1. Josiane Arnaud1, Jean-Philippe Weber2,
Are desirable quality specifications for evaluating laboratory performances in external quality assessment schemes for copper, zinc and selenium in human serum or plasma attainable?
Josiane Arnaud1, Jean-Philippe Weber2,
Cas W Weykamp3, Patrick J Parsons4, Olav Mazarrasa5, Antonio Menditto6, Marina Patriarca6, Andrew Taylor7
1 – CHU de Grenoble, France; 2 – Institut National de Santé Publique, Québec, Canada;
3 – Queen Beatrix Hospital, Winterswijk, The Netherlands;
4 – New York State Department of Health, Albany, USA;
5 – Centro de Seguridad y Salud en el Trabajo, Santander, Spain;
6 – Istituto Superiore di Sanità, Rome, Italy; 7 – University of Surrey, Guildford, UK

2. Thematic Network Organizers of external quality assessment / proficiency testing schemes related to occupational and environmental laboratory medicine
Conflicting conclusions
at the participant level
Different possibilities for
organisation,
statistical analyses,
participant monitoring
ISO 13528,
EURACHEM,
EQALM,
ILAC,
IUPAC,
IFCC…
TE EQAS consensus procedures
Coordonnateur :
Dr Andrew Taylor
(University of Surrey)

3. Uncertainty evaluation
Calculated (sample dependent)
 Consensus participants’ standard deviation
(after exclusion of outliers)
Reference laboratory standard deviation
Metrological laboratory standard deviation
Defined (analyte and medium)
 Defined by the law
 Quality specification = QS

4. Quality specification criteria
Must take into account:
 Analytical possibilities (concentration range)
 Expertise of laboratory
 Biological individual variability
 Overlaps between « normal » and pathological states
Law recommendations (if any)
EQAS role: laboratory licensing or education

5. Quality specification calculation
Horwitz Equation :
0.02C0.8495
Fraser’s equation:
0.25(CV2intra+CV2inter)1/2 + z(0.5xCVintra)
(100/4)* ref. range/mean ref range
Tonk equation:
Quality specification calculation

6. Quality specification calculation
Fraser’s equation, 1999
Desirable total error % =
0.25 (CV2intra + CV2 inter)1/2 + z (0,5 CV intra)
CV intra = intra-individual variability
CV inter = inter individual variability
z = 1.65 for a 95% probability level.
Fraser CG. Scand J Clin Lab Invest 1999;59:

7. Individual Variability (published datas* on healthy populations)
Copper
Zinc
Selenium
intra
2.3 – 9.2
inter
*References
Gallagher SK, et al. Clin Chem 1989;35:369-73
Gonzalez-Revalderia J, et al. Clin Chem 1990;36:
Sabban A. Thesis, University of Surrey, 2005.
Lacher DA, et al. Clin Chem 2005;51:450-2.

8. Cu Zn Se quality specification
Minimal QS*,% 12 15
Desirable QS*,% 8 10
Optimal QS*,% 4 5
*Desirable total error % = 0.25(CV2intra+CV2inter)1/2 + z(0.5xCVintra)
Optimal = 0.5 Desirable.
Minimal = 1.5 Desirable.

9. Uncertainty and concentration
0,00
10,00
20,00
30,00
40,00
50,00
60,00
70,00
Zn CV % (participants)
Zn target concentration, µmol/l (consensus after exclusion of outliers)
Minimal QS: 1.2 µmol/l
 8 µmol/l Desirable QS: 0.8 µmol/l
Optimal QS: 0.4 µmol/l
Zinc

10. Cu Zn Se quality specification (low concentrations)
Cutoff, µmol/l 7 8
0.6
Minimal QS, µmol/l
0.84
1.20
0.072
Desirable QS, µmol/l
0.56
0.80
0.048
Optimal QS, µmol/l
0.28
0.40
0.024

11. Quality specification evaluation

12. Method Sample concentration selection
Cu, µmol/l
3.5 9 15 20 30
Nb participants 82
128
184
239
168
Se, µmol/l
0.25
0.5
1.0
1.5
3.0 69
101 95
143 97
Zn, µmol/l 8
144
156
228

13. Z-score = (xi-X)/(QS/2)
Method Z-score
Z-score = (xi-X)/(QS/2)
where
xi = participant’s result,
X = target value
QS = quality specification.
QS is divided by two to be consistent with the ISO guide which states that performance is
Satisfactory if Z-score 2
Unacceptable if Z-score > 2
Allows
comparison
of  samples

14. Cu, Zn and Se Z-score percentiles
Results
Cu, Zn and Se Z-score percentiles
Minimal Cu
Minimal Se
Minimal Zn
Desirable Cu
Desirable Se
Desirable Zn
Optimal Cu
Optimal Se
Optimal Zn
-8,00
-6,00
-4,00
-2,00
0,00
2,00
4,00
6,00
8,00
10,00
Z-score, percentiles

15. Unacceptable results, %
Cu &Se 30 3 20
1.5 15
1.0 9
0.5
3.5
0.25
Concentrations, µmol/l Zn 20 15 8
% of Z-score>2

16. Discussion Participant value Target value TE EQAS Conclusion 22.0 20.0NY
Satisfactory BE
Unacceptable
Discussion

17. Discussion Fraser’s equation, 1999 Desirable total error % =
0.25 (CV2intra + CV2 inter)1/2 + z (0,5 CV intra)
Limitations
Literature agreement
Pathological states
Analytical possibilities
Advantages
Biological variability
Sample and run independent

18. Discussion Imprecision, % Cu Se Zn Fraser’s QS, optimal (this work) 45
Fraser’s QS, desirable (this work) 8 10
Fraser’s QS, desirable (Ricos, plasma) 12
14.5 11
Fraser’s QS, desirable (Ricos, serum) 14
13.5
Analytical variability (ref. laboratories)
4.3
6.0
5.8
Analytical variability (participants)
10.1
17.4
14.7
Fraser’s QS, minimal (this work) 15
Ricos C et al. Scand J Clin Lab Invest 1999;59:

19. Discussion : Comparison to current QS – Cu & Zn
CA, FR : 0.08x + 0.4
BE, UK : x + 0.9
IT : 0.075x + 0.6
Cu NY : 0.1x
Zn NY : 0.15x
0,00
1,00
2,00
3,00
4,00
5,00
6,00
7,00
8,00 10 20 30 40 50 60
Concentration, µmol/l
QS, µmol/l
Minimal Zn QS :
0.15x if >8 µmol/l
Minimal Cu QS :
0.12x if >7 µmol/l

20. Discussion : Comparison to current QS - Se
IT QS = 0.06x
BE, CA, FR, UK QS = 0.06x
NY QS = 0.2x
0,00
0,10
0,20
0,30
0,40
0,50
0,60
0,70
0,80
0,90
1,00
2,00
3,00
4,00
5,00
Se concentration, µmol/l
Se QS, µmol/l
Minimal QS = 0.12x
if x> 0.6 µmol/l

21. Conclusion Patient’s diagnosis and follow-up Reliable determinations
Participant
laboratory
TE EQAS
objective
quality
specification
Analytical
performances
Individual
variabilty
harmonisation

22. Thank you for your attention