Retrospective clinical samples were used to establish the sensitivity and specificity of the device by comparing results against clinically defined patient groups and predicate device performance.
Clinical validation of EUROLINE Profile Autoimmune Liver Disease 8 Ag (IgG); Retrospective clinical cohort study
Patients with Primary Biliary Cirrhosis (PBC), Autoimmune Hepatitis (AIH), Viral Hepatitis, Primary Sclerosing Cholangitis, and other control conditions; Sample Size: 734 samples total; Number of Sites: Multiple sites
Not applicable for this study
Sensitivity and specificity for autoantibodies (AMA-M2, M2-3E, Sp100, PML, gp210, LKM-1, LC-1, SLA/LP)
Indications for Use
The EUROLINE Profile Autoimmune Liver Disease 8 Ag (IgG) Kit is an immune line-blot strip test intended for the qualitative detection of IgG class antibodies against 8 different antigens: AMA-M2, M2-3E (BPO), Sp100, PML, gp210, LKM-1, LC-1 and SLA/LP in human serum and plasma (EDTA, Li-heparin, Citrate). Detection of these antibodies is used as an aid in the diagnosis of autoimmune liver diseases in conjunction with other laboratory and clinical findings.
Device Story
The EUROLINE Profile Autoimmune Liver Disease 8 Ag (IgG) is an immunoblot test for detecting autoantibodies in human serum or plasma. The device uses antigen-coated membrane strips as the solid phase. Patient samples are incubated on the strips; if specific antibodies are present, they bind to the antigens. An alkaline phosphatase-labeled anti-human IgG conjugate is added, followed by a chromogenic substrate (NBT/BCIP). This produces a visible color reaction at the antigen-specific band site. The test is performed in a clinical or hospital laboratory by trained personnel. Results are evaluated visually by comparing band intensity against a reaction control card. The presence of specific antibodies aids clinicians in diagnosing autoimmune liver diseases, such as primary biliary cirrhosis or autoimmune hepatitis, when combined with other clinical and laboratory findings. The device provides qualitative results for each antibody separately.
Clinical Evidence
Clinical validation involved 734 samples from various patient groups (PBC, AIH, viral hepatitis, PSC, and other controls). Sensitivity for PBC (AMA-M2) was 85.4% (95% CI: 79.8-89.9%). Specificity for PBC across all antigens ranged from 97.2% to 99.8%. For AIH, sensitivity for LKM-1 was 12.3% (overall) and 85.7% (Type 2 AIH). Specificity for AIH across LKM-1, LC-1, and SLA/LP ranged from 98.8% to 99.8%. Method comparison with predicate ELISAs showed high agreement; discrepant samples were primarily from PBC patients. No positive results were found in 150 healthy blood donors.
Technological Characteristics
Qualitative immunoblot (lineblot) assay. Uses purified/recombinant antigens (AMA-M2, M2-3E, Sp100, PML, gp210, LKM-1, LC-1, SLA/LP) coated on membrane strips. Detection via alkaline phosphatase-labeled anti-human IgG conjugate and NBT/BCIP chromogenic substrate. Manual procedure: sample incubation, wash, conjugate incubation, wash, substrate incubation, and visual evaluation. No electronic components or software algorithms; evaluation is visual based on band intensity relative to a control card.
Indications for Use
Indicated for qualitative detection of IgG antibodies against 8 liver-related antigens (AMA-M2, M2-3E, Sp100, PML, gp210, LKM-1, LC-1, SLA/LP) in human serum/plasma to aid diagnosis of autoimmune liver diseases. For prescription use only.
Regulatory Classification
Identification
A multiple autoantibodies immunological test system is a device that consists of the reagents used to measure by immunochemical techniques the autoantibodies (antibodies produced against the body's own tissues) in serum and other body fluids. Measurement of multiple autoantibodies aids in the diagnosis of autoimmune disorders (disease produced when the body's own tissues are injured by autoantibodies).
Predicate Devices
Quanta Lite M2 EP (MIT3) ELISA (k052262)
Quanta Lite Sp100 ELISA (k050662)
Quanta Lite gp210 ELISA (k040885)
Quanta Lite LKM-1 ELISA (k000535)
Quanta Lite SLA ELISA (k021482)
Submission Summary (Full Text)
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# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY
A. 510(k) Number:
k113439
B. Purpose for Submission:
New device
C. Measurand:
IgG antibodies to AMA-M2, M2-3E (BPO), Sp100, PML, gp210, LKM-1, LC-1, SLA/LP
D. Type of Test:
Manual and automated read-out, qualitative immunoblot assay
E. Applicant:
EUROIMMUN US Inc.
