A novel online calculator based on clinical features and hematological parameters to predict total skin clearance in patients with moderate to severe psoriasis
Abstract Background Treatment responses to biologic agents vary between patients with moderate to severe psoriasis; while some patients achieve total skin clearance (TSC), a proportion of patients may only experience partial improvement. Objective This study was designed to identify potential predic...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2024-01-01
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| Series: | Journal of Translational Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12967-023-04847-4 |
| _version_ | 1827326378377216000 |
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| author | Yuxiong Jiang Dawei Huang Qianyu Chen Yingyuan Yu Yifan Hu Yu Wang Rongfen Chen Lingling Yao Xiaoyuan Zhong Luyang Kong Qian Yu Jiajing Lu Ying Li Yuling Shi |
| author_facet | Yuxiong Jiang Dawei Huang Qianyu Chen Yingyuan Yu Yifan Hu Yu Wang Rongfen Chen Lingling Yao Xiaoyuan Zhong Luyang Kong Qian Yu Jiajing Lu Ying Li Yuling Shi |
| author_sort | Yuxiong Jiang |
| collection | DOAJ |
| description | Abstract Background Treatment responses to biologic agents vary between patients with moderate to severe psoriasis; while some patients achieve total skin clearance (TSC), a proportion of patients may only experience partial improvement. Objective This study was designed to identify potential predictors for achieving TSC in psoriasis patients treated with IL-17 inhibitors. It also aimed to develop an easy-to-use calculator incorporating these factors by the nomogram to predict TSC response. Methods A total of 381 patients with psoriasis receiving ixekizumab were included in the development cohort and 229 psoriasis patients who initiated secukinumab treatment were included in the validation cohort. The study endpoint was achieving TSC after 12 weeks of IL-17 inhibitors treatment, defined as the 100% improvement in Psoriasis Area and Severity Index (PASI 100). Multivariate Cox regression analyses and LASSO analysis were performed to identify clinical predictors and blood predictors respectively. Results The following parameters were identified as predictive factors associated with TSC: previous biologic treatment, joint involvement, genital area affected, early response (PASI 60 at week 4), neutrophil counts and uric acid levels. The nomogram model incorporating these factors achieved good discrimination in the development cohort (AUC, 0.721; 95% CI 0.670–0.773) and validation cohort (AUC, 0.715; 95% CI 0.665–0.760). The calibration curves exhibited a satisfactory fit, indicating the accuracy of the model. Furthermore, the decision curve analysis confirmed the clinical utility of the nomogram, highlighting its favorable value for practical application. Web-based online calculator has been developed to enhance the efficiency of clinical applications. Conclusions This study developed a practical and clinically applicable nomogram model for the prediction of TSC in patients with moderate to severe psoriasis. The nomogram model demonstrated robust predictive performance and exhibited significant clinical utility. Trial registration A multi-center clinical study of systemic treatment strategies for psoriasis in Chinese population;ChiCTR2000036186; Registered 31 August 2020; https://www.chictr.org.cn/showproj.html?proj=58256 . |
| first_indexed | 2024-03-07T14:43:36Z |
| format | Article |
| id | doaj.art-5e57a1f2884249ca9918ce07ad9cd989 |
| institution | Directory Open Access Journal |
| issn | 1479-5876 |
| language | English |
| last_indexed | 2024-03-07T14:43:36Z |
| publishDate | 2024-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj.art-5e57a1f2884249ca9918ce07ad9cd9892024-03-05T20:06:39ZengBMCJournal of Translational Medicine1479-58762024-01-0122111310.1186/s12967-023-04847-4A novel online calculator based on clinical features and hematological parameters to predict total skin clearance in patients with moderate to severe psoriasisYuxiong Jiang0Dawei Huang1Qianyu Chen2Yingyuan Yu3Yifan Hu4Yu Wang5Rongfen Chen6Lingling Yao7Xiaoyuan Zhong8Luyang Kong9Qian Yu10Jiajing Lu11Ying Li12Yuling Shi13Department of Dermatology, Shanghai Skin Disease Hospital, Tongji University School of MedicineDepartment of Dermatology, Shanghai Skin Disease Hospital, Tongji University School of MedicineDepartment of Dermatology, Shanghai Skin Disease Hospital, Tongji University School of MedicineDepartment of Dermatology, Shanghai Skin Disease Hospital, Tongji University School of MedicineDepartment of Dermatology, Shanghai Skin Disease Hospital, Tongji University School of MedicineDepartment of Dermatology, Shanghai Skin Disease Hospital, Tongji University School of MedicineDepartment of Dermatology, Shanghai