BIOMARKER-INTEGRATED DIAGNOSTIC ALGORITHM TO REDUCE MISCLASSIFICATION IN PEDIATRIC DEMYELINATING DISORDERS

Background: Pediatric acquired demyelinating disorders of the central nervous system, including multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), and myelin oligodendrocyte glycoprotein–associated disease (MOGAD), represent a heterogeneous group of immune-mediated conditions with overlapping clinical and radiological features. Accurate differentiation among these entities is critical due to differences in immunopathogenesis, prognosis, and therapeutic strategies. In regions with variable access to advanced serological testing, diagnostic misclassification remains a significant concern. Objective: To develop a structured, biomarker-integrated diagnostic framework for pediatric demyelinating disorders adapted to Central Asian healthcare settings. Methods: This study employed a conceptual analysis grounded in international diagnostic criteria (IPMSSG, McDonald, and NMOSD) and contemporary neuroimmunology literature. A scenario-based modeling approach was used to identify high-risk clinical phenotypes associated with diagnostic uncertainty and to construct a stepwise algorithm incorporating anti–aquaporin-4 (AQP4-IgG) and anti–myelin oligodendrocyte glycoprotein (MOG-IgG) antibody testing. Results: The proposed diagnostic algorithm prioritizes early recognition of clinical “red flags,” including opticospinal phenotypes and longitudinally extensive spinal cord lesions, followed by stepwise serological evaluation before definitive application of MS diagnostic criteria. This framework has the potential to reduce diagnostic misclassification and support phenotype-specific therapeutic decision-making in resource-limited environments. Conclusion: A biomarker-integrated diagnostic approach may enhance diagnostic accuracy and treatment safety in pediatric demyelinating disorders in Central Asia. Prospective validation studies are warranted to evaluate the real-world impact of this framework on clinical outcomes.

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Publication Details

Journal
Central Asian Journal of Medical Hypotheses and Ethics
Published
2026-03-31
DOI
https://doi.org/10.47316/cajmhe.2026.7.1.10
Primary Topic
Multiple Sclerosis Research Studies
Type
article
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article

BIOMARKER-INTEGRATED DIAGNOSTIC ALGORITHM TO REDUCE MISCLASSIFICATION IN PEDIATRIC DEMYELINATING DISORDERS

Zhanar Sabyrdilda, Aliya Baidauletova, Aigerim Galym, Saya Zhorabek et al.
Central Asian Journal of Medical Hypotheses and Ethics
Multiple Sclerosis Research Studies
article

BIOMARKER-INTEGRATED DIAGNOSTIC ALGORITHM TO REDUCE MISCLASSIFICATION IN PEDIATRIC DEMYELINATING DISORDERS

Zhanar Sabyrdilda, Aliya Baidauletova, Aigerim Galym, Saya Zhorabek, Akylbek Bakytzhan, Zarina Ravil
article en

Abstract

Background: Pediatric acquired demyelinating disorders of the central nervous system, including multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), and myelin oligodendrocyte glycoprotein–associated disease (MOGAD), represent a heterogeneous group of immune-mediated conditions with overlapping clinical and radiological features. Accurate differentiation among these entities is critical due to differences in immunopathogenesis, prognosis, and therapeutic strategies. In regions with variable access to advanced serological testing, diagnostic misclassification remains a significant concern. Objective: To develop a structured, biomarker-integrated diagnostic framework for pediatric demyelinating disorders adapted to Central Asian healthcare settings. Methods: This study employed a conceptual analysis grounded in international diagnostic criteria (IPMSSG, McDonald, and NMOSD) and contemporary neuroimmunology literature. A scenario-based modeling approach was used to identify high-risk clinical phenotypes associated with diagnostic uncertainty and to construct a stepwise algorithm incorporating anti–aquaporin-4 (AQP4-IgG) and anti–myelin oligodendrocyte glycoprotein (MOG-IgG) antibody testing. Results: The proposed diagnostic algorithm prioritizes early recognition of clinical “red flags,” including opticospinal phenotypes and longitudinally extensive spinal cord lesions, followed by stepwise serological evaluation before definitive application of MS diagnostic criteria. This framework has the potential to reduce diagnostic misclassification and support phenotype-specific therapeutic decision-making in resource-limited environments. Conclusion: A biomarker-integrated diagnostic approach may enhance diagnostic accuracy and treatment safety in pediatric demyelinating disorders in Central Asia. Prospective validation studies are warranted to evaluate the real-world impact of this framework on clinical outcomes.

Central Asian Journal of Medical Hypotheses and EthicsVol. 7(1)
Al-Farabi Kazakh National University (KZ), Kazakh National Medical University (KZ)
Openalex Percentile: Top 31%
Multiple Sclerosis Research Studies
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