esp lung eqa schemes - olv z

obo Prof. Dr. Els Dequeker

Biomedical Quality Assurance Research Unit

Department of Public Health & Primary Care

KU Leuven, Leuven, Belgium

Pathology symposium

OLV Ziekenhuis Aalst

10 December 2019

ESP Lung EQA schemesPrograms for quality assurance of IHC

and molecular tests in non-small cell lung cancer

Cleo Keppens

Domain:

• DNA analysis

• RNA analysis

• IHC (+ digital cases)

• FISH (+ digital cases)

Genes: ALK, ROS1, PD-L1,

EGFR, KRAS, BRAF, c-MET

≈ 230 labs, 37 countries

- Steering comittee with medical and technical experts

- Validating labs, experts and assessors

- Recognized EQA coordination center

http://lung.eqascheme.org

http://www.esp-pathology.org

Accredited as EQA provider by BELAC in

accordance with standard NBN EN ISO/IEC

17043:2010 (PT-215)

ESP Lung EQA Scheme: organized since 2012

2

EMA, European Medicines Agency;

FDA, US Food and Drug Administration.

2014: New

biomarker ROS1

included

2017: New joint pilot

EQA scheme for

ctDNA EGFR/KRAS

2012:

pilot round

2015: Technical

assessment for

ALK IHC

2017: New scheme set-up:

3 rounds

New biomarkers:

PD-L1,

KRAS (mol), BRAF (mol)

Expansion of scheme according to current needs

2018: New

biomarker:

genomic cMET

20132012 2014 2015 2016 2017 2018 2019

2016: Technical

assessment for

ROS1 IHC

2020

2019: RNA

analysis of

cMET

2020: RNA analysis

ALK and ROS1 in

combination with MET

2018: full joint

cfDNA scheme for

EGFR

2012: EMA

approves

Xalkori

2015: FDA

approves

osimertinib

2016: EMA

approves

osimertinib

2013: EMA/FDA

approve afatinib

2013: EGFR

pilot included

2016: EMA/FDA

update label

crizotinib to ROS+

2014: FDA

approves

ceritinib

2015: EMA

approves

ceritinib/alectinib

2016: EMA

approves

alectinib

2017:

FDA/EMA

Dabrafenib

+ trametinib

(BRAF

V600E)

2012-2019: Participant’s feedback

2017:

participants

workshop cfDNA

2016: survey on

cfDNA

implementation

2018:

Osimertinib

(1st L EGFR)

2018:

FDA/EMA

approves

durvaluma/

nivolumab/

Pembrolizu

mab

2015: EMA

approves

nivolumab

2019 FDA

approves

pembrolizumab

3

PD-L1 ALK ROS1 EGFR

KRAS/BRAF

C-MET

IHC IHC IHC

FISHFISH

Genomic

variant

analysis

Genomic

variant

analysis

RNA analysis

2017 2012 2014

20142012

2018

2019

2013

2017

Currently assessed biomarkers & techniques

4

ALK IHC

ROS1 IHC • Genotyping results

• Technical assessment

• Reporting

• Interpretation of IHC

digital cases

PD-L1 IHC

ALK FISH

ROS1 FISH

• Genotyping

• Interpretation of FISH

digital cases

• Reporting

EGFR, KRAS, BRAF • Genotyping results

• Reporting

C-MET

N=8 N=4

N=10

N=5

N=5

N=5 N=5

ESP Lung EQA scheme: Set-up

FFPE resection specimens

Digitals

5

PD-L1 ALK ROS1 EGFR

KRAS/BRAF

C-MET

IHC IHC IHC

FISHFISH

Genomic

variant

analysis

Genomic

variant

analysis

RNA analysis


6

7

Overview of PD-L1 test results

Year Subscheme N° laboratories% successful

laboratories*

Average

score (%)

2017 (pilot)

IHC

11 100% 96%

2018 10 90% 94%

2019 24 (ongoing)

2017 (pilot)IHC technical

assessment

9 89% 89%

2018 11 100% 89%

2019 24 (ongoing)

2019: sponsored by * ≥90% analysis score or ≥3/5 technical score


laboratories*

Average

score (%)

2017 (pilot)

