Artificial Intelligence Based Models for Primary Sjögren's Syndrome Diagnosis

NCT ID: NCT06982482

Last Updated: 2025-05-21

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

27432 participants

Study Classification

OBSERVATIONAL

Study Start Date

2013-01-01

Study Completion Date

2025-01-01

Brief Summary

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The goal of this observational study is to develop and validate artificial intelligence (AI)-driven models for improving the diagnosis of Primary Sjögren's Syndrome (PSS) using routine laboratory test data. The main question it aims to answer is:

Can AI-based algorithms accurately diagnose Primary Sjögren's Syndrome by analyzing laboratory test results, and do they outperform traditional diagnostic criteria in Chinese populations?

Researchers will retrospectively analyze anonymized clinical records and laboratory data (e.g., autoantibody levels, inflammatory markers) from patients with suspected or confirmed PSS across multiple medical centers in China. No new interventions will be administered, as the study utilizes existing historical data to train and validate the AI models. The performance of AI algorithms will be compared with current diagnostic standards (e.g., ACR/EULAR criteria) in terms of sensitivity, specificity, and clinical utility.

Detailed Description

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Conditions

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Primary Sjögren's Syndrome (pSS)

Study Design

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Observational Model Type

CASE_CONTROL

Study Time Perspective

RETROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

* Patients with clinician-diagnosed primary Sjögren's syndrome (pSS) meeting the 2016 ACR/EULAR or 2002 ACEG classification criteria (objective oral/ocular dryness, positive anti-SSA/Ro antibodies, or focal lymphocytic sialadenitis on biopsy).
* Control groups: Individuals with non-pSS autoimmune diseases (e.g., rheumatoid arthritis, systemic lupus erythematosus) or non-autoimmune conditions (e.g., dry eye/sicca symptoms without systemic autoimmunity).

Exclusion Criteria

* Pregnancy, breastfeeding, with a clear diagnosis of other autoimmune diseases, severe infection and malignant tumors.
* Not newly diagnosed in any of the hospitals.
* Without any available laboratory tests.
Minimum Eligible Age

18 Years

Maximum Eligible Age

65 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Xinran Yuan, MD

Role: STUDY_CHAIR

Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University

Locations

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Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University

Nanjing, Jiangsu, China

Site Status

Countries

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China

Other Identifiers

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B2022-529-04

Identifier Type: -

Identifier Source: org_study_id

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