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Development and validation of a clinical radiomics nomogram to predict secondary loss of response to infliximab in Crohn's disease patients.
Zhu, Chao; Wang, Xingwei; Wang, Shihui; Hu, Jing; Gao, Yankun; Li, Cuiping; Li, Jianying; Wu, Xingwang.
Afiliación
  • Zhu C; Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, PR China.
  • Wang X; Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, PR China.
  • Wang S; Department of Radiology, The First Affiliated Hospital of Wannan Medical College, Wuhu, 241001, PR China.
  • Hu J; Department of Gastroenterology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, PR China.
  • Gao Y; Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, PR China.
  • Li C; Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, PR China.
  • Li J; CT Research Center, GE Healthcare China, Shanghai, 210000, PR China.
  • Wu X; Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, PR China.
Heliyon ; 9(4): e14594, 2023 Apr.
Article en En | MEDLINE | ID: mdl-37151630
ABSTRACT

Background:

Infliximab (IFX) is the first-line treatment for Crohn's disease (CD). However, the secondary loss of response (LOR) is common in IFX therapy. Therefore, non-invasive assessment of LOR in CD patients is the goal pursued by clinicians.

Methods:

A multicenter study involving 181 CD patients was conducted, with patients being split into a training cohort (n = 102), testing cohort (n = 45), and validation cohort (n = 34). The study evaluated various clinical factors to establish a clinical model, and a radiomics signature was constructed based on reproducible features from computed tomography enterography (CTE). Logistic regression modeling was used to create models based on the radiomics signature and significant clinical factors, with the receiver operating characteristic curve (ROC) used to compare their performance.

Results:

The study found that 64 of the 181 CD patients included experienced secondary LOR. The radiomics signature performed well in predicting secondary LOR, showing good discrimination in the training cohort (AUC [area under the curve], 0.947; 95% confidence interval [CI], 0.910-0.976), the testing cohort (AUC, 0.860; 95% CI, 0.768-0.941), and the validation cohort (AUC, 0.921; 95% CI 0.831-1.000). Decision curve analysis (DCA) demonstrated the clinical value of the radiomics nomogram.

Conclusions:

The CTE-based radiomics model showed good performance in predicting secondary LOR in CD patients. The nomogram can help clinicians choose alternative biologics early for CD patients.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Heliyon Año: 2023 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Heliyon Año: 2023 Tipo del documento: Article