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Identifying antinuclear antibody positive individuals at risk for developing systemic autoimmune disease: development and validation of a real-time risk model.
Barnado, April; Moore, Ryan P; Domenico, Henry J; Green, Sarah; Camai, Alex; Suh, Ashley; Han, Bryan; Walker, Katherine; Anderson, Audrey; Caruth, Lannawill; Katta, Anish; McCoy, Allison B; Byrne, Daniel W.
Afiliação
  • Barnado A; Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States.
  • Moore RP; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States.
  • Domenico HJ; Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States.
  • Green S; Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, United States.
  • Camai A; Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States.
  • Suh A; Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States.
  • Han B; Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States.
  • Walker K; Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States.
  • Anderson A; Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States.
  • Caruth L; Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States.
  • Katta A; Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States.
  • McCoy AB; Division of Rheumatology & Immunology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States.
  • Byrne DW; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States.
Front Immunol ; 15: 1384229, 2024.
Article em En | MEDLINE | ID: mdl-38571954
ABSTRACT

Objective:

Positive antinuclear antibodies (ANAs) cause diagnostic dilemmas for clinicians. Currently, no tools exist to help clinicians interpret the significance of a positive ANA in individuals without diagnosed autoimmune diseases. We developed and validated a risk model to predict risk of developing autoimmune disease in positive ANA individuals.

Methods:

Using a de-identified electronic health record (EHR), we randomly chart reviewed 2,000 positive ANA individuals to determine if a systemic autoimmune disease was diagnosed by a rheumatologist. A priori, we considered demographics, billing codes for autoimmune disease-related symptoms, and laboratory values as variables for the risk model. We performed logistic regression and machine learning models using training and validation samples.

Results:

We assembled training (n = 1030) and validation (n = 449) sets. Positive ANA individuals who were younger, female, had a higher titer ANA, higher platelet count, disease-specific autoantibodies, and more billing codes related to symptoms of autoimmune diseases were all more likely to develop autoimmune diseases. The most important variables included having a disease-specific autoantibody, number of billing codes for autoimmune disease-related symptoms, and platelet count. In the logistic regression model, AUC was 0.83 (95% CI 0.79-0.86) in the training set and 0.75 (95% CI 0.68-0.81) in the validation set.

Conclusion:

We developed and validated a risk model that predicts risk for developing systemic autoimmune diseases and can be deployed easily within the EHR. The model can risk stratify positive ANA individuals to ensure high-risk individuals receive urgent rheumatology referrals while reassuring low-risk individuals and reducing unnecessary referrals.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Reumatologia / Doenças Autoimunes Limite: Female / Humans / Male Idioma: En Revista: Front Immunol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Reumatologia / Doenças Autoimunes Limite: Female / Humans / Male Idioma: En Revista: Front Immunol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Suíça