IHC

78 71% 91%

2018 72 85% 93%

2019 107 (ongoing)

2017 (pilot)IHC technical

assessment

67 81% 76%

2018 74 96% 86%

2019 107 (ongoing)

PD-L1 analysis methods (2018 – R3)

58%22%

7%

6%4% 3%

EU (n=72)

22C3 (Dako)

SP263 (Ventana)

E1L3N (cell signaling)

28-8 (Abcam)

QR1 (Quartett)

CAL10 (Biocare Medical)

SP142 (Ventana)82%

9%

9%

BE (n=11)

8

9

Overview of PD-L1 test results


laboratories*

Average

score (%)

2017 (pilot)

IHC

11 100% 96%

2018 10 90% 94%

2019 24 (ongoing)

2017 (pilot) IHC technical

assessment

9 89% 89%

2018 11 100% 89%

2019 24 (ongoing)

2019: sponsored by * ≥90% analysis score or ≥3/5 technical score


laboratories*

Average

score (%)

2017 (pilot)

IHC

78 71% 91%

2018 72 85% 93%

2019 107 (ongoing)

2017 (pilot) IHC technical

assessment

67 81% 76%

2018 74 96% 86%

2019 107 (ongoing)

Keppens C et al. 2019. PD-L1 immunohistochemistry in non-small cell lung cancer:

unraveling differences in staining quality and interpretation. Under review.

Technical assessment of staining performance

(2017-2018)

▪ 1 TMA slide – 3 µm

▪ Team of min. 2 pathologists

▪ Microscopic review of staining quality

compared to optimal staning for specific antibody

▪ Indivual comments on staining quality

3 cases (2017)

4 cases (2018)

+ Tonsil control

Link of staining score (on 5 points) to

▪ Laboratory setting (type, accreditation)

▪ Experience (# samples, laboratory size,..)

▪ Applied protocols

5 Excellent staining

4 Pass + minor remark

3 Deficiency without clinical effect

2 Deficiency with clinical effect

1Failure to stain the slides, no

interpretation possible

10



Primary antibody

Epitope retrieval kit

Detection system# times

used (%) (n=141)

Method code

OR (95% CI) relative to method

a b c d e f

22C3 (Dako)

Cc1 (Ventana) OptiView DAB IHC Detection Kit (Ventana)

35 (24.8%)

a /1.247

[0.547; 2.843]

4.075 [1.314;

12.632]*

0.129 [0.042;

0.396]***

1.769 [0.482; 6.494]

1.211 [0.422; 3.481]

EnVisionFLEX Target Retrieval Solution, low pH (Dako)

Envision flex (Dako)

32 (22.7%)

b0.802

[0.352; 1.828]

/3.269

[0.979; 10.919]

0.103 [0.029;

0.371]***

1.419 [0.361; 5.579]

0.972 [0.311; 3.037]

various various 1 (0.7%) c0.245

[0.079; 0.761]*

0.306[0.092; 1.022]

/0.032

[0.007; 0,147]****

0.434 [0.090; 2.102]

0.297[0.075; 1.178]

SP263 (Ventana)


24 (17.0%)

d

7.752 [2.525;

23.810]***

9.709 [2.695;

34.483]***

31.660 [6.809;

147.22]****

/13.746 [2.699;

70.007]**

9.412 [2.466;

35.916]**


Bond Epitope Retrieval 2 (Leica)or homebrew EDTA

various 6 (4.3%) e0.565

[0.154; 2.075]

0.705[0.179; 2.770]

2.304[0.476; 11.111]

0.073[0.014;

0.371]**/

0.685[0.149; 3.155]

Other various various 1 (0.7%) f0.826

[0.287; 2.370]

1.029[0.329; 3.215]

3.364 [0.849; 13.321]

0.106[0.028;

0.406]**

1.461 [0.317; 6.719]

/

Comparison of PD-L1 IHC assays

OR=Odds Ratio [90% CI], *p<0.05, **p<0.01, ***p<0.001.