F. Proprietary and Established Names:
EUROLINE Profile Autoimmune Liver Disease 8 Ag (IgG) Kit
G. Regulatory Information:
1. Regulation section:
21CFR§866.5090 – Antimitochondrial antibody immunological test system
2 CFR§866.5660 – Multiple autoantibodies immunological test system
2. Classification:
Class II
3. Product code:
DBM - Antimitochondrial antibody, indirect immunofluorescent, antigen, control
NUM - Autoantibodies, nuclear body protein, Sp100
NRI - Autoantibodies, nuclear pore glycoprotein gp210
NIY - Autoantibodies, anti-soluble liver antigen (SLA), autoimmune hepatitis
NBS - Autoantibodies, LKM-1(liver/kidney microsome, type 1)
4. Panel:
Immunology (82)
H. Intended Use:
1. Intended use(s):
The EUROLINE Profile Autoimmune Liver Disease 8 Ag (IgG) Kit is an immune line-blot strip test intended for the qualitative detection of IgG class antibodies against 8 different antigens: AMA-M2, M2-3E (BPO), Sp100, PML, gp210, LKM-1, LC-1 and SLA/LP in human serum and plasma (EDTA, Li-heparin, Citrate).
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Detection of these antibodies is used as an aid in the diagnosis of autoimmune liver diseases in conjunction with other laboratory and clinical findings.
2. Indication(s) for use:
Same as intended use
3. Special conditions for use statement(s):
For Prescription use only.
4. Special instrument requirements:
CanoScan LiDE Series flatbed scanner using ScanGear and EUROLineScan softwares for automated read.
# I. Device Description:
The EUROLINE Profile Autoimmune Liver Disease 8 Ag (IgG) Kit consists of antigen coated line blot strips, a positive control (100x concentrate), biotin-ExtrAvidin-alkaline phosphatase-labeled goat anti-human IgG conjugate (10X concentrate), sample buffer (ready-to-use), wash buffer (10X concentrate), Nitrobluetetrazoliumchloride/5-Bromo-4-chloro-3-indolylphosphate (NBT/BCIP) substrate solution (ready-to-use), incubation tray and test instruction.
# J. Substantial Equivalence Information:
1. Predicate device name(s) and 510(k) number(s):
| EUROLINE Profile Autoimmune Liver Disease Autoantibodies | Predicate device | 510(k) number |
| --- | --- | --- |
| Anti-AMA-M2/M2-3E (BPO) | Quanta Lite M2 EP (MIT3) ELISA | k052262 |
| Anti-Sp100 and PML | Quanta Lite Sp100 ELISA | k050662 |
| Anti-gp210 | Quanta Lite gp210 ELISA | k040885 |
| Anti-LKM-1 and LC-1 | Quanta Lite LKM-1 ELISA | k000535 |
| Anti-SLA/LP | Quanta Lite SLA ELISA | k021482 |
2. Comparison with predicate:
| Similarities | | | |
| --- | --- | --- | --- |
| Item | Device | | Predicate |
| Intended Use | Qualitative detection of IgG antibodies against 8 different antigens complete to aid in the diagnosis of autoimmune liver diseases. | | Same (when combined) |
| Capture antigens | Sp100 | Recombinant Sp100, expressed by cloning the corresponding human cDNA in E.coli | Same |
| | gp210 | Recombinant gp210, expressed by cloning the corresponding | Same |
| | | human cDNA in E.coli | |
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| Similarities | | | |
| --- | --- | --- | --- |
| Item | Device | | Predicate |
| | | human cDNA in E.coli | |
| | LKM-1 | Recombinant cytochrome P450 IID6, expressed by cloning the corresponding human cDNA in insect cells using a baculovirus vector. | Same |
| | SLA/LP | Recombinant SLA/LP, expressed by cloning the corresponding human cDNA in E.coli | Same |
| Detection antibody | Goat anti-human IgG | | Same |
| Sample dilution | 1:101 | | Same |
| Differences | | | |
| --- | --- | --- | --- |
| Item | Device | | Predicate |
| Assay format | Qualitative, positive/negative | | Semi-quantitative |
| Solid phase | Membrane test strips | | Polystyrene microwells |
| Instrument | Manual visual readout | | Spectrophotometer |
| Capture antigens | AMA-M2 | Natively purified from bovine heart | Affinity purified recombinant M2 EP MIT3. |
| | M2-3E (BPO) | Recombinant fusion protein, produced in E.coli | |
| | PML | Recombinant PML, expressed by cloning the corresponding human cDNA in E.coli | Not included |
| | LC-1 | Recombinant LC-1 expressed by cloning the corresponding human cDNA in insect cells using a baculovirus vector. | Not included |
| Sample type | Serum or plasma (EDTA, Li-heparin, Citrate) | | Serum |
| Controls | One positive control, 100X concentrate | | 3 controls (high positive, low positive, negative) |
| Conjugate | biotin-ErxtAvidin-alkaline phosphatase, 10X concentrate | | horseradish peroxidase |
| Substrate | NBT/BCIP | | 3,5',5',5' Tetramethylbenzidine |
| Interpretation of results | positive/negative compared to reaction control card | | Units |
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K. Standard/Guidance Document Referenced (if applicable):
DIN EN 13640:2002: Stability testing of in vitro diagnostic reagents
L. Test Principle:
The principle of the EUROLINE Profile Autoimmune Liver Disease 8 Ag (IgG) Kit is that of an enzyme linked immunosorbent assay (ELISA), using a membrane as the solid phase instead of microtiter wells. Different purified antigens have been coated and applied in easy to read lines (bands) onto a membrane strip.
