Establishment and internal validation of a model to predict the efficacy of Adalimumab in Crohn’s disease
Abstract Background: Clinically, the ability to distinguish which Crohn’s disease patients can benefit from Adalimumab is limited. Aims: This study aimed to develop a model for predicting clinical remission probability for Crohn’s disease patients with Adalimumab at 12 weeks. The model assists clini...
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Nature Portfolio
2025-01-01
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| Online Access: | https://doi.org/10.1038/s41598-024-82855-0 |
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| author | Fang Wang He Zhou Yujie Zhang Yu Da Tiantian Zhang Yanting Shi Tong Wu Jie Liang |
| author_facet | Fang Wang He Zhou Yujie Zhang Yu Da Tiantian Zhang Yanting Shi Tong Wu Jie Liang |
| author_sort | Fang Wang |
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| description | Abstract Background: Clinically, the ability to distinguish which Crohn’s disease patients can benefit from Adalimumab is limited. Aims: This study aimed to develop a model for predicting clinical remission probability for Crohn’s disease patients with Adalimumab at 12 weeks. The model assists clinicians in identifying which Crohn’s disease patients are likely to benefit from Adalimumab treatment before starting therapy, thus optimizing individualized treatment strategies. Methods: Demographic and clinical characteristics of Crohn’s disease patients were utilized to develop a model for clinical remission probability. LASSO regression was used to select predictive factors, and predictions were made using a logistic regression model. The model was internally validated using the bootstrap method (resampling 1000 times). Results: 68 patients with Crohn’s disease were enrolled in this study. Clinical remission was observed in 55.9% at 12 weeks. Three variables were selected through the least absolute shrinkage and selection operator regression method, including Adalimumab-positive cell count, disease duration, and neutrophil count of Crohn’s disease patients. A predictive model was constructed by multivariate logistic regression (Adalimumab-positive cell count (OR, 1.143; 95%CI, 1.056–1.261), disease duration (OR, 0.967; 95%CI, 0.937–0.986), and neutrophil count (×109/L) (OR, 1.274; 95%CI,1.014–1.734)). The predictive model yielded an area under the curve of 0.866 (95%CI, 0.776–0.956), and in the internal validation, the area under the curve was 0.870 (95%CI, 0.770–0.940). Conclusions: This model provides a convenient tool to assess the likelihood of patient remission prior to Adalimumab treatment, thereby supporting the development of personalized treatment plans. |
| format | Article |
| id | doaj-art-5ea75e526b5f44b48d47763fee95419f |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-5ea75e526b5f44b48d47763fee95419f2025-01-19T12:21:43ZengNature PortfolioScientific Reports2045-23222025-01-0115111110.1038/s41598-024-82855-0Establishment and internal validation of a model to predict the efficacy of Adalimumab in Crohn’s diseaseFang Wang0He Zhou1Yujie Zhang2Yu Da3Tiantian Zhang4Yanting Shi5Tong Wu6Jie Liang7State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical UniversityState Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical UniversityDepartment of Histology and Embryology, School of Basic Medicine, Xi’an Medical UniversityState Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical UniversityState Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical UniversityState Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical UniversityState Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical UniversityState Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, Fourth Military Medical UniversityAbstract Background: Clinically, the ability to distinguish which Crohn’s disease patients can benefit from Adalimumab is limited. Aims: This study aimed to develop a model for predicting clinical remission probability for Crohn’s disease patients with Adalimumab at 12 weeks. The model assists clinicians in identifying which Crohn’s disease patients are likely to benefit from Adalimumab treatment before starting therapy, thus optimizing individualized treatment strategies. Methods: Demographic and clinical characteristics of Crohn’s disease patients were utilized to develop a model for clinical remission probability. LASSO regression was used to select predictive factors, and predictions were made using a logistic regression model. The model was internally validated using the bootstrap method (resampling 1000 times). Results: 68 patients with Crohn’s disease were enrolled in this study. Clinical remission was observed in 55.9% at 12 weeks. Three variables were selected through the least absolute shrinkage and selection operator regression method, including Adalimumab-positive cell count, disease duration, and neutrophil count of Crohn’s disease patients. A predictive model was constructed by multivariate logistic regression (Adalimumab-positive cell count (OR, 1.143; 95%CI, 1.056–1.261), disease duration (OR, 0.967; 95%CI, 0.937–0.986), and neutrophil count (×109/L) (OR, 1.274; 95%CI,1.014–1.734)). The predictive model yielded an area under the curve of 0.866 (95%CI, 0.776–0.956), and in the internal validation, the area under the curve was 0.870 (95%CI, 0.770–0.940). Conclusions: This model provides a convenient tool to assess the likelihood of patient remission prior to Adalimumab treatment, thereby supporting the development of personalized treatment plans.https://doi.org/10.1038/s41598-024-82855-0Crohn’s diseasePredictionNomogram |
| spellingShingle | Fang Wang He Zhou Yujie Zhang Yu Da Tiantian Zhang Yanting Shi Tong Wu Jie Liang Establishment and internal validation of a model to predict the efficacy of Adalimumab in Crohn’s disease Scientific Reports Crohn’s disease Prediction Nomogram |
| title | Establishment and internal validation of a model to predict the efficacy of Adalimumab in Crohn’s disease |
| title_full | Establishment and internal validation of a model to predict the efficacy of Adalimumab in Crohn’s disease |
| title_fullStr | Establishment and internal validation of a model to predict the efficacy of Adalimumab in Crohn’s disease |
| title_full_unstemmed | Establishment and internal validation of a model to predict the efficacy of Adalimumab in Crohn’s disease |
| title_short | Establishment and internal validation of a model to predict the efficacy of Adalimumab in Crohn’s disease |
| title_sort | establishment and internal validation of a model to predict the efficacy of adalimumab in crohn s disease |
| topic | Crohn’s disease Prediction Nomogram |
| url | https://doi.org/10.1038/s41598-024-82855-0 |
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