11



Primary antibody



used (%) (n=141)

Method code


a b c d e f

22C3 (Dako)


35 (24.8%)

a /1.247

[0.547; 2.843]

4.075 [1.314;

12.632]*

0.129 [0.042;

0.396]***

1.769 [0.482; 6.494]

1.211 [0.422; 3.481]



32 (22.7%)

b0.802

[0.352; 1.828]

/3.269

[0.979; 10.919]

0.103 [0.029;

0.371]***

1.419 [0.361; 5.579]

0.972 [0.311; 3.037]


[0.079; 0.761]*

0.306[0.092; 1.022]

/0.032

[0.007; 0,147]****

0.434 [0.090; 2.102]

0.297[0.075; 1.178]

SP263 (Ventana)


24 (17.0%)

d

7.752 [2.525;

23.810]***

9.709 [2.695;

34.483]***

31.660 [6.809;

147.22]****

/13.746 [2.699;

70.007]**

9.412 [2.466;

35.916]**



various 6 (4.3%) e0.565

[0.154; 2.075]

0.705[0.179; 2.770]

2.304[0.476; 11.111]

0.073[0.014;

0.371]**/

0.685[0.149; 3.155]


[0.287; 2.370]

1.029[0.329; 3.215]

3.364 [0.849; 13.321]

0.106[0.028;

0.406]**

1.461 [0.317; 6.719]

/



12



Primary antibody



used (%) (n=141)

Method code


a b c d e f

22C3 (Dako)


35 (24.8%)

a /1.247

[0.547; 2.843]

4.075 [1.314;

12.632]*

0.129 [0.042;

0.396]***

1.769 [0.482; 6.494]

1.211 [0.422; 3.481]



32 (22.7%)

b0.802

[0.352; 1.828]

/3.269

[0.979; 10.919]

0.103 [0.029;

0.371]***

1.419 [0.361; 5.579]

0.972 [0.311; 3.037]


[0.079; 0.761]*

0.306[0.092; 1.022]

/0.032

[0.007; 0,147]****

0.434 [0.090; 2.102]

0.297[0.075; 1.178]

SP263 (Ventana)


24 (17.0%)

d

7.752 [2.525;

23.810]***

9.709 [2.695;

34.483]***

31.660 [6.809;

147.22]****

/13.746 [2.699;

70.007]**

9.412 [2.466;

35.916]**



various 6 (4.3%) e0.565

[0.154; 2.075]

0.705[0.179; 2.770]

2.304[0.476; 11.111]

0.073[0.014;

0.371]**/

0.685[0.149; 3.155]


[0.287; 2.370]

1.029[0.329; 3.215]

3.364 [0.849; 13.321]

0.106[0.028;

0.406]**

1.461 [0.317; 6.719]

/



13

Optimal/weak PD-L1 stainings: an example



Optim

al

Suboptim

al

Weak +

Cytoplasmic stainingExcessive background

staining

Background

stainingWeak +

Cytoplasmic staining

Weak

staining

14

Staining artefacts



More than 1 artefact could be observed per laboratory

15



Staining quality directly affects TPS

estimations & technical failures

Importance

of including

a technical

assessment

to improve

outcomes!

IRR=Incidence Rate Ratio [90% CI]

16




(2017-2018)

▪ 32 different protocols

❑ 22C3 (Dako) 56.7%

❑ SP263 (Ventana) 19.1%

❑ E1L3N (Cell Signaling) 7.1%

▪ Staining artefacts

❑ Very weak or weak antigen demonstration 63.0%

❑ Excessive background staining 19.8%

▪ Positive influences

❑ EQA scheme year

❑ Use of CE-IVD kit without protocol manipulation LDT

❑ Antibody dilution: RTU

❑ Laboratory accreditation (overestimations only)

17

PD-L1 ALK ROS1 EGFR

KRAS/BRAF

C-MET

IHC IHC IHC

FISHFISH

Genomic

variant

analysis

Genomic

variant

analysis

RNA analysis


18

ALK ROS1

Year Subscheme # participantsSuccessful

participants*# participants

Successful

participants*

2012

IHC

analysis

29 (pilot) 52% / /

2013 58 64% / /

2014 96 70% 31 (pilot) 90%

2015 95 92% 31 58%

2016 102 88% 36 94%

2017 109 83% 53 94%

2018 99 90% 58 97%

2019 104 (ongoing) 79 (ongoing)

