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For In Vitro Diagnostic Use

Mouse Anti-Human T-cell, CD3/FITC, UCHT1 + Mouse Anti-Human B-cell, CD19/RPE, HD37 (DAKO Anti-CD3/FITC and Anti-CD19/RPE) has been developed for use in flow cytometry for the analysis of T-cells and B-cells. This reagent allows simultaneous detection and quantification of total T-cells and B-cells in peripheral blood of normal and pathological conditions such as immunodeficiency disorders. It is one component of the suggested monoclonal antibody (MAb) combinations for routine immunophenotyping of lymphocytes in peripheral blood using flow cytometry.

Purified mouse anti-human CD3, Clone UCHT1, conjugated with fluorescein isothiocyanate, isomer 1 (FITC) + purified mouse anti-human CD19, Clone HD37, conjugated with R-phycoerythrin, present in 0.05M Tris-HCl buffer, pH 7.2, 15 mM NaN3, 0.1M NaCl, stabilized with 1% carrier protein

Subpopulations of lymphocytes may be stained with fluorochrome-conjugated antibody and evaluated in peripheral blood specimens when contaminating red blood cells (RBC's) are lysed prior to flow cytometric analysis. A subpopulation of WBC's are selected for assessment based upon cell morphology.

Here's an analysis of the acceptance criteria and study details based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The acceptance criteria are "implied" because the document doesn't explicitly list them as "acceptance criteria." Instead, it describes the performance targets they aimed to achieve in comparison to the predicate device. The high correlation values (0.98 and 0.99) and linearity (0.999) strongly suggest these were the performance benchmarks for acceptance.

2. Sample Size and Data Provenance (Test Set)

• Sample Size: Not explicitly stated as a numerical count of patients or samples. The document mentions "peripheral blood samples obtained from apparently healthy adults as well as ill patients."
• Data Provenance: Not explicitly stated (e.g., country of origin). The data is described as "clinical evaluation" of "peripheral blood samples." Whether it's retrospective or prospective is also not specified, but the phrasing "were completed" suggests it was a completed study at the time of submission.

3. Number of Experts and Qualifications (Test Set Ground Truth)

Not applicable. This device is a diagnostic reagent for flow cytometry, which quantifies cell populations based on antibody binding. The "ground truth" for its performance is its correlation with a well-established predicate device and intrinsic laboratory performance characteristics like linearity and reproducibility, rather than expert interpretation of images or clinical outcomes.

4. Adjudication Method (Test Set)

Not applicable, for the same reasons as #3.

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

No, an MRMC comparative effectiveness study was not done. This type of study is relevant for devices involving human interpretation of diagnostic results (e.g., radiologists reading images) where the AI assists the human. This submission is for a laboratory reagent.

6. Standalone (Algorithm Only) Performance

Yes, the study primarily evaluates the standalone performance of the DAKO reagent. The "performance characteristics have been established by clinical evaluation" compared to the predicate device, and the linearity, reproducibility, and cross-reactivity tests are all measures of the reagent's inherent performance. There is no human-in-the-loop component being evaluated for this specific device.

7. Type of Ground Truth Used (Test Set)

• Predicate Device Comparison: The primary "ground truth" or reference standard for comparison was the results obtained from the Becton Dickinson Simultest CD3/CD19 predicate device.
• Internal Validation: Linearity was established using JM cells (for CD3/FITC) and Raji cells (for CD19/RPE), which are established cell lines. Reproducibility was assessed using "replicates (from peripheral blood)."

8. Sample Size for the Training Set

Not applicable. This device is a monoclonal antibody reagent, not a machine learning algorithm that requires a "training set" in the conventional sense. Its development involved well-established immunological and biochemical methods (e.g., UCHT1 and HD37 clones were identified at Leukocyte Typing Workshops).

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

Not applicable, as there's no "training set" in the context of a machine learning algorithm. The "ground truth" for the development of these specific antibody clones (UCHT1 for CD3 and HD37 for CD19) was established through extensive research and consensus from the Leukocyte Typing Workshops, where immunologists characterized and classified cell surface markers. These workshops established the specificity and utility of these antibody clones for identifying T-cells and B-cells, respectively.

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