Autoantibodies in patient samples bind to the bands and are detected via a secondary antibody linked to an enzyme. The strips are evaluated visually by comparison of the band intensity with the reaction control card or scanned and then evaluated with EUROLineScan.
The control band on the strips contains (non-specific) anti-human IgG, which reacts with the sample IgG to show a color reaction if the incubation was performed correctly and so represents a function test on each single strip.
The positive control contains a mixture of the targeted antibodies which bind to the antigen coated on the blot strips. A strip incubated with the positive control shows a positive result. If either the control band or the strip incubated with the positive control is negative, test results are invalid and should be repeated.
The qualitative results are reported for each individual antibody separately as positive or negative. The intensity of the reaction is not reported but only as a means to distinguish between a positive and negative reaction and not as an indication of disease status. The interpretation of the test results does not include a combined score or diagnosis.
M. Performance Characteristics (if/when applicable):
1. Analytical performance:
Test results were evaluated by visual or automated reading of the test strips.
For visual evaluation, the reaction intensity of each antigen band on the test strip was compared to the two color bars on the reaction control card that correspond to the intensities just below (negative) and just above (positive) the cut-off.
For automated evaluation, the test strips are scanned using a flatbed scanner and evaluated with EUROLineScan with a cut-off of 11 grey scale units.
a. Precision/Reproducibility:
i. Visual evaluation.
Assay reproducibility was determined by testing 5 to 9 samples that cover the complete range of results (negative, positive and near to cut-off) for each antigen (see table below). The intra-assay reproducibility is based on 20 replicates tested in one day and the inter-assay reproducibility on 20 different runs, each run performed by the same reader on a different day. The lot-to-lot reproducibility was tested in 3 different runs using 3 different lots. The reproducibility data showed no positive sample was
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found negative and vice versa.
The inter-reader reproducibility of 3 samples that cover the complete range of results (negative, positive and near to cut-off) for each antigen (see table below) was evaluated by 3 different technicians and under 3 different light conditions (sunlight, neon light and electric bulb light). No deviation was observed between the individual readings and from the light conditions.
Intra-assay reproducibility
| Antigen band | Sample characterization | Sample Number | Visual evaluation result | |
| --- | --- | --- | --- | --- |
| | | | % pos | % neg |
| AMA-M2 | pos | 2 | 100% | 0% |
| | neg (near to cut-off) | 1 | 0% | 100% |
| | neg | 2 | 0% | 100% |
| M2-3E | pos | 2 | 100% | 0% |
| | neg (near to cut-off) | 1 | 0% | 100% |
| | neg | 2 | 0% | 100% |
| Sp100 | pos | 1 | 100% | 0% |
| | neg (near to cut-off) | 1 | 0% | 100% |
| | neg | 3 | 0% | 100% |
| PML | pos | 1 | 100% | 0% |
| | pos (near to cut-off) | 1 | 100% | 0% |
| | neg | 3 | 0% | 100% |
| gp210 | pos | 1 | 100% | 0% |
| | pos (near to cut-off) | 1 | 100% | 0% |
| | neg | 3 | 0% | 100% |
| LKM-1 | pos | 2 | 100% | 0% |
| | neg (near to cut-off) | 1 | 0% | 100 |
| | neg | 2 | 0% | 100% |
| LC-1 | pos | 1 | 100% | 0% |
| | neg (near to cut-off) | 1 | 0% | 100% |
| | neg | 3 | 0% | 100% |
| SLA/LP | pos | 1 | 100% | 0% |
| | neg (near to cut-off) | 1 | 0% | 100% |
| | neg | 3 | 0% | 100% |
Inter-assay reproducibility
| Antigen band | Sample characterization | Sample Number | Visual evaluation result | |
| --- | --- | --- | --- | --- |
| | | | % pos | % neg |
| AMA-M2 | pos | 2 | 100% | 0% |
| | pos (near to cut-off) | 3 | 100% | 0% |
| | neg (near to cut-off) | 1 | 40% | 60% |
| | neg (near to cut-off) | 1 | 55% | 45% |
| | neg | 2 | 0% | 100% |
| M2-3E | pos | 2 | 100% | 0% |
| | pos (near to cut-off) | 1 | 100% | 0% |
| | neg (near to cut-off) | 3 | 95% | 5% |
| | neg (near to cut-off) | 1 | 90% | 10% |
| | neg | 2 | 0% | 100% |
