A nomogram to predict the risk of lupus enteritis in systemic lupus erythematosus patients with gastroinctestinal involvement

• Main Authors: Zhihui Liu, Min Guo, Yurui Cai, Yi Zhao, Fanxin Zeng, Yi Liu
• Format: Article
• Language: English
• Published: Elsevier 2021-06-01
• Series: EClinicalMedicine
• Online Access: http://www.sciencedirect.com/science/article/pii/S2589537021001802

Background: Lupus enteritis (LE), a main cause of acute abdominal pain in systemic lupus erythematosus (SLE) patients, is a serious and potentially fatal complication. This study aimed to identify clinical serological indicators to establish a nomogram to assess LE in SLE patients with gastrointestinal manifestations. Methods: The clinical and laboratory data of SLE patients with gastrointestinal manifestations that were hospitalized in the West China Hospital from January 2010 to January 2020 were retrospectively analyzed. The least absolute shrinkage and selection operator logistic regression model was used to select potentially relevant features. Subsequently, a nomogram was developed using multivariable logistic analysis. The performance of the nomogram was evaluated using a receiver operating characteristic curve, a calibration curve, and decision curve analysis (DCA). Findings: We included a total of 8,505 SLE patients, of which 251 had experienced gastrointestinal manifestations. The patients were randomly divided into training (n = 176) and validation (n = 75) groups. The LRA (LE Risk Assessment) model consisted of 11 significantly associated variables, which included complement 4, antineutrophil cytoplasmic antibody, albumin, anion gap, age, d-dimer, platelet, serum chlorine, anti-Sjögren's-syndrome-related antigen A, anti-ribosomal P protein, and anti-ribonucleoprotein. In the training and validation cohorts, the areas under the curve were 0.919 (95% confidence interval [CI]: 0.876–0.962) and 0.870 (95% CI: 0.775–0.964), respectively. The nomogram demonstrated excellent performance in the calibration curve and DCA. Interpretation: The LRA model exhibits good predictive ability in assessing LE risk in SLE patients with gastrointestinal manifestations.