Nomogram for short-term outcome assessment in AChR subtype generalized myasthenia gravis

Author:

Zhao Rui,Wang Ying,Huan Xiao,Zhong Huahua,Zhou Zhirui,Xi Jianying,Da Yuwei,Lei Lin,Chang Ting,Ruan Zhe,Luo Lijun,Li Shengnan,Yang Huan,Li Yi,Luo SushanORCID,Zhao Chongbo

Abstract

Abstract Background An accurate prediction for prognosis can help in guiding the therapeutic options and optimizing the trial design for generalized myasthenia gravis (gMG). We aimed to develop and validate a predictive nomogram to assess the short-term outcome in patients with the anti-acetylcholine receptor (AChR) subtype gMG. Methods We retrospectively reviewed 165 patients with AChR subtype gMG who were immunotherapy naïve at the first visit from five tertiary centers in China. The short-term clinical outcome is defined as the achievement of minimal symptom expression (MSE) at 12 months. Of them, 120 gMG patients from Huashan Hospital were enrolled to form a derivation cohort (n = 96) and a temporal validation cohort (n = 24) for the nomogram. Then, this nomogram was externally validated using 45 immunotherapy naïve AChR subtype gMG from the other four hospitals. Multivariate logistic regression was used to screen independent factors and construct the nomogram. Results MSE was achieved in 70 (72.9%), 20 (83.3%), and 33 (73.3%) patients in the training, temporal validation, and external validation cohort, respectively. The duration ≤ 12 months (p = 0.021), ocular score ≤ 2 (p = 0.006), QMG score > 13 (p = 0.008), and gross motor score ≤ 9 (p = 0.006) were statistically associated with MSE in AChR subtype gMG. The nomogram has good performance in predicting MSE as the concordance indexes are 0.81 (95% CI, 0.72–0.90) in the development cohort, 0.944 (95% CI, 0.83–1.00) in the temporal validation cohort, and 0.773 (95% CI, 0.63–0.92) in the external validation cohort. Conclusion The nomogram achieved an optimal prediction of MSE in AChR subtype gMG patients using the baseline clinical characters.

Funder

National Natural Science Foundation of China

Shanghai Municipal Science and Technology Major Project

Publisher

Springer Science and Business Media LLC

Subject

General Biochemistry, Genetics and Molecular Biology,General Medicine

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