Vollständiger Abstract
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<h4>Background</h4>Efgartigimod has emerged as an effective treatment option for acetylcholine receptor antibody-positive generalized myasthenia gravis (AChR+ gMG). This study aimed to develop and validate a predictive nomogram to evaluate the achievement of Minimal Symptom Expression (MSE) in AChR+ gMG patients following efgartigimod treatment.<h4>Methods</h4>We retrospectively reviewed 119 patients with AChR+ gMG who received at least one cycle of efgartigimod and had ≥ 12 weeks of follow-up. Clinical response was defined as MSE, referring to an MG-ADL score of 0 or 1 within 4 weeks of treatment initiation and sustained for ≥ 4 consecutive weeks. Independent predictors of MSE were identified using multivariable logistic regression and incorporated into a nomogram. Model performance was assessed by discrimination (AUC-ROC) and calibration, with internal validation performed using bootstrap resampling.<h4>Results</h4>The MSE responder rate was 37.0%. New-onset MG (OR=2.691, p=0.031), thymoma-associated MG (TAMG) (OR=0.209, p=0.027), baseline QMG score (OR=0.888, p=0.007), and the reduction in IgG levels after one treatment cycle (ΔIgG) (OR=1.168, p=0.040) were independently associated with the clinical response. The nomogram demonstrated moderate discrimination, with a bootstrap-corrected AUC of 0.744 (95% CI: 0.732-0.771), indicating stable performance after internal validation.<h4>Discussion</h4>The nomogram indicates that new-onset MG and ΔIgG are associated with a higher probability of achieving MSE, while TAMG and a higher baseline QMG score are linked to poorer outcomes. These findings further support the potential value of early intervention and dynamic IgG monitoring in guiding individualized treatment strategies.<h4>Conclusion</h4>By integrating new-onset MG, TAMG, baseline QMG score, and ΔIgG, this nomogram provides an individualized prediction of MSE in AChR+ gMG patients treated with efgartigimod, offering a practical clinical tool to help tailor treatment strategies.
Abstract: PubMed · Datensatz
Bibliografischer Nachweis
Publikationsdaten
- Autor:innen
- Simona Balestrini, Sanjay M. Sisodiya
- Quelle
- Current Pharmaceutical Design
- Publikation
- 2018-01-01
- Band / Ausgabe
- Nicht angegeben
- Seiten
- Nicht angegeben
- ISSN / ISBN
- 1381-6128
- Zitationen
- 7 laut Crossref
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Zitierfähiger Nachweis
Simona Balestrini, Sanjay M. Sisodiya (2018). 10.2174/1381612823666170809115827. Current Pharmaceutical Design. https://doi.org/10.2174/011570159x499275260731080332