GOLD STANDARD DIAGNOSTICS ANTI-NUCLEAR ANTIBODY (ANA) SCREEN ELISA TEST KIT
K131330 · Gold Standard Diagnostics · LJM · Jan 28, 2014 · Immunology
Device Facts
Record ID
K131330
Device Name
GOLD STANDARD DIAGNOSTICS ANTI-NUCLEAR ANTIBODY (ANA) SCREEN ELISA TEST KIT
Applicant
Gold Standard Diagnostics
Product Code
LJM · Immunology
Decision Date
Jan 28, 2014
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 866.5100
Device Class
Class 2
Attributes
Real-World Evidence
Real-World Evidence
Submission
Device
Sponsor
RWD Sources
RWE Use Summary
Key Tags
K131330 · Jan 28, 2014
GOLD STANDARD DIAGNOSTICS ANTI-NUCLEAR ANTIBODY (ANA) SCREEN ELISA TEST KIT
Gold Standard Diagnostics
Retrospective clinical serum samples from serum brokers with associated clinical diagnosis and demographic information
Retrospective clinical samples were used to evaluate the clinical sensitivity and specificity of the device across various connective tissue diseases (CTD) and non-CTD conditions.
Patients with various clinical diagnoses including Systemic Lupus Erythematosus (SLE), Systemic Sclerosis (SSc), Polymyositis (PM), Dermatomyositis (DM), Mixed Connective Tissue Disease (MCTD), Sjögren's Syndrome (SjS), and various non-CTD conditions.; Sample Size: 753
Not applicable for this study
Clinical sensitivity and specificity
Indications for Use
The Gold Standard Diagnostics Antinuclear Antibody (ANA) Screen ELISA Test Kit is a qualitative assay for the detection of ANAs in human serum. The assay collectively detects in one well ANAs against double stranded DNA (dsDNA), SSA (Ro60 and Ro52), SSB (La), Sm, Sm/RNP, Scl-70, Jo-1, Ribosomal P, and Centromeric antibodies along with sera positive for immunofluorescent HEp-2 ANAs. The assay is used as an aid in the diagnosis of Systemic Lupus Erythematosus, Mixed Connective Tissue Disease, Sjögren's Syndrome, Progressive Systemic Sclerosis, and Polymyositis/Dermatomyositis, and should be used in conjunction with other laboratory tests and clinical findings.
Device Story
The Gold Standard Diagnostics ANA Screen ELISA is an in vitro diagnostic test for human serum samples. The device uses microtiter wells coated with a mixture of antigens (dsDNA, SSA, SSB, Sm, Sm/RNP, Scl-70, Jo-1, Ribosomal P, and Centromeric proteins). Patient serum is added; if specific ANAs are present, they bind to the antigens. After washing, an HRP-conjugated anti-human IgG is added, followed by a TMB substrate. The resulting color intensity, proportional to the amount of bound antibody, is measured spectrophotometrically at 450nm. The assay is performed in a clinical laboratory setting by trained technicians. Results are reported as an OD ratio or converted to units to determine if the sample is negative, equivocal, or positive. Clinicians use these results in conjunction with other laboratory tests and clinical findings to support the diagnosis of systemic autoimmune rheumatic diseases.
Clinical Evidence
Clinical performance was evaluated using 848 samples across three sites, comparing the subject device to a commercially available ANA ELISA. With equivocal results treated as positives, percent positive agreement was 94.9% (95% CI: 91.5%-97.2%) and negative agreement was 92.2% (95% CI: 89.7%-94.2%). With equivocal results treated as negatives, positive agreement was 92.3% (95% CI: 88.4%-95.2%) and negative agreement was 96.2% (95% CI: 94.3%-97.6%). Additional testing on 55 samples confirmed reactivity across individual analytes. Clinical sensitivity and specificity were further assessed against diagnosed connective tissue disease (CTD) and non-CTD cohorts.
Technological Characteristics
ELISA-based qualitative assay using 96-well microtiter plates. Antigen mixture includes dsDNA, SSA (Ro60/Ro52), SSB (La), Sm, Sm/RNP, Scl-70, Jo-1, Ribosomal P, and Centromeric antibodies. Detection uses HRP-conjugated anti-human IgG and TMB substrate. Results measured spectrophotometrically at 450nm. Calibration is relative evaluation using cutoff, positive, and negative controls. Sample dilution is 1:101.
