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The assay is intended for use in detecting antibodies to Scl-70 antigen in a single human serum sample. The results of the assay are to be used as an aid in the diagnosis of autoimmune disorders.

The Is-anti-Scl-70 Test Kit System is an enzyme-linked immunosorbent assay (ELISA) for the detection and semi-quantitation of IgG to Scl-70 antigen in human serum.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Is-anti-Scl-70 Test System:

This document focuses on the performance characteristics of an in vitro diagnostic device (IVD), specifically an Enzyme-Linked Immunosorbent Assay (ELISA) for detecting antibodies to Scl-70 antigen. For IVDs, "acceptance criteria" are usually demonstrated through tests of sensitivity, specificity, accuracy (agreement), precision, linearity, and and cross-reactivity compared to a predicate device or established reference methods. The "study" described is the validation study performed to demonstrate these characteristics.

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state "acceptance criteria" as distinct numerical thresholds for approval. Instead, it presents performance characteristics and compares them to a predicate device. For IVDs, the reported performance is what demonstrates the device is "safe and effective for its intended use" as compared to the predicate.

Given the context of a 510(k) summary, the implicit acceptance criteria would be substantial equivalence to the predicate device. This means the new device performs at least as well as, or comparably to, the legally marketed predicate device.

Note: The precision for MAGO for "NEG CTRL" has an Inter-CV% of 29.4%, which might be considered higher than ideal for some IVD applications, but is presented without further commentary on its acceptability against specific criteria.

2. Sample Size Used for the Test Set and Data Provenance

• Test Set Sample Size:

  • Comparison Testing (Sensitivity, Specificity, Agreement): 162 sera (24 autoimmune patients + 138 normal blood donors). One equivocal sample was excluded from calculations, leading to calculations based on 162 or 163 samples depending on the specific calculation.
  • Linearity: The Calibrator, tested after serial two-fold dilutions. The number of individual samples is not specified, but it's a test of the assay's range performance.
  • Precision Testing: 6 different sera (2 negative, 4 positive), a calibrator, a positive control, and a negative control. Each was tested 10 times in one run and 10 times over three different days.
  • Cross-reactivity: 24 sera (positive for six different autoimmune specificities: SSA, SSB, Sm, RNP, Jo-1, Scl-70).
  • Expected Values (Clinical Samples): 50 clinically characterized sera + 100 normal donor sera.
  • Correlation (Manual vs. MAGO): 150 samples.

• Data Provenance:

  • The document implies the data was collected for this study, making it prospective in nature, as new testing was performed against the predicate.
  • Country of Origin: For "Expected Values," 100 normal donor sera were collected in South Florida, USA. No other specific country of origin is mentioned for the other sample sets, but the applicant (Diamedix Corporation) is based in Miami, Florida, suggesting the studies were likely conducted in the USA.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

• The document does not specify the number of experts used, nor their specific qualifications (e.g., radiologist with X years of experience).
• For a serological test like this, the "ground truth" for patient samples (autoimmune vs. normal) would typically be established based on clinical diagnosis by physicians following standard diagnostic criteria, often supported by various laboratory tests, including the predicate device or a "gold standard" method. The document mentions "clinically characterized sera" for expected values and "autoimmune patients" for comparison testing, implying such clinical determination.

4. Adjudication Method for the Test Set

• The document does not describe an explicit adjudication method (e.g., 2+1, 3+1).
• For the comparison testing, if the predicate device serves as the primary comparator, any discrepancies might have been resolved by a "third method" as mentioned: "Three sera negative by Is-anti-Scl-70 (manual) and positive by the comparative method were negative when tested by a third method." This implies a form of discrepancy testing/resolution rather than a formal expert adjudication of images/readings.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done, If So, What Was the Effect Size of How Much Human Readers Improve with AI vs Without AI Assistance

• No, this application describes the validation of an in vitro diagnostic (IVD) immunoassay, not an AI-assisted diagnostic imaging device or a device involving human readers interpreting outputs for improved performance. Therefore, an MRMC study and a human-in-the-loop effect size are not applicable to this device type.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Yes, this is a standalone IVD device. The test system (Is-anti-Scl-70 Test Kit) generates qualitative (positive/negative) and semi-quantitative (EU/ml) results.
• The "MAGO" system mentioned in the results appears to be an automated analyzer for processing the immunoassay, but it is still part of the standalone test system and does not involve human interpretation of complex data (like images) that would typically benefit from "human-in-the-loop" AI. The comparison between "Manual" and "MAGO" results demonstrates the performance of the assay itself, with the MAGO representing an automated reading of the assay's output.

7. The Type of Ground Truth Used

• Clinical Diagnosis / Reference Method:
  • For the comparative study (sensitivity, specificity, agreement), the predicate device (Helix Diagnostics Enzyme Immunoassay Anti-Scl-70 Antibody Test Kit) served as the primary reference for defining positive and negative samples for establishing relative performance.
  • For discordant results, a "third method" was used for resolution, acting as a secondary reference or adjudicator.
  • For "Expected Values," samples were categorized as "normal donor sera" and "clinically characterized sera," implying their status was determined by clinical evaluation and/or established diagnostic criteria, not solely by the test results themselves.
  • For "Cross-reactivity," samples were "positive for the six autoimmune specificities," indicating their status was established by prior diagnostic testing/clinical diagnosis.

8. The Sample Size for the Training Set

• The document does not describe a separate "training set" in the context of machine learning or AI. This is a traditional IVD assay.
• For an IVD like this, assay development and initial characterization (e.g., reagent optimization, cutoff determination) would occur using various panels of known positive and negative samples, but these are part of assay development rather than a formally designated "training set" for an algorithm in the AI sense. The samples used for linearity, precision, and cross-reactivity could be seen as part of the overall characterization of the assay's behavior.

9. How the Ground Truth for the Training Set Was Established

• As there is no explicitly defined "training set" in the context of an AI/ML algorithm, this question is not applicable in the same way.
• However, for the development of the assay itself and the establishment of its cut-offs, the "ground truth" for samples used in that phase would similarly be established through clinical diagnosis, expert clinical consensus, and/or comparison to established reference methods or predicate devices to define positive and negative cases of Scl-70 antibodies.

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