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| Antigen band | Sample characterization | Sample Number | Visual evaluation result | |
| --- | --- | --- | --- | --- |
| | | | % pos | % neg |
| Sp100 | pos | 2 | 100% | 0% |
| | pos (near to cut-off) | 5 | 100% | 0% |
| | neg | 2 | 0% | 100% |
| PML | pos | 1 | 100% | 0% |
| | pos (near to cut-off) | 1 | 100% | 0% |
| | neg (near to cut-off) | 2 | 80% | 20% |
| | neg (near to cut-off) | 2 | 75% | 25% |
| | neg | 2 | 0% | 100% |
| gp210 | pos | 2 | 100% | 0% |
| | pos (near to cut-off) | 1 | 100% | 0% |
| | neg (near to cut-off) | 1 | 45% | 55% |
| | neg (near to cut-off) | 1 | 40% | 60% |
| | neg | 2 | 0% | 100% |
| LKM-1 | pos | 1 | 100% | 0% |
| | pos (near to cut-off) | 3 | 100% | 0% |
| | neg (near to cut-off) | 2 | 80% | 20% |
| | neg | 2 | 0% | 100% |
| LC-1 | pos | 1 | 100% | 0% |
| | pos (near to cut-off) | 1 | 100% | 0% |
| | neg (near to cut-off) | 1 | 90% | 10% |
| | neg (near to cut-off) | 1 | 80% | 20% |
| | neg (near to cut-off) | 1 | 75% | 25% |
| | neg | 2 | 0% | 100% |
| SLA/LP | pos | 1 | 100% | 0% |
| | pos (near to cut-off) | 1 | 100% | 0% |
| | neg (near to cut-off) | 2 | 55% | 45% |
| | neg (near to cut-off) | 1 | 45% | 55% |
| | neg (near to cut-off) | 1 | 40% | 60% |
| | neg | 2 | 0% | 100% |
Inter-reader reproducibility:
| Antigen band | Sample characterization | Sample Number | Visual evaluation result | |
| --- | --- | --- | --- | --- |
| | | | % pos | % neg |
| AMA-M2 | pos | 2 | 100% | 0% |
| | neg (near to cut-off) | 1 | 0% | 100% |
| | neg | 2 | 0% | 100% |
| M2-3E | pos | 3 | 100% | 0% |
| | neg | 2 | 0% | 100% |
| Sp100 | pos | 2 | 100% | 0% |
| | neg (near to cut-off) | 1 | 0% | 100% |
| | neg | 2 | 0% | 100% |
| PML | pos | 2 | 100% | 0% |
| | neg | 3 | 0% | 100% |
| gp210 | pos | 2 | 100% | 0% |
| | neg | 3 | 0% | 100% |
| LKM-1 | pos | 2 | 100% | 0% |
| | neg (near to cut-off) | 1 | 0% | 100% |
| | neg | 2 | 0% | 100% |
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| Antigen band | Sample characterization | Sample Number | Visual evaluation result | |
| --- | --- | --- | --- | --- |
| | | | % pos | % neg |
| LC-1 | pos | 2 | 100% | 0% |
| | neg (near to cut-off) | 1 | 0% | 100% |
| | neg | 2 | 0% | 100% |
| SLA/LP | pos | 1 | 100% | 0% |
| | neg (near to cut-off) | 1 | 0% | 100% |
| | neg | 3 | 0% | 100% |
ii. Automated evaluation.
The reproducibility of the automatic evaluation was investigated by repeated scanning and analysis of test strips incubated with 16 different serum samples displaying signals for different antibodies near the cut off. The processed test strips were scanned using three different flatbed scanners, each scanner was used 10 times scanning the same strips and the results were evaluated by EUROLineScan. The scanner intensity values of the 30 analyses were used to calculate coefficients of variation (CV's). The results are shown in the tables below.
Samples near the cut-off (n = 3 x 10 = 30)
| Sample | EUROLineScan Intensity values | | |
| --- | --- | --- | --- |
| | Mean value | SD | % CV |
| AMA-M2 | 13 | 0.7 | 5.5 |
| M2-3E | 14 | 0.4 | 2.7 |
| Sp100 | 12 | 0.4 | 3.1 |
| PML | 13 | 0.4 | 3.4 |
| gp210 | 12 | 0.0 | 0.0 |
| LKM-1 | 14 | 0.5 | 3.9 |
| LC-1 | 12 | 0.2 | 1.5 |
| SLA/LP | 14 | 0.7 | 4.9 |
Positive samples (n = 3 x 10 = 30)
| Sample | EUROLineScan Intensity values | | |
| --- | --- | --- | --- |
| | Mean value | SD | % CV |
| AMA-M2 | 69 | 0.7 | 1.0 |
| M2-3E | 37 | 0.4 | 1.0 |
| Sp100 | 47 | 0.6 | 1.3 |
| PML | 66 | 0.4 | 0.7 |
| gp210 | 51 | 0.7 | 1.3 |
| LKM-1 | 73 | 0.6 | 0.8 |
| LC-1 | not available | | |
| SLA/LP | 39 | 0.4 | 0.9 |
iii. Comparability of visual and automatic reading
The use of the EUROLineScan software compared to visual reading was investigated using a panel of serum sample preparations covering the whole range of antigens. The samples were tested in 20 different runs, each run on a different day using the same kit lot. Each run was performed by the same technician and evaluation was performed both
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visually using the reaction control card and automatically using the EUROLineScan software with a cut-off of 11 grey scale units. The results are shown in the table below. Only a few results from sample preparations exactly at the cut-off gave discrepant results between visual and automatic reading.
