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The STC Cocaine Metabolite Micro-Plate EIA is intended for use in the qualitative determination of cocaine and cocaine metabolites in oral fluid collected with the OraSure® Oral Specimen Collection Device. For In Vitro Diagnostic Use.

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This is a very old document (1998) and describes the clearance of an in vitro diagnostic device, specifically an EIA (enzyme immunoassay) for cocaine metabolites in oral fluid. The information provided is typical for a 510(k) clearance letter and an Indications for Use statement, but it does not contain the detailed study results, acceptance criteria, or most of the very specific information you are requesting about AI/algorithm performance.

Therefore, I cannot provide a table of acceptance criteria and reported device performance, nor details about sample sizes for test/training sets, experts, adjudication methods, MRMC studies, or standalone algorithm performance, as these concepts are largely relevant to more modern AI/ML device submissions and are not included in this type of 1998 clearance document.

However, I can extract the following relevant information from the provided text:

• Device Name: STC Cocaine Metabolite Micro-Plate EIA
• Intended Use: Qualitative determination of cocaine and cocaine metabolites in oral fluid collected with the OraSure® Oral Specimen Collection Device. For In Vitro Diagnostic Use.
• Regulatory Class: II
• Product Code: DIO

To answer your request based on the lack of this specific information, here's what I can deduce:

1. A table of acceptance criteria and the reported device performance:

   • N/A. This document is a 510(k) clearance letter and "Indications for Use" statement. It does not include the detailed performance study results or predefined acceptance criteria (e.g., sensitivity, specificity thresholds) that would have been part of the 510(k) submission itself. For an in vitro diagnostic device, the acceptance criteria would typically relate to analytical performance (e.g., detection limit, precision, accuracy/agreement with a reference method) and clinical performance (e.g., sensitivity, specificity against a confirmed drug use status). These metrics would have been compared to a legally marketed predicate device to establish substantial equivalence.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

   • N/A. This information is not present in the provided document. The sample size and data provenance for the clinical studies would have been included in the 510(k) submission. For IVD devices, clinical samples would be tested to evaluate performance.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

   • N/A. This information is not present in the provided document. For a drug metabolite test, the "ground truth" would typically come from confirmatory laboratory methods (e.g., GC/MS or LC/MS/MS) on the same or split samples, not from human experts interpreting images or signals in the same way a radiologist would.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   • N/A. This information is not present in the provided document. "Adjudication" often refers to resolving discrepancies between human readers, which is not directly applicable to the primary analytical performance evaluation of this type of in vitro diagnostic device.

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:

   • N/A. This device is an in vitro diagnostic immunoassay kit, not an AI/ML-based device that assists human readers. Therefore, an MRMC study and the concept of "human improvement with AI" are not relevant to this product.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • Yes, in spirit, but not in the AI/ML context. The STC Cocaine Metabolite Micro-Plate EIA is a test kit designed to provide a result (qualitative determination of cocaine metabolites) based on biochemical reactions, without a human "algorithm" or interpretation in the way AI systems operate. Its performance would be evaluated as a standalone product. However, this is not an "algorithm" in the modern AI sense.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

   • Likely confirmatory laboratory methods (e.g., GC/MS, LC/MS/MS). For drug metabolite detection, the gold standard for ground truth is typically a highly sensitive and specific mass spectrometry-based method performed on the same biological samples. This is superior to "expert consensus" in this context.

8. The sample size for the training set:

   • N/A. This concept of a "training set" is specific to machine learning algorithms. This device is a biochemical assay kit and does not involve an AI/ML algorithm that requires training data.

9. How the ground truth for the training set was established:

   • N/A. As above, the concept of a training set and its ground truth is not applicable to this type of in vitro diagnostic assay.

In summary, this document pertains to a traditional in vitro diagnostic device from 1998, and thus most of your detailed questions regarding AI/ML device study design and performance criteria are not applicable. The 510(k) clearance process for such devices focused on demonstrating substantial equivalence to a legally marketed predicate device through analytical and clinical performance studies, the details of which are not described in this high-level clearance letter.

