Background: This study aims to establish and validate a predictive nomogram for the short-term clinical outcomes of myasthenia gravis (MG) patients treated with low-dose rituximab.
Methods: We retrospectively reviewed 108 patients who received rituximab of 600 mg every 6 months in Huashan Hospital and Tangdu Hospital. Of them, 76 patients from Huashan Hospital were included in the derivation cohort to develop the predictive nomogram, which was externally validated using 32 patients from Tangdu Hospital. The clinical response is defined as a ≥ 3 points decrease in QMG score within 6 months. Both clinical and genetic characteristics were included to screen predictors via multivariate logistic regression. Discrimination and calibration were measured by the area under the receiver operating characteristic curve (AUC-ROC) and Hosmer-Lemeshow test, respectively.
Results: Disease duration (OR = 0.987, p = 0.032), positive anti-muscle-specific tyrosine kinase antibodies (OR = 19.8, p = 0.007), and genotypes in FCGR2A rs1801274 (AG: OR = 0.131, p = 0.024;GG:OR = 0.037, p = 0.010) were independently associated with clinical response of post-rituximab patients. The nomogram identified MG patients with clinical response with an AUC-ROC (95% CI) of 0.875 (0.798-0.952) in the derivation cohort and 0.741(0.501-0.982) in the validation cohort. Hosmer-Lemeshow test showed a good calibration (derivation: Chi-square = 3.181, p = 0.923; validation: Chi-square = 8.098, p = 0.424).
Conclusions: The nomogram achieved an optimal prediction of short-term outcomes in patients treated with low-dose rituximab.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11090079 | PMC |
http://dx.doi.org/10.1111/cns.14761 | DOI Listing |
Abdom Radiol (NY)
January 2025
Department of Hepato-Biliary-Pancreatic Surgery, Huadong Hospital affiliated to Fudan University, Shanghai, China.
Background: The prognostic prediction of pancreatic ductal adenocarcinoma (PDAC) remains challenging. This study aimed to develop a radiomics model to predict Ki-67 expression status in PDAC patients using radiomics features from dual-phase enhanced CT, and integrated clinical characteristics to create a radiomics-clinical nomogram for prognostic prediction.
Methods: In this retrospective study, data were collected from 124 PDAC patients treated surgically at a single center, from January 2017 to March 2023.
Objectives: Combining Computed Tomography (CT) intuitive anatomical features with Three-Dimensional (3D) CT multimodal radiomic imaging features to construct a model for assessing the aggressiveness of pancreatic neuroendocrine tumors (pNETs) prior to surgery.
Methods: This study involved 242 patients, randomly assigned to training (170) and validation (72) cohorts. Preoperative CT and 3D CT radiomic features were used to develop a model predicting pNETs aggressiveness.
Aim: Many combinations of inflammation-based markers have been reported their prognostic ability. The prognostic value of albumin-to-gama-glutamyltransferase ratio (AGR), an inflammation-related index, has been identified for several cancers. However, the predictive value of AGR for high-grade glioma patients remains unclear.
View Article and Find Full Text PDFFront Pediatr
January 2025
Department of Neonatology, The First Affiliated Hospital of Zheng Zhou University, Zhengzhou, China.
Objective: To explore the risk factors for the reactivate of retinopathy of prematurity (ROP) after intravitreal injection of anti-vascular endothelial growth factor (VEGF) and to construct a nomogram model to predict the risk of ROP reactivate.
Methods: A retrospective analysis was conducted on 185 ROP children who underwent anti-VEGF treatment at the First Affiliated Hospital of Zhengzhou University from January 2017 to October 2023. They were randomly divided into a training set (129 cases) and a validation set (56 cases) at a ratio of 7:3.
Front Surg
January 2025
Department of Cardio-Thoracic Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Objective: This study aimed to explore the risk factors of hypokalemia after radical resection of esophageal cancer (EC) and establish a nomogram risk prediction model to evaluate hypokalemia risk after esophagectomy. Thus, this study provides a reference for the clinical development of intervention measures.
Methods: Clinical data of EC patients who underwent radical surgery from January 2020 to November 2022 in the First Affiliated Hospital of Guangxi Medical University were retrospectively collected.
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