Indications for Use
Indicated for the qualitative detection of anti-nuclear antibodies (ANAs) in human serum to aid in the diagnosis of systemic autoimmune rheumatic diseases, including Systemic Lupus Erythematosus, Mixed Connective Tissue Disease, Sjögren's Syndrome, Progressive Systemic Sclerosis, and Polymyositis/Dermatomyositis. For prescription use only.
Regulatory Classification
Identification
An antinuclear antibody immunological test system is a device that consists of the reagents used to measure by immunochemical techniques the autoimmune antibodies in serum, other body fluids, and tissues that react with cellular nuclear constituents (molecules present in the nucleus of a cell, such as ribonucleic acid, deoxyribonucleic acid, or nuclear proteins). The measurements aid in the diagnosis of systemic lupus erythematosus (a multisystem autoimmune disease in which antibodies attack the victim's own tissues), hepatitis (a liver disease), rheumatoid arthritis, Sjögren's syndrome (arthritis with inflammation of the eye, eyelid, and salivary glands), and systemic sclerosis (chronic hardening and shrinking of many body tissues).
Predicate Devices
Aeskulisa ANA Hep2 (k040953)
Submission Summary (Full Text)
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510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION
DECISION SUMMARY
ASSAY ONLY
A. 510(k) Number:
k131330
B. Purpose for Submission:
New device
C. Measurand:
Anti-Nuclear Antibodies (ANA)
D. Type of Test:
Manual, qualitative enzyme linked immunosorbent assay (ELISA)
E. Applicant:
Gold Standard Diagnostics Corporation
F. Proprietary and Established Names:
Proprietary Name: Gold Standard Diagnostics Anti-nuclear Antibody (ANA) Screen ELISA Test Kit
Established Name: Antinuclear Antibody (Enzyme-Labeled), Antigen, Controls
G. Regulatory Information:
1. Regulation section:
21 CFR §866.5100 Antinuclear antibody immunological test system
2. Classification:
Class II
3. Product code:
LJM, antinuclear antibody (enzyme-labeled), antigen, controls
{1}
4. Panel:
82 (Immunology)
H. Intended Use:
1. Intended use(s):
The Gold Standard Diagnostics Antinuclear Antibody (ANA) Screen ELISA Test Kit is a qualitative assay for the detection of ANAs in human serum. The assay collectively detects in one well ANAs against double stranded DNA (dsDNA), SSA (Ro60 and Ro52), SSB (La), Sm, Sm/RNP, Scl-70, Jo-1, Ribosomal P, and Centromeric antibodies along with sera positive for immunofluorescent HEp-2 ANAs.
The assay is used as an aid in the diagnosis of Systemic Lupus Erythematosus, Mixed Connective Tissue Disease, Sjögren's Syndrome, Progressive Systemic Sclerosis, and Polymyositis/Dermatomyositis, and should be used in conjunction with other laboratory tests and clinical findings.
2. Indication(s) for use:
Same as Intended Use
3. Special conditions for use statement(s):
Prescription use only
4. Special instrument requirements:
Microwell plate reader capable of measuring OD at 450 nm and at 620 nm for dual wavelength readings.
I. Device Description:
The device, as described in the labeling, is a kit composed of the following reagents:
1. One microtiterplate consisting of 96 wells with coated antigen (lyophilized) from which single wells can be broken.
2. Sample Buffer (orange cap) 100 mL ready to use solution, with preservative and Tween 20.
3. Wash Buffer (blue cap), 100 mL 10x concentrate solution, with preservative and Tween 20. Add to 900 mL deionized water.
4. Negative Control, 2.0 mL, human serum with protein-stabilizer and preservative, ready to use.
5. Positive Control, 2.0 mL, human serum containing antibodies positive for ANA with
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protein-stabilizer and preservative, ready to use.
6. Cutoff Control, 2.0 mL, human serum containing antibodies positive for ANA with protein-stabilizer and preservative, ready to use.
7. Conjugate (red cap), 14 mL ready to use solution, peroxidase-labeled goat antihuman IgG conjugate with protein-stabilizer and preservative.
