test result. In other
words, the definition refers towords, the definition refers to
.

19. As used by ISO here, intended use and quality of results
describe quality goals or requirements. Such quality
goals are meant to guide selection of methods and
design of SQC procedures.
.

20. SPECIFICHE DI QUALITA’
Traguardi Analitici
a. Data based on components of biological variation
b. Data based on analysis of clinicians' opinions
The Consensus Hierarchy from Stockholm Conference
b. Data based on analysis of clinicians' opinions
a. From national and international expert bodies
b. From expert local groups or individuals
a. Regulatory bodies
b. Organizers of External Quality Assessment (EQA) schemes
a. As demonstrated by data from EQA or Proficiency Testing

21. SPECIFICHE DI QUALITA’
Traguardi Analitici
, although new
perspectives were forwarded inducing cautious modifications and
explanatory additions.
- are available to set performances goals: some
of these are better suited for certain measurands than for others:of these are better suited for certain measurands than for others:
•Model 1:
•Model 2:
•Model 3:

22. SPECIFICHE DI QUALITA’
Traguardi Analitici
The first EFLM Strategic Conference – MILAN 2014
This model is since it is based on the actual
clinical outcome; however, in practice
since it is difficult to show the direct effect of laboratory tests
on medical outcome. Different options are available:
•Use the results of the outcome studies: how the analytical
performance influences the clinical outcome
•Investigate by a simulation study the impact of the analytical
performance on the probability of clinical outcomes
•Use surveys of clinicians or “experts” opinions to check the
impact of analytical performance on medical decisions

23. SPECIFICHE DI QUALITA’
Traguardi Analitici
The first EFLM Strategic Conference – MILAN 2014
This model seeks to
. Its applicability can however be

24. SPECIFICHE DI QUALITA’
Traguardi Analitici
This model is the one where . It is linked
to the highest level of analytical quality achievable with the
currently available techniques. If the best laboratories can achieve
The first EFLM Strategic Conference – MILAN 2014
currently available techniques. If the best laboratories can achieve
only a “certain” analytical quality not at the level required by Models
1 and 2, then manufacturers have to strive to develop better assays.
On the other hand, if the majority of laboratories can achieve the
analytical quality required by Model 1 and 2, then the laboratories
that cannot, have to change their practice. With this model,
however, there is no link or only a weak one between what is
technically achievable at present and what is needed to obtain a
better outcome for the patient (Model 1) or to minimize the ratio of
the analytical noise to the biological signal (Model 2). For this
reason, Model 3 .

25. Analytical Goal Survey Results
Sten Westgard, MS
January 2015

28. SPECIFICHE DI QUALITA’
Traguardi Analitici per FOB

29. SPECIFICHE DI QUALITA’
Traguardi Analitici per FOB
>>> Traguardi “decisi”>>> Traguardi “decisi”
più o meno arbitrariamente da organizzatori di
Programmi VEQ “istituzionali”
a. Regulatory bodies
b. Organizers of External Quality Assessment (EQA) schemes
The Consensus Hierarchy from Stockholm Conference

30. Can/should observed total error
specifications be calculated for each
laboratory based on laboratory estimates
of imprecision and bias?

32. Stima dell’Esattezza
VEQ >>> accettabileVEQ >>> accettabile

34. The need for and the practicality of
measurement

38. Un esempio di Report di CQA

40. I Box plot

41. La statistica descrittiva

44. M
M+2SD
M-2SD

45. M
M+2SD
M-2SD

46. La stima dell’Errore Totale
Errore totale (ET)=|Bias%|+1.65*CV%
Tendenza centrale
Dispersione

47. Errore totale (ET)=|Bias%|+1.65*CV%

48. Errore totale (ET)=|Bias%|+1.65*CV%
M lab-M peer gr.
M peer gr.
|Bias%|=
M peer gr.
=
108.77-108.96
108.96
= 0.17

49. Errore totale (ET)=|Bias%|+1.65*CV%

50. Errore totale (ET)=|Bias%|+1.65*CV%
0.17 + 1.65*5.76 = 9.68%0.17 + 1.65*5.76 = 9.68%

54. Calcolo CVR

55. CV1 CV2
a 6,26 6,22
b 5,43 5,07
c 7,13 5,54
d 6,28 4,09
e 5,05 4,89
f 5,71 3,89
g 5,76 4,47
Calcolo CVR
g 5,76 4,47
h 3,60 3,38
i 4,30 2,54
CUMULAT 6,47 5,12
5.76 / 6.47 =

56. Calcolo SDI

57. Livello 1

58. Livello 1

59. Livello 2

60. Livello 2