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ImmunoCAP Allergen o215, Component nGal-alpha-1,3-Gal (alpha-Gal) Thyroglobulin, bovine, is intended for in vitro diagnostic use, in human serum or EDTA plasma, as an aid in the diagnosis of IgE mediated mammalian (red) meat hypersensitivity, due to alpha-Gal sensitization, and to be used in conjunction with other clinical findings. This test is not to be the sole criterion for diagnosing allergy to alpha-Gal. It is a quantitative test to be used in clinical laboratories. ImmunoCAP Allergen 0215, alpha-Gal is to be used with the ImmunoCAP Specific IgE assay on the instrument Phadia™ 250.

ImmunoCAP Allergen o215, Component nGal-alpha-1,3-Gal (alpha-Gal) Thyroglobulin, bovine, is a component of, and is designed to be used with, the ImmunoCAP Specific IgE assay, previously cleared under K051218. The test has the same overall design as all other ImmunoCAP Allergen components and uses identical assay and system specific reagents, instruments and software.

This document describes the performance characteristics and acceptance criteria for the ImmunoCAP Allergen o215, Component nGal-alpha-1,3-Gal (alpha-Gal) Thyroglobulin, bovine test, which is intended to aid in the diagnosis of IgE mediated mammalian (red) meat hypersensitivity.

1. Table of Acceptance Criteria and Reported Device Performance

The provided document describes both analytical and clinical performance studies, but directly states acceptance criteria only for analytical performance implicitly through the successful completion of the studies. For clinical performance, it discusses the study design and patient numbers, from which performance can be inferred.

Analytical Performance Characteristics:
The document states that analytical performance characteristics were established by studies of:

• Precision
• Lot-to-Lot Reproducibility
• Linearity
• Limit of Quantitation
• Sample Matrix Equivalency
• Interference
• Inhibition
• Stability

While specific numerical acceptance criteria for each of these analytical characteristics are not explicitly listed in the provided text, the overall conclusion is that the device's analytical performance was verified and supports its substantial equivalence. The document concludes: "Analytical performance characteristics for the new ImmunoCAP Allergen Components were established by studies of Precision, Lot-to-Lot Reproducibility, Linearity, Limit of Quantitation, Sample Matrix equivalency, Interference, Inhibition and Stability." This implies that the device met the pre-defined acceptance criteria for these analytical aspects.

Clinical Performance Characteristics:
For clinical performance, a retrospective study was conducted. The document does not explicitly present a table of acceptance criteria (e.g., minimum sensitivity, specificity) against which the device's performance was measured for clinical use. Instead, it describes the study design, and the implied acceptance is that the device demonstrated sufficient performance to be considered an "aid in the diagnosis."

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

• Test Set Sample Size: The clinical performance was evaluated using samples from 200 subjects with a case history of mammalian meat hypersensitivity (cases) and 110 control subjects.
• Data Provenance: The study was a retrospective study. The country of origin of the data is not specified in the provided text.

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

The document does not specify the number of experts used to establish the ground truth for the test set, nor does it detail their specific qualifications (e.g., "radiologist with 10 years of experience"). It mentions that the 200 subjects had a "case history of mammalian meat hypersensitivity," implying that their status was established through clinical diagnosis, likely by medical professionals.

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1) used for establishing the ground truth for the test set.

5. Multi Reader Multi Case (MRMC) Comparative Effectiveness Study

No MRMC comparative effectiveness study was reported in which human readers' improvement with AI vs. without AI assistance was assessed. This device is an in-vitro diagnostic assay, not an AI-assisted imaging device, so such a study would not be applicable.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Performance

This device is an in-vitro diagnostic test kit that provides quantitative measurements of IgE antibodies. Its performance, as described, is inherently "standalone" in the sense that the test itself generates a result without direct human interpretation influencing the measurement, though human interpretation is required for the final diagnostic aid. The "performance characteristics" detailed refer to the analytical and clinical performance of the assay itself, which is analogous to a standalone performance evaluation in the context of an IVD.

7. Type of Ground Truth Used

The ground truth for the clinical study was based on a "case history of mammalian meat hypersensitivity" for the 200 subjects and "control subjects" for the 110 individuals. This suggests that the ground truth was established by clinical diagnosis and patient history, rather than a specific expert consensus on images, pathology, or outcomes data from a prospective study directly.

8. Sample Size for the Training Set

The document does not mention a separate "training set" or its sample size. This is typical for an IVD assay, where performance is established through validation studies rather than machine learning model training. The development process for such an assay would involve internal development and optimization, but not typically in the sense of a machine learning training set with a distinct ground truth establishment process as described for AI models.

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

Since no distinct "training set" is mentioned in the context of this device's validation, the method for establishing its ground truth is not applicable. The development of an IVD assay involves extensive R&D, but the concept of "ground truth for a training set" usually applies to machine learning algorithms.

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