8. Substrate (3, 3', 5, 5'-TetraMethylBenzidine), 14 mL ready to use solution.
9. Stop Solution, 14 mL ready to use solution, contains acid.
## J. Substantial Equivalence Information:
1. Predicate device name(s) and 510(k) number(s):
Aeskulisa ANA Hep2, k040953
2. Comparison with predicate:
| Similarities | | |
| --- | --- | --- |
| Item | Device | Predicate |
| Intended Use | A qualitative assay for the detection of ANAs in human serum | Same |
| Measured analytes | Antibodies to double stranded DNA (dsDNA), SS-B (La), Sm, RNP/Sm, Scl-70, Jo-1 and centromeric antigens, and antibodies detected against Hep2 cells by immunofluorescence test | Same |
| Assay technology | Colorimetric enzyme immunoassay | Same |
| Immunoglobulin detected | Human IgG autoantibodies | Same |
| Captured antigens | Lysed Hep-2 extract
Purified native: Ro60, Sm
Recombinant: SSB, RNP, Scl-70, Jo-1, CENP-B | Same |
| Detection antibody | Horseradish peroxidase (HRP) labeled goat anti-human IgG | Same |
| Substrate | 3, 3', 5, 5'-tetramethylbenzidine (TMB) | Same |
| Controls | Positive, negative and cut-off controls | Same |
| Sample matrix | Serum | Same |
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| Differences | | |
| --- | --- | --- |
| Item | Device | Predicate |
| Measured analytes and captured antigens | Antibodies to SSA [Ro60 (purified native) and Ro52 (recombinant)]
Ribosomal P (recombinant) | Antibodies to SS-A (Ro) only
Ribosomal P not detected |
| Interpretation | Convert to units:
Negative <0.83 units;
Equivocal units 0.83-1.2 units
Positive >1.2 units | Convert to units:
Negative <1.0 units;
no equivocal zone
Positive >1.0 units |
K. Standard/Guidance Document Referenced (if applicable):
1. CLSI EP07-A2 Interference Testing in clinical chemistry
2. FDA Guidance for Industry and Staff. Recommendations for anti-nuclear antibody (ANA) test systems premarket submissions
L. Test Principle:
The Antinuclear Antibody (ANA) Screen ELISA Test kit is an enzyme linked immunosorbent assay where natural and recombinant Extractable Nuclear Antigens (ENAs) are collectively bound to microwells in polystyrene microtiter plates. Human serum containing ANA (IgG) antibodies is added to the wells and any ANAs bind to their cognate antigen(s). After incubation, the wells of the plate are washed to remove unbound serum components and non-ANA IgGs. A detection antibody conjugated with HRP is added to detect human IgG antibodies bound to antigens on the microtiter well. After an incubation period, the wells of the plate are washed to remove unbound enzyme-labeled anti-human IgG. Upon its addition to the washed wells the substrate TMB is converted by bound enzyme-conjugate antibody producing a blue end product. The Stop Solution is an acid that stops the reaction and turns the substrate yellow. The amount of color produced is proportional to the amount of antibody is present in the patient serum.
The antigens used in the Screen ELISA Test are a lysed HEp-2 cell extract with added purified antigens. The assay collectively detects in one well antibodies against double stranded DNA (dsDNA), SSA (Ro60 and Ro52), SSB (La), Sm, Sm/RNP, Scl-70, Jo-1, Ribosomal P, and Centromeric antibodies along with antibodies with reactivity against HEp-2 cells.
