A retrospective study of 117 patients treated between August 2019 and January 2025. The dataset contains a logistic regression model and nomogram built by Chenlu Hou to predict minimal symptom expression after low-dose rituximab treatment in anti-acetylcholine receptor antibody-positive myasthenia gravis.
Use Cases
- Validate the predictive model's performance based on the reported AUC of 0.777.
- Stratify patients into high- and low-probability groups based on the Youden index threshold of 0.534.
- Investigate the relationship between achieving minimal symptom expression and the five screened variables: new-onset MG, baseline MG-ADL score, high CD19+/CD27+ B lymphocyte proportion, high-dose prednisone, and early immunotherapy initiation.
Strengths
- Model performance was internally validated using bootstrap resampling with 1000 replications.
- The dataset includes a specific patient cohort of 117 individuals with defined treatment and outcome criteria.
- The model's clinical utility was assessed using decision curve analysis.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
- The dataset is very small at 9.5 KB, indicating limited scope.
Provenance
- Source
- figshare
- Collection Method
- Retrospective review of patients who visited the research center and received RTX treatment.
- Time Range
- August 2019 to January 2025
- Freshness
- Last updated 2026-06-03 04:53:34; freshness should be verified.