Predicting long-term trends in inflammatory neuropathy outcome measures using latent class modelling

Area of Science:

• Neurology
• Immunology
• Clinical Outcome Measurement

Background:

• Immunoglobulin (Ig) therapy is crucial for managing chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) and multifocal motor neuropathy with conduction block (MMNCB).
• Regular Ig infusions aim for symptom control, with disease activity monitored via clinical outcome measurements.
• Understanding variations in these measures during stable periods is key for refining treatment strategies.

Purpose of the Study:

• To examine outcome measure variation during clinically stable periods in Ig-treated CIDP and MMNCB patients.
• To explore the utility of serial outcome measurements in predicting long-term outcomes.
• To identify factors influencing longitudinal trends in Ig-dependent neuropathies.

Main Methods:

• Retrospective longitudinal analysis of 85 CIDP and 23 MMNCB patients (2009-2020).
• Comparison of grip strength, Rasch-built overall disability scales (RODS), and MRC sum scores (MRC-SS) changes against minimal clinically important differences (MCID).
• Latent class mixed modelling (LCMM) to identify longitudinal trends and influencing factors.

Main Results:

• Group-averaged outcome measures showed minimal change, but intra-individual variations frequently exceeded MCID.
• Subclinical trends towards improvement or deterioration were identified in both CIDP and MMNCB cohorts.
• Contiguous sub-MCID declines in multiple outcome measures best predicted 'deteriorator' status.

Conclusions:

• Intra-individual outcome measure variation is common in Ig-dependent neuropathies, often surpassing MCID.
• Serial outcome measurements, particularly contiguous sub-MCID declines across multiple measures, offer predictive value for long-term prognosis.
• These findings can inform therapeutic decision-making and long-term outcome prediction in treated neuropathies.