Optical density values read by the spectrophotometer are converted into 3 categories based upon a ratio of optical density of the samples (or controls) to the optical density of a cutoff control reagent present in the assay kit. Three result categories are determined by optical density ratio values as follows:
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| Optical density ratio | Interpretation |
| --- | --- |
| < 0.83 units | negative |
| 0.83 – 1.2 units | equivocal |
| > 1.2 units | positive |
# M. Performance Characteristics (if/when applicable):
# 1. Analytical performance:
# a. Precision/Reproducibility:
Assessment of the repeatability of the assay was performed on seven samples; three positive samples, one equivocal sample, and three negative samples. One positive sample was diluted with normal human serum to give a unit value $20\%$ above the positive ratio cutoff (1.36 U). The other two positive samples gave assay units approximately 2.56 and 5.60. One negative sample was diluted to $20\%$ below the negative cutoff ratio (approximately 0.70 units). The other two negative samples gave assay units approximately 0.3 and 0.15. Each sample was tested twice a day for ten days for a total of 20 replicates. All the observed results matched the expected results. The results, presented as ratio Units, are summarized in the following table:
# Repeatability:
| Sample | Mean (U) | Range (U) | Expected qualitative result | % Observed matching expected result |
| --- | --- | --- | --- | --- |
| 1 | 5.60 | 5.18–5.82 | Positive | 100% |
| 2 | 2.56 | 2.13–2.96 | Positive | 100% |
| 3 | 1.36 | 1.24–1.67 | Positive | 100% |
| 4 | 1.06 | 0.93–1.30 | Equivocal | 90% |
| 5 | 0.73 | 0.62–0.90 | Negative | 90% |
| 6 | 0.34 | 0.27–0.38 | Negative | 100% |
| 7 | 0.16 | 0.12–0.20 | Negative | 100% |
The reproducibility of the assay (between-lab imprecision) was done by testing three samples in duplicate for five days, twice a day, at three sites with two technicians per site for a total of 60 replicates. The mean results, reported as ratio Units, are summarized in the table below:
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Reproducibility:
| Sample | Mean (U) | Site | Range (U) | Expected qualitative result | % Observed result |
| --- | --- | --- | --- | --- | --- |
| 1 | 0.20 | 1 | 0.18-0.24 | Negative | 100% |
| 1 | | 2 | 0.18-0.26 | Negative | 100% |
| 1 | | 3 | 0.20-0.27 | Negative | 100% |
| 2 | 1.45 | 1 | 1.05-1.57 | Equivocal | 95% |
| 2 | | 2 | 1.06-1.45 | Equivocal | 95% |
| 2 | | 3 | 1.4-1.55 | Equivocal | 100% |
| 3 | 3.08 | 1 | 2.94-3.14 | Positive | 100% |
| 3 | | 2 | 2.51-3.18 | Positive | 100% |
| 3 | | 3 | 3.04-3.37 | Positive | 100% |
Lot to Lot:
Three samples were tested five times each on three different lots. The mean results, reported as ratio Units, are summarized in the table below:
| Sample | Mean (U) | Lot Number | Range (U) | Expected qualitative result | % Observed result matching expected result |
| --- | --- | --- | --- | --- | --- |
| 1 | 1.474 | 1 | 1.42-1.51 | Positive | 100% |
| 1 | | 2 | 1.48-1.60 | Positive | 100% |
| 1 | | 3 | 1.39-1.47 | Positive | 100% |
| 2 | 0.960 | 1 | 0.92-0.96 | Equivocal | 100% |
| 2 | | 2 | 0.92-1.01 | Equivocal | 100% |
| 2 | | 3 | 0.96-1.00 | Equivocal | 100% |
| 3 | 0.519 | 1 | 0.51-0.58 | Negative | 100% |
| 3 | | 2 | 0.50-0.52 | Negative | 100% |
| 3 | | 3 | 0.50-0.51 | Negative | 100% |
b. Linearity/assay reportable range:
Linearity: Not applicable.
Assay reportable range: Not applicable.
Hook effect:
To evaluate the hook effect on the assay, five sera with high antibody concentrations were diluted 1:100 to 1:12,000 and the units were calculated after completion of the testing. No hook effect was seen at the maximum measurement of 12 U.
c. Traceability, Stability, Expected values (controls, calibrators, or methods):
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## Traceability:
There is no recognized standard or reference material, so the assay is calibrated in arbitrary units. Each new lot of the cutoff control is traceable to an internal master control.
## Positive and Negative Control:
Positive control was prepared from a pool of eight pathological sera obtained from various plasma brokers determined to be positive for ANAs by HEp-2 immunofluorescence. Negative control was prepared by diluting the positive control pool 100-fold with sample diluent and protein stabilizer. The package insert states that the negative control must have an OD of <0.15; the positive control must have an OD of 0.6 to 1.6.