| Antigen | Sample Characterization | Visual evaluation result | | EUROLineScan result | | Grey scale units result | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | % pos | % neg | % pos | % neg | Mean | Range |
| AMA-M2 | pos (near to cut-off) | 100% | 0% | 100% | 0% | 15 | 13 - 18 |
| | pos | 100% | 0% | 100% | 0% | 68 | 60 - 76 |
| | Neg | 0% | 100% | 0% | 100% | 1 | 0 - 1 |
| | neg | 0% | 100% | 0% | 100% | 1 | 0 - 2 |
| | pos | 100% | 0% | 100% | 0% | 54 | 48 - 58 |
| | pos (near to cut-off) | 100% | 0% | 100% | 0% | 13 | 11 - 15 |
| | pos (near to cut-off) | 100% | 0% | 100% | 0% | 14 | 11 - 16 |
| | neg (near to cut-off) | 40% | 60% | 40% | 60% | 10 | 6 - 12 |
| | neg (near to cut-off) | 55% | 45% | 55% | 45% | 11 | 8 - 12 |
| M2-3E | pos (near to cut-off) | 100% | 0% | 100% | 0% | 18 | 14 - 23 |
| | pos | 100% | 0% | 100% | 0% | 47 | 38 - 57 |
| | neg | 0% | 100% | 0% | 100% | 2 | 2 - 3 |
| | neg | 0% | 100% | 0% | 100% | 3 | 2 - 4 |
| | pos | 100% | 0% | 100% | 0% | 40 | 32 - 45 |
| | pos (near to cut-off) | 95% | 5% | 95% | 5% | 13 | 10 - 15 |
| | neg (near to cut-off) | 95% | 5% | 95% | 5% | 12 | 10 - 15 |
| | neg (near to cut-off) | 90% | 10% | 90% | 10% | 12 | 10 - 15 |
| | pos (near to cut-off) | 95% | 5% | 95% | 5% | 13 | 10 - 15 |
| Sp100 | pos | 100% | 0% | 100% | 0% | 45 | 38 - 49 |
| | pos (near to cut-off) | 100% | 0% | 100% | 0% | 14 | 11 - 17 |
| | neg | 0% | 100% | 0% | 100% | 0 | 0 - 1 |
| | neg | 0% | 100% | 0% | 100% | 0 | 0 - 1 |
| | pos | 100% | 0% | 100% | 0% | 86 | 75 - 96 |
| | pos (near to cut-off) | 100% | 0% | 100% | 0% | 14 | 11 - 17 |
| | pos (near to cut-off) | 100% | 0% | 100% | 0% | 14 | 11 - 17 |
| | pos (near to cut-off) | 100% | 0% | 100% | 0% | 14 | 11 - 18 |
| | pos (near to cut-off) | 100% | 0% | 100% | 0% | 14 | 11 - 19 |
| PML | pos (near to cut-off) | 100% | 0% | 100% | 0% | 16 | 12 - 20 |
| | pos | 100% | 0% | 100% | 0% | 68 | 62 - 78 |
| | neg | 0% | 100% | 0% | 100% | 1 | 1 - 2 |
| | neg | 0% | 100% | 0% | 100% | 1 | 0 - 2 |
| | neg (near to cut-off) | 75% | 25% | 75% | 25% | 12 | 8 - 14 |
| | neg (near to cut-off) | 75% | 25% | 75% | 25% | 12 | 10 - 14 |
| | neg (near to cut-off) | 80% | 20% | 80% | 20% | 12 | 7 - 14 |
| | neg (near to cut-off) | 80% | 20% | 80% | 20% | 11 | 10 - 13 |
| gp210 | pos (near to cut-off) | 100% | 0% | 100% | 0% | 13 | 11 - 15 |
| | pos | 100% | 0% | 100% | 0% | 53 | 46 - 58 |
| | neg | 0% | 100% | 0% | 100% | 1 | 1 - 2 |
| | neg | 0% | 100% | 0% | 100% | 0 | 0 - 1 |
| | pos | 100% | 0% | 100% | 0% | 135 | 131 - 140 |
| | neg (near to cut-off) | 45% | 55% | 45% | 55% | 11 | 8 - 12 |
| | neg (near to cut-off) | 40% | 60% | 40% | 60% | 10 | 9 - 12 |
| | neg (near to cut-off) | 45% | 55% | 45% | 55% | 11 | 9 - 13 |
| | neg (near to cut-off) | 40% | 60% | 40% | 60% | 11 | 9 - 13 |
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| Antigen | Sample Characterization | Visual evaluation result | | EUROLineScan result | | Grey scale units result | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | % pos | % neg | % pos | % neg | Mean | Range |
| LKM-1 | pos (near to cut-off) | 100% | 0% | 100% | 0% | 13 | 12 - 16 |
| | pos | 100% | 0% | 100% | 0% | 71 | 63 - 79 |
| | neg | 0% | 100% | 0% | 100% | 1 | 0 - 2 |
| | neg | 0% | 100% | 0% | 100% | 1 | 0 - 1 |
| | pos (near to cut-off) | 100% | 0% | 95% | 5% | 14 | 10 - 17 |
| | pos (near to cut-off) | 100% | 0% | 100% | 0% | 13 | 12 - 16 |
| | neg (near to cut-off) | 80% | 20% | 80% | 20% | 11 | 10 - 14 |