2015

IHC technical

assessment

73 (pilot) 90% / /

2016 90 95% 31 (pilot) 100%

2017 95 97% 52 90%

2018 93 96% 54 98%


19

Tembuyser L, Tack V, Zwaenepoel K, et al. Plos One 2014;9(11);e112159

Keppens C et al. Oncotarget 2018; 9(29); pp: 20524-20538

Overview of ALK/ROS1 IHC test results

* ≥90% analysis score or ≥3/5 technical score

20




ALK ROS1



Successful

participants*

2012

IHC

analysis

(pilot) / /

2013 1 100% / /

2014 11 64% 5 (pilot) 100%

2015 12 100% 4 50%

2016 11 82% 7 100%

2017 11 73% 8 100%

2018 13 77% 9 89%


2015

IHC technical

assessment

11 (pilot) 100% / /

2016 9 89% 5 (pilot) 100%

2017 8 100% 12 100%

2018 14 93% 8 100%



ALK/ROS1 IHC antibodies (2018 – R3)

48%

23%

8%

7%

5%2%

7%

ALK EU (n=99) D5F3 (Ventana)

D5F3 (Cell SignallingTechnology)1A4 (Origene)

5A4 (Leica)

5A4 (Novocastra)

5A4 (Abcam)

Other

36%

36%

14%

7%7%

ALK BE (n=14)

ROS1 (n8):

• 100% D4D6 (Cell Signalling

Technology)

ROS1 (n=58):

• 91% D4D6 (Cell Signalling Technology)

• 4% EP282 (Epitomics)

• 2% D4D6 (Genemed)

• 2% D4D6 (Ozyme)

• 2% oti1a1 (ThermoFisher)

21

ALK ROS1



Successful

participants*

2012

IHC

analysis

29 (pilot) 52% / /

2013 58 64% / /

2014 96 70% 31 (pilot) 90%

2015 95 92% 31 58%

2016 102 88% 36 94%

2017 109 83% 53 94%

2018 99 90% 58 97%


2015

IHC technical

assessment

73 (pilot) 90% / /

2016 90 95% 31 (pilot) 100%

2017 95 97% 52 90%

2018 93 96% 54 98%


22





Keppens C et al. 2019. Staining performance of ALK and ROS1 immunohistochemistry and influence

on molecular interpretation in NSCLC. In preparation.


(2015-2018)

▪ Similar set-up as for PD-L1

Marker ALK ROS1

EQA scheme year 2015 2016 2017 2018 2016 2017 2018

# participants 73 91 96 92 31 52 54

Average staining

score

(on a total of 5

points)

3,7 4,2 4,3 4,1 4,0 3,9 4,5

# assessorsOne group of 2

One group of 32 3 3 3 3 2

Sample type All resectionsAll

resections

All

resections

All

resections

All

resections

-2 resections

-1 cell-line with

a positive and

negative core

All

resections

# cases provided 5 5 3 3 5 4 3

# positive cases 2 2 1 2 2 2 1

# negative cases 3 3 2 1 3 2 2

Abbreviations: #, number; ALK, anaplastic lymphoma kinase;

EQA, External quality assessment; ROS1, ROS proto-oncogene 1.

23



Influencers of staining performance

Marker ALK ROS1

More samples tested in last 12 months

# staff involved in testing

More successive EQA participations

Later EQA scheme year

Laboratory setting

Laboratory accreditation

Use of a CE-IVD kit N/A

Switched protocol between schemes

Antibody dilution

Incubation time > 60 min.

Incubation temperature > 40 °C

Incubation at room temperature

24

Staining quality directly affects false-positives,

false-negatives and technical failures

Similar to PD-L1 -> EQA providers should assess both aspects!