## Cut-off Control:
Cutoff controls are derived from a pool of eight pathological sera obtained from various plasma brokers determined to be positive by HEp-2 immunofluorescence. The cutoff control is prepared by diluting the serum pool with analyte-free serum to the appropriate concentration. The OD value of the cutoff control is compared with the master cutoff control. The unit ratio (OD cutoff control / OD master cutoff control) during the in-house QC procedure has to be 0.87 – 1.15. Each new lot of the cutoff controls, which are prepared by dilution of the pool stock, is compared with the master control and must meet the pre-specified acceptance criteria. Further, a set of 12 sera representing the antigen specificities is measured for each new lot of the controls and have to fall within their pre-specified ranges (which was obtained from several tests with different lots).
## Calibrators: Not applicable
Stability: The sponsor provided data demonstrating real-time stability of an opened kit for 6 months when stored at 2-8°C.
## d. Detection limit:
Not applicable
## e. Analytical specificity:
The effect of endogenous substances in serum specimens that could cause interference with the ANA ELISA Screen Test was evaluated. Five samples ranging from 1.4 to 2.5 U were spiked with the concentrations of hemoglobin, bilirubin, rheumatoid factor and triglycerides indicated below. The recovery in relation to the un-spiked sample without interferent was calculated. In addition, to assess the interference in the assay from heterophilic antibodies, two samples were spiked with three concentrations of HAMA type 1 antibody. The recommended concentrations from the guideline “Interference Testing in Clinical Chemistry” from the Clinical and Laboratory Standards Institute were used (CLSI EP7-A2). The tested substances as listed below did not affect the performance of the ELISA Screen Test.
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| Substance | Concentration | Mean Percent Inhibition |
| --- | --- | --- |
| Hemoglobin | 2 g/L | -2.1% |
| Bilirubin | 20 mg/dL | -3.0% |
| Rheumatoid Factor | 100 IU/mL | 8.8% |
| Triglycerides | 3000 mg/dL | -1.4% |
| Heterophile | 65 μg/mL | 5.4% |
| Heterophile | 32.5 μg/mL | 2.2% |
| Heterophile | 16.25 μg/mL | -0.6% |
Ten CDC and AMLI samples were tested in duplicate. The following table summarizes the specific reactivity of each sample and the result of each replicate.
| Sample | Specificity | Result 1 | Result 2 |
| --- | --- | --- | --- |
| CDC #1 | DNA | Positive | Positive |
| CDC #2 | SS-A/SS-B | Positive | Positive |
| CDC #3 | RNP, SS-A, SS-B | Positive | Positive |
| CDC #4 | RNP | Positive | Positive |
| CDC #5 | Sm | Positive | Positive |
| CDC #7 | SS-A/Ro | Positive | Positive |
| CDC #8 | CENP-B | Positive | Positive |
| CDC #9 | Scl-70 | Positive | Positive |
| CDC #10 | Jo-1 | Positive | Positive |
| CDC #12 | Ribosomal-P | Positive | Positive |
| AMLI #1 | Negative | Negative | Negative |
| AMLI #2 | SS-A/SS-B | Positive | Positive |
| AMLI #3 | SmRNP | Positive | Positive |
| AMLI #4 | SS-A/Ro | Positive | Positive |
| AMLI #5 | SS-A/SS-B | Positive | Positive |
| AMLI #6 | Scl-70 | Positive | Positive |
| AMLI #7 | Jo-1 | Positive | Positive |
| AMLI #8 | CENP-B | Positive | Positive |
| AMLI #9 | dsDNA | Positive | Positive |
| AMLI #10 | Negative | Negative | Negative |
f Assay cut-off
The cutoff was determined by testing 99 normal blood donors and three known negative samples. The mean value plus three standard deviations of the negative samples was established as the cutoff. To encourage a repeat testing of samples close to the cutoff, an equivocal range of $\pm 20\%$ of the cutoff was established.