| | neg (near to cut-off) | 80% | 20% | 80% | 20% | 12 | 10 - 14 |
| LC-1 | pos | 100% | 0% | 100% | 0% | 52 | 36 - 59 |
| | pos | 100% | 0% | 100% | 0% | 98 | 89 - 104 |
| | pos (near to cut-off) | 100% | 0% | 100% | 0% | 12 | 11 - 16 |
| | neg | 0% | 100% | 0% | 100% | 1 | 0 - 2 |
| | neg | 0% | 100% | 0% | 100% | 0 | 0 - 2 |
| | neg (near to cut-off) | 55% | 45% | 40% | 60% | 11 | 8 - 17 |
| | neg (near to cut-off) | 90% | 10% | 90% | 10% | 12 | 10 - 16 |
| | neg (near to cut-off) | 75% | 25% | 75% | 25% | 12 | 10 - 14 |
| | neg (near to cut-off) | 80% | 20% | 80% | 20% | 12 | 10 - 14 |
| SLA/LP | pos (near to cut-off) | 100% | 0% | 100% | 0% | 16 | 13 - 18 |
| | pos | 100% | 0% | 100% | 0% | 41 | 36 - 45 |
| | neg | 0% | 100% | 0% | 100% | 1 | 0 - 1 |
| | neg | 0% | 100% | 0% | 100% | 0 | 0 - 1 |
| | neg (near to cut-off) | 55% | 45% | 55% | 45% | 11 | 8 - 12 |
| | neg (near to cut-off) | 40% | 60% | 40% | 60% | 11 | 8 - 14 |
| | neg (near to cut-off) | 45% | 55% | 45% | 55% | 11 | 10 - 14 |
| | neg (near to cut-off) | 55% | 45% | 55% | 45% | 11 | 8 -14 |
b. Linearity/assay reportable range:
Not applicable
c. Traceability, Stability, Expected values (controls, calibrators, or methods):
Traceability: There are no reference standards for these analytes.
Kit Stability:
i. Real-time and Accelerated stability
The stability studies were performed in accordance with EN 13640 (Stability Testing of In Vitro Diagnostic Reagents) to demonstrate unopened kit shelf-life stability (from the date of manufacture when stored at recommended temperature $2 - 8^{\circ}\mathrm{C}$ ) and opened kit shelf-life stability. The acceptance criteria are that results do not differ more than one result level [pos, pos (near the cutoff), neg (near the cutoff) and neg] from the reference run.
For real-time stability study, three lots of all kit components stored at recommended storage temperature $2 - 8^{\circ}\mathrm{C}$ were evaluated at different occasions with three samples per antigen band. Original sealed kits and opened kits were demonstrated to be stable for up to 18 and 12 months, respectively, when stored at $2 - 8^{\circ}\mathrm{C}$ .
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For accelerated study, three lots of all kits components were stored for 7 days at 37°C and evaluated with 3 samples per antigen band. The same lots stored at 4°C were used as reference. Reagents were shown to be stable for 7 days at 37°C.
ii. Transport stability
To simulate transportation of kits from Europe to US, one lot of an example EuroLine test kit with equal composition and technology as EUROLINE Profile Autoimmune Liver Disease 8 Ag (IgG) Kit was stored for 7 days at 4°C and -20°C and evaluated with 4 different samples. Transportation has no significant influence on the results.
d. Detection limit:
Not applicable
e. Analytical specificity:
Cross-reactivity: Cross-reactivity was investigated using a panel of samples serologically positive for antibodies to granulocyte cytoplasm (n = 10), thyroid gland antigens (n=10), islet cell antigens (n=10), cardiolipin/anti-phospholipid syndrome (n=5) and the CDC ANA reference panel (n=12). Clinical samples from the following groups were also included: autoimmune hepatitis type 1 (n=84), primary sclerosing cholangitis (n=19), systemic lupus erythematosus (n=10), rheumatoid arthritis (n=50), celiac disease (n=7), non-alcoholic steatohepatitis (n=30) and viral hepatitis (HBV, HCV; n=39). Out of 286 total samples, 9 samples tested positive.