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The STC Cocaine Metabolite Micro-Plate EIA is intended for use in the qualitative determination of cocaine and cocaine metabolites in oral fluid collected with the EpiScreen™ Oral Specimen Collection Device. For In Vitro Diagnostic Use.

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Below is an analysis of Acceptance Criteria and the study from the provided document.

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state quantitative acceptance criteria or a detailed performance table. However, it does indicate the device is intended for "qualitative determination of cocaine and cocaine metabolites in oral fluid." The FDA's letter states the device is "substantially equivalent" to predicate devices. This implies that its performance is considered acceptable based on comparison to existing, legally marketed devices.

To infer potential acceptance criteria and reported performance, we can assume that "substantial equivalence" in a qualitative test means the device demonstrated comparable accuracy (sensitivity and specificity) to a predicate device for detecting cocaine metabolites in oral fluid. Without the specific predicate device or the detailed 510(k) submission, we cannot provide exact numbers.

Inferred Table:

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

The provided documents (FDA 510(k) clearance letter and Indications for Use statement) do not contain information regarding the sample size used for the test set or the data provenance (e.g., country of origin, retrospective/prospective). This information would typically be detailed in the 510(k) submission itself, which is not included here.

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

The document does not provide information on the number of experts or their qualifications used to establish ground truth for the test set. For a qualitative diagnostic device detecting drug metabolites, the ground truth would likely be established through a confirmatory test method (e.g., GC/MS), not strictly by human expert consensus on interpretations of the initial test.

4. Adjudication Method for the Test Set:

Given the nature of a qualitative test for drug metabolites, an adjudication method like 2+1 or 3+1 typically used for image interpretation or subjective assessments is unlikely to be directly applicable. The ground truth would most probably be established by an objective, gold-standard laboratory method. The document does not specify any adjudication method used.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study (comparing human readers with and without AI assistance) is not applicable and was not performed/reported for this device. This device is an "in vitro diagnostic" (IVD) test, specifically a micro-plate EIA for qualitative determination. It's a laboratory test, not an AI-assisted diagnostic imaging or interpretation tool for human readers.

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

This device is an "in vitro diagnostic" (IVD) kit. Its performance, as an EIA (Enzyme Immunoassay), is inherently standalone in the sense that the assay itself produces a result (e.g., optical density reading) which is then interpreted against a cut-off to determine a qualitative positive or negative. There isn't an "algorithm only" component separate from the physical assay. The study would have focused on the performance of the entire assay system (reagents, plates, reader, interpretation) in detecting the target analyte.

The FDA's "substantial equivalence" determination implies that the standalone performance of the device was found to be comparable to predicate devices. However, the document does not detail the specific standalone performance study.

7. Type of Ground Truth Used:

While not explicitly stated in the provided text, for a device intended for "qualitative determination of cocaine and cocaine metabolites," the ground truth for performance studies would almost certainly be established by a confirmatory analytical method, such as Gas Chromatography-Mass Spectrometry (GC/MS) or Liquid Chromatography-Mass Spectrometry (LC/MS). These are considered gold-standard methods for drug detection and quantification in biological samples.

8. Sample Size for the Training Set:

The document does not provide information regarding the sample size used for the training set. For IVD devices, a "training set" in the context of machine learning (AI) is not typically applicable. If any "training" occurred, it would be related to optimization of reagents, cut-off values, or assay conditions during development, not in the sense of an AI model's training data. The primary performance evaluation would be done on independent test sets.

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

As mentioned in point 8, the concept of a "training set" with established ground truth in the AI context isn't directly applicable here. If referring to the process of developing the assay and establishing its optimal cut-off, the ground truth would again rely on a gold-standard confirmatory method (e.g., GC/MS or LC/MS) to calibrate the assay's response and set the appropriate thresholds for positive/negative results. The document does not detail this developmental process.

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