2. Comparison studies:
a. Method comparison with predicate device:
A comparison of the performance of the test device and the predicate was performed at three different sites using a total of 848 samples. The sera used for this study were prospectively obtained from the reference labs that were from samples that were
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submitted for ANA serology testing. The results are summarized in the following table with the percent positive (PPA) and percent negative (NPA) agreements:
| | Predicate device | | |
| --- | --- | --- | --- |
| Gold Standard Diagnostic ANA ELISA | Positive | Negative | Total |
| Positive | 251 | 22 | 273 |
| Equivocal | 7 | 23 | 30 |
| Negative | 14 | 531 | 545 |
| Total | 272 | 576 | 848 |
Equivocals considered as Positive: $\mathrm{PPA} = 94.9\%$ (95% C.I. 91.5% - 97.2%), $\mathrm{NPA} = 92.2\%$ (95% C.I. 89.7% - 94.2%), $\mathrm{Overall} = 93.0\%$ (95% C.I. 91.1% - 95.7%),
Equivocals considered as Negative: $\mathrm{PPA} = 92.3\%$ (95% C.I. 88.4% - 95.2%) $\mathrm{NPA} = 96.2\%$ (95% C.I. 94.3% - 97.6%) $\mathrm{Overall} = 94.9\%$ (95% C.I. 93.2% - 96.3%)
To demonstrate the proposed test has comparable performance to the individual analyte assays, five samples known to be positive for each analyte (dsDNA, SS-A/Ro 60, SS-A/Ro 52, SS-B, Sm, Sm/RNP, Scl-70, Jo-1, Ribosomal P, Centromere, and HEp-2 IFA, total of 55 samples) were obtained and were tested on the proposed ANA Screening test, on an FDA-cleared test that measures each analyte individually, and by ANA HEp-2 IFA test. The percentage of the five samples from each analyte that were positive in the different tests is shown in the following table:
| Sample reactivity | GSD test | Individual analyte assay- % positive | | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | DNA | SSA (Ro60) | SSA (Ro52) | SSB (Ro52) | Sm | SM/RNP | SCL-70 | Jo-1 | Ribosomal P | Centromere | Hep-2 |
| dsDNA | 100% | 100% | 60% | 20% | 20% | 40% | 40% | 0% | 0% | 20% | 0% | 100% |
| SSA (Ro60) | 100% | 60% | 100% | 40% | 20% | 0% | 0% | 0% | 0% | 20% | 0% | 100% |
| SSA (Ro52) | 80% (1 equivocal) | 20% | 80% | 100% | 20% | 0% | 0% | 0% | 0% | 0% | 0% | 80% |
| SSB | 100% | 20% (1 equivocal) | 100% | 60% | 100% | 0% | 0% | 0% | 0% | 0% | 0% | 100% |
| Sm | 100% | 60% | 0% | 0% | 0% | 100% | 100% | 0% | 0% | 0% | 0% | 100% |
| Sm/RNP | 100% | 80% | 20% | 0% | 0% | 60% | 100% | 0% | 0% | 40% | 0% | 100% |
| SCL-70 | 100% | 20% | 0% | 0% | 0% | 0% | 0% | 100% | 0% | 0% | 0% | 100% |
| Jo-1 | 100% | 0% | 20% | 40% | 0% (1 equivocal) | 0% | 0% | 0% | 100% | 0% | 0% | 20% |
| Ribosomal | 100% | 80% | 40% | 0% | 0% | 0% | 40% | 0% | 0% | 100% | 0% | 80% |
| Centromere | 100% | 0% | 0% | 0% | 0% | 0% | 0% | 0% | 0% | 0% | 100% | 100% |
| Hep-2 | 100% | 40% | 40% | 0% | 20% | 20% | 40% | 20% | 0% | 40% | 0% | 100% |
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b. Matrix comparison: Not applicable.
# 3. Clinical studies:
# a. Clinical Sensitivity and Specificity:
A comparison of the assay results to clinical diagnosis was performed using 753 retrospective samples with associated clinical diagnosis and demographic information obtained from serum brokers. No NHS or proficiency samples were used in the Clinical Sensitivity and Specificity study.