+ Fewer analysis failures when more samples are tested annually,

more failures when a new method is introduced



IRR=Incidence Rate Ratio [90% CI]

25

PD-L1 ALK ROS1 EGFR

KRAS/BRAF

C-MET

IHC IHC IHC

FISHFISH

Genomic

variant

analysis

Genomic

variant

analysis

RNA analysis


26

27

Year Subscheme # laboratories % of labs successful**

2012 (pilot)ALK FISH 54 72%

ALK FISH digital 67 82%

2013ALK FISH 104 68%


2014ALK FISH 116 69%

ALK FISH digital 81 educational

2015

ALK FISH + digital*

111 79%

2016 113 82%

2017 116 79%

2018 103 98%

2019 (ongoing)

2014 (pilot)

ROS1 FISH + digital*

56 64%

2015 68 78%

2016 71 70%

2017 85 82%

2018 86 94%

2019 (ongoing)

Overview of ALK/ROS1 FISH test results

*Combination of wet and digital cases

** >90% analysis score


Keppens C et al. Oncotarget 2018; 9(29); pp: 20524-20538 27

28

Year Subscheme # laboratories % of labs successful**

2012 (pilot)ALK FISH 7 ND

ALK FISH digital 7 ND

2013ALK FISH 9 56%


2014ALK FISH 9 67%

ALK FISH digital 9 educational

2015

ALK FISH + digital*

6 100%

2016 5 100%

2017 7 57%

2018 6 50%

2019 5 (ongoing)

2014 (pilot)

ROS1 FISH + digital*

4 ND

2015 3 100%

2016 4 75%

2017 6 83%

2018 6 83%

2019 5 (ongoing)

Overview of ALK/ROS1 FISH test results

*Combination of wet and digital cases

** >90% analysis score


Keppens C et al. Oncotarget 2018; 9(29); pp: 20524-20538 28

ALK FISH methods EU (n=103) % BE (n=6) %

Vysis ALK break apart FISH Probe (Abbott) 48 (46.6%) 4 (66.7%)

ZytoLight SPEC ALK Dual Color Break Apart Probe (ZytoVision) 21 (20.4%)

ZytoLight SPEC ALK/EML4 TriCheck Probe (ZytoVision) 8 (7.8%)

ALK FISH DNA Probe, Split Signal (Dako) 5 (4.9%

Non-commercial method 5 (4.9%)

Repeat-Free Poseidon ALK (2p23) Break Probe (Kreatech) 4 (3.9%)

ALK IQFISH Break-Apart Probe for Dako Omnis (Dako, Agilent) 3 (2.9%) 2 (33.3%)

ROS FISH methods EU (n=86) % BE (n=6) %

ZytoLight SPEC ROS1 Dual Color Break Apart Probe

(ZytoVision)49 57,0%

2 33,3%

Repeat-Free Poseidon ROS1 (6q22) Break FISH Probe

(Kreatech Diagnostics)8 9,3%

6q22 ROS1 Break Apart FISH Probe RUO Kit (Abbott Molecular) 7 8,1% 1 16,7%

ROS1 break apart Probe (Cytocell) 4 4,7%

Vysis LSI ROS1 (Cen) SpectrumGreen Probe (Abbott) 3 3,5% 1 16,7%

Homebrew 3 3,5%

ROS1 IQFISH Break-Apart Probe for Dako Omnis (Dako,

Agilent)3 3,5%

2 33,3%

ALK/ROS1 FISH probes (2018 – R3)(most frequently used)

29

↑ errors for ROS1

↓ errors for ALK

Keppens C, et al. Oncotarget 2018; 9(29); pp: 20524-20538

Longitudinal analysis:

Errors IHC > errors FISH

Errors FISH > errors FISH digital

30

Error rates in earliest schemes

Error rates are calculated taking into account the number of false positive and false negative results as

well as the total number of samples for which a result was submitted, with the exclusion of educational

cases for which more than or equal to 25% of the participants were not able to obtain a result.

30

PD-L1 ALK ROS1 EGFR

KRAS/BRAFC-MET

IHC IHC IHC

FISHFISH

Genomic

variant

analysis

Genomic

variant

analysis

RNA analysis


31

2018 MET pilot EQA scheme

Sample

numberOutcome MET NM_000245.3 VAF Errors (%)

Technical

failures (%)

L18.MET1WT

SNP c.2975C>T, p.(T992I)

/

19%1/37 (3) 0/37 (0)

L18.MET2 c.3023_3028+9del 24% 9/37 (24) 0/37 (0)

L18.MET3c.3028+3A>G

SNP c.2975C>T, p.(T992I)

