Yufang Yang, Tao Liang, Mingming Zhao, Hongxia Yang, Zhilan Zhao, Lu Yu, Linlin Yan, Siyuan Li, Peng Zhang, Guoyan Qi, Jian Yin, Zucai Xu, Zhong Luo
Background: Efgartigimod, a neonatal Fc receptor (FcRn) blocker, is approved for generalized Myasthenia Gravis (gMG), but predictors of early response are unclear. Using minimal symptom expression (MSE) as the therapeutic target, we developed and externally validated a clinical model to predict early MSE response after starting efgartigimod. This efgartigimod-tailored model estimates the baseline probability of achieving early MSE and may assist in individualized treatment selection at therapy initiation.
Methods: We retrospectively analyzed 118 adults with gMG treated at five tertiary centers in China (efgartigimod 10 mg/kg IV weekly ×4). MSE was defined as Myasthenia Gravis-Activities of Daily Living (MG-ADL) ≤ 1 sustained ≥ 4 weeks; early MSE response was achievement within 4 weeks of initiation. Patients were split into a derivation cohort (n = 64; three centers) and an external validation cohort (n = 54; two centers). Candidate predictors included demographics, baseline severity, and laboratory indices. Variables associated with early MSE in univariable analyses entered multivariable logistic regression to construct a nomogram. Discrimination (AUC-ROC), calibration (curves and Spiegelhalter Z-test), and clinical utility (decision curve analysis, DCA) were assessed, with bootstrap internal validation.
Results: Early MSE response occurred in 26/64 derivation and 22/54 validation patients. Lower bulbar MG-ADL (OR 0.633, p = 0.040), higher FVC% (OR 1.042, p = 0.048), and lower IgG (OR 0.795, p = 0.036) independently predicted early MSE response. The nomogram showed strong discrimination-derivation AUC 0.869 (95% CI 0.797-0.941), bootstrap AUC 0.880 (0.806-0.954), and external AUC 0.839 (0.760-0.919)-and good calibration (Spiegelhalter Z: 1.03, p = 0.303; 0.94, p = 0.347; 1.17, p = 0.242). DCA indicated net benefit across thresholds 0.05-0.82, with validation curves mirroring derivation.
Conclusions: A three-factor nomogram (bulbar MG-ADL, FVC%, and serum IgG) provides an efgartigimod-specific baseline estimate of early sustained-MSE response probability, which may help neurologists select appropriate candidates, counsel expected benefit, and tailor follow-up intensity or alternative escalation strategies.
Trail registration: Chinese Clinical Trial Registry (ChiCTR2500101971).
背景:Efgartigimod是一种新生儿Fc受体(FcRn)阻滞剂,被批准用于全身性重症肌无力(gMG),但早期反应的预测因素尚不清楚。以最小症状表达(MSE)为治疗靶点,我们建立了一个临床模型并进行了外部验证,以预测efgartigimod开始后MSE的早期反应。这个为efgartigimod量身定制的模型估计了实现早期MSE的基线概率,并可能有助于在治疗开始时进行个体化治疗选择。方法:我们回顾性分析了118名在中国5个三级医疗中心接受治疗的成人gMG患者(efgartigimod 10mg /kg IV weekly ×4)。MSE定义为重症肌无力-日常生活活动(MG-ADL)≤1,持续≥4周;早期的MSE反应是在开始的4周内实现的。患者被分为衍生队列(n = 64,三个中心)和外部验证队列(n = 54,两个中心)。候选预测因子包括人口统计学、基线严重程度和实验室指标。在单变量分析中,与早期MSE相关的变量进入多变量逻辑回归以构建nomogram。鉴别(AUC-ROC)、校准(曲线和Spiegelhalter z检验)和临床效用(决策曲线分析,DCA)进行评估,采用bootstrap内部验证。结果:早期MSE反应发生在26/64的衍生患者和22/54的验证患者中。较低的球MG-ADL (OR 0.633, p = 0.040)、较高的FVC% (OR 1.042, p = 0.048)和较低的IgG (OR 0.795, p = 0.036)独立预测早期MSE反应。nomogram显示出较强的判别性(导数AUC 0.869 (95% CI 0.797-0.941), bootstrap AUC 0.880(0.806-0.954),外部AUC 0.839(0.76 -0.919))和良好的校准(Spiegelhalter Z: 1.03, p = 0.303; 0.94, p = 0.347; 1.17, p = 0.242)。DCA表明净效益跨越阈值0.05-0.82,验证曲线反映了推导。结论:三因素nomogram(球MG-ADL, FVC%和血清IgG)提供了一个针对艾格替吉莫的早期持续mse反应概率的基线估计,这可能有助于神经科医生选择合适的候选人,咨询预期收益,并定制随访强度或替代升级策略。试验注册:中国临床试验注册中心(ChiCTR2500101971)。
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