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The EarliPoint System device is indicated as a tool to aid qualified clinicians in the diagnosis and assessment of Autism Spectrum Disorder (ASD) in children ages 16 months through 30 months, who are at risk based on concerns identified by a parent, caregiver, or healthcare provider.

The EarliPoint system uses an eye tracker to capture the patient's looking behavior while viewing a series of videos. The system then remotely analyzes the looking behavior data using software and outputs a diagnosis of the patient's ASD status and associated developmental delay indicies.
The EarliPoint System device consists of the following:
• Eye-tracking module and a separate Operator Module that can control the Eye-tracking module remotely. The patient sits on a chair and the Eye-tracking module is adjusted by the operator such that the patient's eyes are within the specification of the eye tracking window.
• Eye-tracking module captures the patient visual response to social information provided in the form of a series of age-appropriate videos.
• Operator's module is used to initiate and monitors the session remotely
• WebPortal securely stores all patient information, analyzes the eye tracking data, and outputs the results. Users can retrieve the results directly from the web-portal.
• Artificial intelligence software analyzes the eye-tracking data and provides a diagnosis for ASD. In addition, it also outputs 3 developmental delay indices (called EarliPoint Severity Indices) that proxy the ADOS-2 and Mullen validated ASD instruments Social Disability Index correlates and proxies ADOS-2 Verbal Ability Index correlates and proxies the age equivalent Mullen Verbal Ability score Non-verbal Ability Index correlates and proxies the age equivalent non-verbal Mullen Ability score

The EarliPoint System device's acceptance criteria and the study proving its performance are detailed below. It's important to note that the provided text is an FDA 510(k) clearance letter and summary, which primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting a full clinical study report. Therefore, some information, particularly granular details about study design, expert qualifications, or the exact training process, might not be explicitly stated to the level one would find in a peer-reviewed publication.

Acceptance Criteria and Reported Device Performance

The core acceptance criteria for the EarliPoint System, as demonstrated in the pivotal study, revolve around its ability to accurately diagnose Autism Spectrum Disorder (ASD) in comparison to expert clinical diagnosis. The key metrics are Sensitivity and Specificity.

Table of Acceptance Criteria and Reported Device Performance

Note: The document does not explicitly state pre-defined acceptance thresholds for sensitivity and specificity. The reported performance suggests the levels that were considered acceptable for clearance.

Study Details

2. Sample Size and Data Provenance

• Test Set Sample Size: 475 evaluable patients. 25 patients had missing data for either the device or the control diagnosis, making the initial enrollment 500 patients.
• Data Provenance:
  • Country of Origin: United States (six sites).
  • Retrospective or Prospective: Prospective.

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: Not explicitly stated how many individual experts were used across the six sites, but the ground truth was established by "expert clinicians" as the "current best practice for diagnosis of ASD."
• Qualifications of Experts: Not explicitly detailed, but they are referred to as "expert clinicians" in "specialized developmental disabilities centers," implying specialized training and experience in diagnosing ASD.

4. Adjudication Method for the Test Set

• The document does not explicitly describe an adjudication method for the expert clinical diagnosis (ground truth). It refers to it as the "current best practice," suggesting that the consensus or standard diagnostic process by qualified clinicians was deemed sufficient as the reference standard.

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

• Was an MRMC study done? No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly mentioned or performed in the context of human readers improving with AI vs. without AI assistance. The study described is a direct comparison of the EarliPoint system's diagnosis (algorithm only) against expert clinical diagnosis, not an AI-assisted human reader study.

6. Standalone (Algorithm Only) Performance

• Was a standalone performance study done? Yes, the presented sensitivity and specificity values are for the EarliPoint System's diagnosis alone (algorithm only), without human-in-the-loop assistance for interpretation of the device's output itself for the primary outcome. The system produces a diagnosis for ASD.

7. Type of Ground Truth Used

• Type of Ground Truth: "Expert clinician diagnosis (current best practice for diagnosis of ASD)." This is a form of expert consensus or clinical standard of care, rather than pathology or long-term outcomes data.

8. Sample Size for the Training Set

• The document does not provide the sample size for the training set. The clinical study details refer to a "pivotal study" used for evaluating safety and effectiveness, which serves as the test set for the device, rather than data used for initial model training.

9. How Ground Truth for the Training Set was Established

• The document does not provide details on how the ground truth for the training set was established. Since the pivotal study's data is described as the test set (evaluable N=475), any training data and its associated ground truth establishment would have occurred prior to this specific study and are not disclosed in this regulatory submission summary.

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