Interferences: Interference testing was performed for each antigen using at least 5 samples that cover the complete range of results (negative, positive and near to cut-off) for each antigen. Each sample was spiked with three different levels of endogenous interfering substances, namely hemoglobin, triglycerides and bilirubin. Evaluation of test results was performed visually and no significant interference was observed for concentrations up to 500 mg/dl for hemoglobin, 2000 mg/dl for triglycerides and 40 mg/dl for bilirubin.
f. Assay cut-off:
The cut-off is predefined by the visual evaluation. A sample is positive if the respective band is clearly visible. The cutoff for each antigen on the EUROLINE was set to the lowest limit of a clearly visible band. To achieve the uniform cut-off for each antigen, during the production several sample strips for each antigen are manufactured with the antigen used in different dilutions. These sample strips are then processed with positive and negative reference sera and the optimal dilution for each antigen is identified. Afterwards the strips are manufactured using each antigen in its optimal dilution.
To confirm the assay cut-off, 261 clinically characterized samples from PBC and AIH patients, as well as 171 control samples were tested. The results
10
{10}
showed that negative and positive results can clearly be discriminated by the assay.
## 2. Comparison studies:
### a. Method comparison with predicate device:
A total of 295 clinically characterized samples (99 from patients with autoimmune hepatitis, 89 from patients with primary biliary cirrhosis, 15 from patients with AIH/PBC overlap syndrome, 42 from patients with viral hepatitis, and 50 from patients with rheumatoid arthritis (RA)) were evaluated and results were compared to the results for the predicate devices. In addition, 6 to 29 artificial samples with antibody concentrations close to the cut-off were created for each antigen by mixing positive samples with negative sample as diluent of the same matrix. The results and the positive and negative agreement between the device and the predicates are shown below. Borderline results (from the predicate) were not included in the agreement calculations.
| | Predicate ELISA | | | Positive agreement*
Negative agreement*
% (95% C.I.)* | | |
| --- | --- | --- | --- | --- | --- | --- |
| | | | positive | | borderline | negative |
| EUROLINE Profile Autoimmune Liver Disease 8 Ag (IgG) Kit | n = 281 | | M2 EP (MIT3) | | | Pos: 95.1 % (88.9 – 98.4 %)
Neg: 98.9 % (95.9 – 99.9 %) |
| | AMA-M2 and/or M2-3E | positive | 97 | 0 | 2 | |
| | | negative | 5 | 4 | 173 | |
| | n = 293 | | Sp100 | | | Pos: 94.4 % (81.3 – 99.3 %)
Neg: 99.2 % (97.2 – 99.9 %) |
| | Sp100 | positive | 34 | 1 | 2 | |
| | | negative | 2 | 2 | 252 | |
| | n = 296 | | gp210 | | | Pos: 100 % (89.4 – 100 %)
Neg: 88.5 % (84.0 – 92.1 %) |
| | gp210 | positive | 33 | 2 | 30*** | |
| | | negative | 0 | 0 | 231 | |
| | n = 325 | | LKM-1 | | | Pos: 92.6 % (82.1 – 97.9 %)
Neg: 98.9 % (96.8 – 99.8 %) |
| | LKM-1 | positive | 50 | 0 | 3 | |
| | | negative | 4 | 1 | 267 | |
| | n = 298 | | SLA | | | Pos: 100 % (88.4 – 100 %)
Neg: 99.6 % (97.9 – 100.0 %) |
| | SLA/LP | positive | 30 | 0 | 1 | |
| negative | | 0 | 1 | 266 | | |
* Calculations do not include borderline samples; ** 20 PBC, 1 artificial; *** 16 PBC, 7 AIH, 6 AIH/PBC, 1 RA.
### b. Matrix comparison:
Comparisons between serum and each of EDTA, heparin, and citrated plasma were performed using 8-11 sample pairs selected to cover the complete range of results (negative, positive and close to cut-off) for each antigen. The results found no positive sample was found negative and vice versa.