62%

40%8/37 (22) 1/37 (3)

L18.MET4 WT / 0/37 (0) 0/37 (0)

L18.MET5 WT / 0/37 (0) 1/37 (3)

▪ For genomic DNA analysis (mutations)

▪ 49 laboratories

▪ 12 laboratories used RNA tests (ex 14 skipping)

Not included in assessment

Separate RNA evaluation in 2019 EQA

▪ NGS: 31/37, non-commercial sequencing: 6/37

SNPs not considered to calculate scores

Successful state not determined (pilot)

▪ Average score: 90.4% (n=37)

32

PD-L1 ALK ROS1 EGFR

KRAS/BRAFC-MET

IHC IHC IHC

FISHFISH

Genomic

variant

analysis

Genomic

variant

analysis

RNA analysis


33

EU BE

Year Gene(s) # participantsSuccessful

particpants**# participants

Successful

particpants**

2013 (pilot)EGFR 107 educational 10 educational

KRAS 92 educational 5 educational

2014 EGFR 144 61% 8 75%

2015 EGFR 114 52% 10 70%

2016 EGFR 97 71% 7 100%

2017*

EGFR 101 71% 9 89%

KRAS 51 98% 9 100%

BRAF 47 98% 7 100%

2018*

EGFR 98 82% 8 100%

KRAS 56 91% 6 100%

BRAF 55 96% 6 100%

2019*

EGFR 95 (ongoing) 7 (ongoing)

KRAS 70 (ongoing) 7 (ongoing)

BRAF 73 (ongoing) 7 (ongoing)

34


Overview of molecular test results

*EGFR = mandatory, KRAS/BRAF=optional

**>90% analysis score

0

10

20

30

40

50

60

70

101 144 114 97 101 98 95

2013 2014 2015 2016 2017 2018 2019

% p

arti

cip

ants

EGFR methods

Prescreening

Commercial test kit

NGS

LDT

N=

Technological expansion: NGS in favour of LDTs

NGS=next-generation sequencing, LDT=Laboratory developed test35

https://varnomen.hgvs.org/

Keppens C, et al. Hum Mutat. 2019 Sep 25. doi: 10.1002/humu.23926.

HGVS nomenclature during molecular schemes

Scheme year 2013 2014 2015 2016 2017 2018

Gene Variant % HGVS compliant nomenclature (N)

EGFR

(NM_005228.5)

c.2155G>A

p.(Gly719Ser)/

3.8

(131)/

6.3

(32)/ /

c.2155G>T

p.(Gly719Cys)

0.0

(37)/

9.1

(44)/ / /

c.2235_2249del

p.(Glu746_Ala750del) / /

4.7

(121)***

25.9

(27)

47.2

(36)***/

c.2236_2250del

p.(Glu746_Ala750del)/

5.3

(113)/ / /

20.0

(95)**

c.2303G>T

p.(Ser768Ile)

0.0

(17)/

13.8

(29)

8.7

(23)/ /

c.2369C>T

p.(Thr790Met)

7.0

(71)

4.3

(93)**

5.2

(97)*

18.1

(83)

21.7

(92)**

16.5

(194)

c.2573T>G

p.(Leu858Arg)

3.0

(168)***

0.0

(85)***

6.6

(150)**

18.0

(130)

38.6

(133)***

27.1

(96)***

Recurring variants are shown only. In case a variant was distributed in both ESP and Gen&Tiss EQA schemes within a specific year, average

percentages for both schemes were presented. /: Variant not distributed during this scheme year. Asterisks represent a statistical difference

compared to other scheme years. Chi-squared test or Fisher’s Exact test for cell counts below 5. *p<0.05, **p<0.01, ***p<0.001.

Abbreviations: EGFR, Epidermal Growth Factor Receptor; HGVS, Human genome Variation Society;

36

Keppens C, et al. Hum Mutat. 2019 Sep 25. doi: 10.1002/humu.23926.

HGVS compliance is related to used analysis

techniques

*p<0.05, **p<0.01, ***p<0.001.

NGS = next-generation sequencing

37

Quality Management System

External Quality Assessment

Tools to assure quality of care and

laboratory testing

- Requirements in some European countries

- Hospital and laboratory accreditation

- More and more evidence that obtaining / holding an accreditation is a step forward

38

The outer line indicates the significant results (p < 0.05). The inner line shows the significance level of 0.05.