| Clinical Diagnosis | Number Tested | Positive (%) | Equivocal (%) | Negative (%) |
| --- | --- | --- | --- | --- |
| Systemic Lupus Erythematosus (SLE) | 322 | 269 (82.9) | 11 (3.4) | 42 (13) |
| Systemic Sclerosis (SSc) | 40 | 29 (72.5) | 1 (2.5) | 10 (25) |
| Polymyositis (PM) | 12 | 4 (33.3) | 2 (16.7) | 6 (50) |
| Dermatomyositis (DM) | 15 | 4 (26.7) | 2 (13.3) | 9 (60) |
| PM or DM Overlap | 5 | 1 (20) | 1 (20) | 3 (60) |
| Myositis | 10 | 4 (40) | 1 (10) | 5 (50) |
| Mixed Connective Tissue Disease (MCTD) | 28 | 28 (100) | 0 | 0 |
| Undifferentiated CTD (UTCD) | 3 | 3 (100) | 0 | 0 |
| Sjögren's Syndrome (SjS) | 75 | 63 (84) | 4 (5.3) | 8 (10.7) |
| Total (CTD) | 510 | 405 (79.4) | 22 (4.3) | 83 (16.3) |
| Clinical Diagnosis | Number Tested | Positive (%) | Equivocal (%) | Negative (%) |
| --- | --- | --- | --- | --- |
| Rheumatoid Arthritis (RA) | 100 | 2 (2) | 0 | 98 (98) |
| Osteoarthritis | 20 | 5 (25) | 0 | 15 (75) |
| Primary Biliary Cirrhosis (PBC) | 8 | 1 (12.5) | 0 | 7 (87.5) |
| Autoimmune Hepatitis (AIH) | 2 | 0 | 0 | 2 (100) |
| Hashimoto's Thyroiditis | 17 | 0 | 0 | 17 (100) |
| Grave's Disease | 17 | 0 | 0 | 17 (100) |
| Ulcerative Colitis | 5 | 0 | 0 | 5 (100) |
| Celiac Disease | 5 | 0 | 0 | 5 (100) |
| Primary Anti-phospholipid Syndrome (PAPS) | 22 | 0 | 0 | 22 (100) |
| Granulomatosis with polyangitis (Wegener's) | 5 | 0 | 0 | 5 (100) |
| Total (non-CTD) | 201 | 8 (4) | 0 | 193 (96) |
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| Clinical Diagnosis | Number Tested | Positive (%) | Equivocal (%) | Negative (%) |
| --- | --- | --- | --- | --- |
| Herpes Simplex Virus (HSV) | 7 | 0 | 0 | 7 (100) |
| Epstein Barr Virus (EBV) | 7 | 0 | 0 | 7 (100) |
| Syphilis | 7 | 0 | 0 | 7 (100) |
| Varicella Zoster Virus (VZV) | 7 | 0 | 0 | 7 (100) |
| Mumps | 7 | 0 | 0 | 7 (100) |
| Rheumatoid Factor | 7 | 0 | 0 | 7 (100) |
| Total (other) | 42 | 0 | 0 | 42 (100) |
Equivocals considered as Positive:
Sensitivity = 83.5% (95% C.I. = 79.1% - 86.0%)
Specificity = 96.7% (95% C.I. = 93.6% - 98.6%)
Overall = 87.8% (95% C.I. = 85.2% - 90.0%)
Equivocals considered as Negative:
Sensitivity = 79.2% (95% C.I. = 75.4% - 82.7%)
Specificity = 96.7% (95% C.I. = 93.6% - 98.6%)
Overall = 84.9% (95% C.I. = 82.1% - 87.4%)
b. Other clinical supportive data (when a. is not applicable):
Not applicable
4. Clinical cut-off:
Not applicable.
1) Expected values/Reference range:
The expected value is negative; however, it is known that a certain percentage of NHS will be positive. In the sponsor's cutoff study, of the 99 samples from normal healthy donors, two were positive, for a prevalence of ANAs in the healthy population detected by this assay of 7%. The results are presented below.
| Total | |
| --- | --- |
| N | 99 |
| Positives | 2 |
| Equivocals | 7 |
| Negatives | 92 |
| Prevalence | 7.0 % |
| Ratio Mean (SD) (U) | 0.59 (0.2) |
| Ratio Range (U) | 0.1 – 1.58 |
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| By Gender | Number Tested | Mean Units | SD | 95^{th} Percentile |
| --- | --- | --- | --- | --- |
| Male | 51 | 0.62 | 0.24 | 1.09 |
| Female | 48 | 0.55 | 0.13 | 0.82 |
N. Proposed Labeling:
The labeling meets 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.
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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.