Skin Disease Hospital, Tongji University School of MedicineDepartment of Dermatology, Shanghai Skin Disease Hospital, Tongji University School of MedicineDepartment of Dermatology, Shanghai Skin Disease Hospital, Tongji University School of MedicineDepartment of Dermatology, Shanghai Skin Disease Hospital, Tongji University School of MedicineInstitute of Psoriasis, Tongji University School of MedicineDepartment of Dermatology, Shanghai Skin Disease Hospital, Tongji University School of MedicineDepartment of Dermatology, Shanghai Skin Disease Hospital, Tongji University School of MedicineDepartment of Dermatology, Shanghai Skin Disease Hospital, Tongji University School of MedicineAbstract Background Treatment responses to biologic agents vary between patients with moderate to severe psoriasis; while some patients achieve total skin clearance (TSC), a proportion of patients may only experience partial improvement. Objective This study was designed to identify potential predictors for achieving TSC in psoriasis patients treated with IL-17 inhibitors. It also aimed to develop an easy-to-use calculator incorporating these factors by the nomogram to predict TSC response. Methods A total of 381 patients with psoriasis receiving ixekizumab were included in the development cohort and 229 psoriasis patients who initiated secukinumab treatment were included in the validation cohort. The study endpoint was achieving TSC after 12 weeks of IL-17 inhibitors treatment, defined as the 100% improvement in Psoriasis Area and Severity Index (PASI 100). Multivariate Cox regression analyses and LASSO analysis were performed to identify clinical predictors and blood predictors respectively. Results The following parameters were identified as predictive factors associated with TSC: previous biologic treatment, joint involvement, genital area affected, early response (PASI 60 at week 4), neutrophil counts and uric acid levels. The nomogram model incorporating these factors achieved good discrimination in the development cohort (AUC, 0.721; 95% CI 0.670–0.773) and validation cohort (AUC, 0.715; 95% CI 0.665–0.760). The calibration curves exhibited a satisfactory fit, indicating the accuracy of the model. Furthermore, the decision curve analysis confirmed the clinical utility of the nomogram, highlighting its favorable value for practical application. Web-based online calculator has been developed to enhance the efficiency of clinical applications. Conclusions This study developed a practical and clinically applicable nomogram model for the prediction of TSC in patients with moderate to severe psoriasis. The nomogram model demonstrated robust predictive performance and exhibited significant clinical utility. Trial registration A multi-center clinical study of systemic treatment strategies for psoriasis in Chinese population;ChiCTR2000036186; Registered 31 August 2020; https://www.chictr.org.cn/showproj.html?proj=58256 .https://doi.org/10.1186/s12967-023-04847-4PsoriasisTotal skin clearancePsoriasis area and severity indexNomogramPredictive modeling |
| spellingShingle | Yuxiong Jiang Dawei Huang Qianyu Chen Yingyuan Yu Yifan Hu Yu Wang Rongfen Chen Lingling Yao Xiaoyuan Zhong Luyang Kong Qian Yu Jiajing Lu Ying Li Yuling Shi A novel online calculator based on clinical features and hematological parameters to predict total skin clearance in patients with moderate to severe psoriasis Journal of Translational Medicine Psoriasis Total skin clearance Psoriasis area and severity index Nomogram Predictive modeling |
| title | A novel online calculator based on clinical features and hematological parameters to predict total skin clearance in patients with moderate to severe psoriasis |
| title_full | A novel online calculator based on clinical features and hematological parameters to predict total skin clearance in patients with moderate to severe psoriasis |
| title_fullStr | A novel online calculator based on clinical features and hematological parameters to predict total skin clearance in patients with moderate to severe psoriasis |
| title_full_unstemmed | A novel online calculator based on clinical features and hematological parameters to predict total skin clearance in patients with moderate to severe psoriasis |
| title_short | A novel online calculator based on clinical features and hematological parameters to predict total skin clearance in patients with moderate to severe psoriasis |
| title_sort | novel online calculator based on clinical features and hematological parameters to predict total skin clearance in patients with moderate to severe psoriasis |
| topic | Psoriasis Total skin clearance Psoriasis area and severity index Nomogram Predictive modeling |
| url | https://doi.org/10.1186/s12967-023-04847-4 |
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