All markers in the centre of the figure showed no significant result.

Tack V. et al, Br J Cancer; 2018; Vol. 119; iss. 5; pp. 605 - 614

ESP EQA 2013-2016:

Accreditation leads to:

-successful EQA scores (p =0.018) (score

≥ 90%),

-fewer analysis errors (p = 0.002).

Laboratory setting:

-less analysis errors were made in a

university and research background,

compared to (private) laboratories and

industry laboratories (p = 0.016 and p =

0.012, respectively).

A higher nr of samples tested/year:

-increasing probability to have a successful

EQA

score (p = 0.009)

Effect on EQA performance

39

Longitudinal follow-up of problems reported

by EQA participants (2015-2018)

Deviating EQA results:

o 325 individual surveys

o 184 unique laboratories ~34 countries

o 514 analyzed cases (NSCLC + mCRC)

0 10 20 30 40 50 60 70 80 90 100

FISH (wet cases)

FISH (digital cases)

IHC (wet cases)

IHC (digital cases)

IHC (technical assessment)

Variant analysis

% cases (n=514)

Pre-analytical Analytical Post-analytical Unknown

40Keppens C. et al, Managing deviating EQA results: strategies of clinical laboratories testing for

oncological biomarkers. 2019. Submitted.

Longitudinal follow-up of problems reported

by EQA participants (2015-2018)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

99 102 99 108 66 10

ALK ROS1 PD-L1 EGFR KRAS WT

% c

ase

s

Cause

Unknown/other

Technical problem/equipment

Clerical error/personnel error

Problem with EQA material

Methodological/reagent issue

Interpretation error

41Keppens C. et al, Managing deviating EQA results: strategies of clinical laboratories testing for

oncological biomarkers. 2019. Submitted.

Importance of quality assessment during

all phases in the total test process

For laboratories:

ISO15189:2012a:

“Interlaboratory comparison programme(s) chosen by the laboratory shall, as far as possible, provide clinically

relevant challenges that mimic patient samples and have the effect of checking the entire examination

process, including pre-examination procedures, and post-examination procedures, where possible.”

For EQA providers:

Guideline on the requirements for EQA

providersb:

“Three aspects of molecular testing should be

covered by an EQA program: Pathology review,

the molecular test itself, and reporting.”

a. ISO 15189:2012 Medical laboratories -

Particular requirements for quality and

competence.

b. van Krieken JH et al. (2013) Virchows Arch.

42

ISO 15189:2012 Medical laboratories - Particular requirements for quality and competence (International Organization for Standardization)

van Krieken JH et al. Guideline on the requirements of external quality assessment programs in molecular pathology. Virchows Arch. 462:27-37 (2013)

CAP - Laboratory Accreditation Program - Molecular Pathology Checklist (2014)

Gulley M.L. et al. Clinical laboratory reports in molecular pathology. Arch Pathol Lab Med. 131:852-863 (2007)

ESP EQA SCHEMES FOR NSCLC:

Standards and guidelines on reporting

43

ESP Lung EQA: scoring of the post-analytical phase

Per sample evaluation:

• Test results (genotype given)

• Interpretation given and correct

General items:

• Patient name

• Date of birth

Method information:

• Method used

• Sensitivity/treshold of method

• List of mutations tested

• Reference sequence

44

Average reporting scores over time

0

10

20

30

40

50

60

70

80

90

100

ALK ROS1 ALK ROS1 PD-L1 EGFR/KRAS/BRAF

MET

FISH IHC Variantanalysis

Ave

rag

e r

ep

ort

ing

sc

ore

(%

)

EQA scheme

2012 2013 2014 2015 2016 2017 2018

*2013-2016: EGFR only,

2017-2018: EGFR/KRAS/BRAF

*

45

BE

Technique-specific information (2018)

0102030405060708090

100

Me

tho

d u

se

d, in

cl.