## 1. Clinical studies:
### a. Clinical Sensitivity:
A total of 734 clinically characterized samples obtained from different study sites were analyzed by the EUROLINE Profile Autoimmune Liver Disease 8 Ag (IgG) Kit. The sites providing the indicated panel of samples are as follow:
{11}
The results of the clinical studies are shown in the following tables:
Sensitivity for Primary biliary liver cirrhosis (PBC)
| Panel | n (men, women) | Mean age (age range) | EUROLINE Profile Autoimmune Liver Disease 8 Ag (IgG) Kit Positive (% positive) (95% C.I.) | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | | AMA-M2 | M2-3E | Sp100 | PML | gp210 |
| PBC | 205 (20,185) | 58 y (22-90 y) | 175 (85.4 %) (79.8 - 89.9 %) | 160 (78.0 %) (71.8 - 83.5 %) | 54 (26.3 %) (20.5 - 32.9 %) | 58 (28.3 %) (22.2 - 35.0 %) | 68 (33.2 %) (26.8 - 40.1 %) |
Sensitivity for Autoimmune hepatitis (AIH)
| Panel | n (men, women) | Mean age (age range) | EUROLINE Profile Autoimmune Liver Disease 8 Ag (IgG) Kit Positive (% positive) (95% C.I.) | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | | LKM-1 | LC-1 | SLA/LP | | |
| AIH | 163 (20, 59, 84 un- known) | 38 y (1-86 y, 84 un- known) | 20 (12.3 %) (7.7 - 18.3 %) | 15 (9.2 %) (5.2 - 14.7 %) | 15 (9.2 %) (5.2 - 14.7 %) | | |
| Type 1 | 142 (16, 42, 84 un- known) | 48 y (20-86 y 84 un- known) | 2 (1.4 %) (0.2 - 5.0 %) | 1 (0.7 %) (0.0 - 3.9 %) | 15 (10.6 %) (6.0 - 16.8 %) | | |
| Type 2 | 21 (4, 17) | 12 y (1-45 y) | 18 (85.7 %) (63.7 - 97.0 %) | 14 (66.7 %) (43.0 - 85.4 %) | 0 (0.0 %) (0.0 - 16.1 %) | | |
b. Clinical specificity:
Specificity for PBC
| Panel | n (men, women) | Mean age (age range) | EUROLINE Profile Autoimmune Liver Disease 8 Ag (IgG) Kit Negative (% negative) (95% C.I.) | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | | AMA-M2 | M2-3E | Sp100 | PML | gp210 |
| AIH | 163 (20, 59, | 38 y (1-86 y, | 162 (99.4 %) | 162 (99.4 %) | 162 (99.4 %) | 163 (100 %) | 154 (94.5 %) |
| | 84 un- known) | 84 un- known) | | | | | |
| | | | | | | | |
{12}
13
| Panel | n (men, women) | Mean age (age range) | EUROLINE Profile Autoimmune Liver Disease 8 Ag (IgG) Kit Negative (% negative) (95% C.I.) | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | | AMA-M2 | M2-3E | Sp100 | PML | gp210 |
| | 84 unknown) | 84 unknown) | | | | | |
| Viral hepatitis | 39 (16, 23) | 48 y (25-84 y) | 39 (100 %) | 39 (100 %) | 39 (100 %) | 39 (100 %) | 39 (100 %) |
| PBC | 19 (12, 7) | 48 y (21-73 y) | 19 (100 %) | 19 (100 %) | 19 (100 %) | 19 (100 %) | 19 (100 %) |
| Further controls* | 308 (140, 167,1 unknown) | 18 y (0-83 y) | 304 (98.7 %) | 307 (99.7 %) | 308 (100 %) | 304 (98.7 %) | 302 (98.1 %) |
| Total | 529 | | 524 (99.1 %) (97.8 - 99.7 %) | 527 (99.6 %) (98.6 - 100 %) | 528 (99.8 %) (99.0 - 100 %) | 525 (99.2 %) (98.1 - 99.8 %) | 514 (97.2 %) (95.4 - 98.4 %) |
Specificity for AIH
| Panel | n (men, women) | Mean age (age range) | EUROLINE Profile Autoimmune Liver Disease 8 Ag (IgG) Kit Negative (% negative) (95% C.I.) | | |
| --- | --- | --- | --- | --- | --- |
| | | | LKM-1 | LC-1 | SLA/LP |
| PBC | 205 (20, 185) | 58 y (22-90 y) | 204 (99.5 %) | 205 (100 %) | 199 (97.1 %) |
| Viral hepatitis | 39 (16, 23) | 48 y (25-84 y) | 39 (100 %) | 39 (100 %) | 39 (100.0 %) |
| PSC | 19 (12, 7) | 48 y (21-73 y) | 19 (100 %) | 19 (100 %) | 19 (100.0 %) |
| Further controls* | 308 (140,167, 1 unkn.) | 18 y (0-83 y) | 308 (100 %) | 306 (99.4%) | 307 (99.7 %) |
| Total | 571 | | 570 (99.8 %) (99.0 - 100 %) | 569 (99.6 %) (98.7 - 100 %) | 564 (98.8 %) (97.5 - 99.5 %) |
*from the following groups: systemic lupus erythematosus (n = 10), Sjögren’s syndrome (n = 5), systemic sclerosis (n = 5), myositis (n = 4), rheumatoid arthritis (n = 50), diabetes (n = 9), celiac disease (n = 7), A1 antitrypsin deficiency (n = 30), Alagille syndrome (n = 29), biliary atresia (n = 35), giant cell hepatitis (n = 16), non-alcoholic steatohepatitis (n = 30), hemochromatosis (n = 17), progressive familial intrahepatic cholestatis (n = 31), Wilson’s disease (n = 30)
c. Other clinical supportive data (when a. and b. are not applicable):
Not applicable.
4. Clinical cut-off:
See Assay cut-off.
5. Expected values/Reference range:
The levels of analytes were analyzed in a panel of 150 healthy blood donors of mixed age and sex. None of these samples were found positive. It is
{13}
recommended that each laboratory determine its own normal range based on the population and equipment used.
**N. Proposed Labeling:**
The labeling is sufficient and it satisfies the requirements of 21 CFR Part 809.10.
**O. Conclusion:**
The submitted information in this premarket notification is complete and supports a substantial equivalence decision.
14
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Learn the FDA Browser
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.