aberr

ations teste

d

Me

tho

d t

resh

old

# n

eo

pla

stic c

ells

an

aly

se

d

# c

ells

with s

plit

/sin

gle

sig

nal

Me

tho

d u

se

d, in

cl. a

ntib

od

y

IHC

in

terp

reta

tio

n c

rite

ria

Ne

op

lastic c

ell

co

nte

nt

Me

tho

ds u

se

d

Me

tho

d s

en

sitiv

ity

Sp

ecific

atio

n o

f te

ste

dm

uta

tio

ns

Re

fere

nce

se

qu

en

ce

FISH IHC variantanalysis

Ite

m p

rese

nt a

nd

co

rre

ct (%

)

ALK ROS1 PD-L1 Molecular scheme MET

46

Upcoming ESP Lung EQA schemes

ESP Lung EQA scheme

2020

IQN Path cfDNA EQA scheme

2019-2020

Registrations open now until 18 JAN 2019 Registration period: TBD

3 rounds:

▪ March (wet samples)

▪ May (digital cases)

▪ September (wet samples)

Sample distribution:

▪ February 2020

▪ 5 plasma samples

▪ common EGFR variants

5 digital images for ALK/ROS1 FISH schemes

4 digitals for PD-L1 IHC

Technical evaluation for IHC schemes

5 pre-validated FFPE resections

10 for molecular DNA scheme

1 report/subscheme (mol. DNA scheme: 2 reports)

47

2020: Free participation to PD-L1 subscheme

for BE participants thanks to

The 2020 ESP Lung EQA scheme

New features

PD-L1 ALK ROS1 EGFR

KRAS/BRAF

C-MET

IHC IHC IHC

FISHFISH

Genomic variant analysis

RNA-based analysis

One combined scheme

EGFR = mandatory

New scheme for detection of

ALK/ROS1 fusions and

MET exon 14 skippng

48

New participants platform

www.eqascheme.org

▪ Modernized look

▪ Ease of use

▪ Inegrated datasheets

▪ Automated emailing

▪ One platform for all EQA schemes

Lung, cfDNA, Cystic Fibrosis,

Clonality, …

❑ CF 2020: ongoing

❑ Clonality 2020: January 2020

❑ cfDNA 2020: January 2020

❑ Lung 2021: November 2020

49

http://www.eqascheme.org/

Scheme coordinator and assistant coordinators Prof. Dr. Dequeker E., Gentens R., Hombroeckx E, Tembuyser L., Tack

V., Keppens C., Dufraing K., Van Casteren K, Nauwelaers I

European Society of Pathology Sc. Director Aldieri R., Byrhanga S, Short M,

The reference laboratories University Medical Center Groningen, Groningen, The Netherlands

Erasmus MC, Rotterdam, The Netherlands,

Radboud UMC, Nijmegen, The Netherlands

University Hospital Antwerp, Edegem, Belgium

Charles University, Hradec Králové, Czech Republic

Center of Excellence on Aging, Chieti, Italy

Hospital University Vall d´Hebron, Barcelona, Spain

Institut for Pathology, Cologne, Germany

Institute for Pathology, Basel, Switzerland

Laboratorio de Dianas Terapéuticas, Madrid, Spain

UCL advanced diagnostics, London, UK

VU University Medical Centre, Amsterdam, The Netherlands

UZ Leuven, Leuven, Belgium

The medical/technical experts Prof. Dr. Schuuring E., Dr. ‘t Hart N.,

Dr. von der Thüsen J, Prof. Dr. Ryska A,

Prof. Dr. Pauwels P., Dr. Zwaenepoel K.,

Prof. Dr. Ales Ryska, prof. Dr. Erik Thunnissen

The assessors Bubendorf L., Cabillic F., Delen S., Marchetti A., Miller K.,

Pauwels P., Rouleau E, Ryska A., Schuuring E., Stenzinger A,

t Hart N., Thunnissen E., Tornillo L.., Warth A., Weichert W.,

Zwaenepoel K

Scheme sponsors AstraZeneca Belgium, Pfizer Oncology, Bristol-Myers Squibb, Roche

Turkey, Pfizer (Poland, Croatia, Serbia and Central Balkan Countries),

Pfizer (Czech Republic, Hungary, Slovakia)

The participating laboratories

Acknowledgements

esp lung eqa schemes - olv z

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