The prediction of haemophilic arthropathy progression based on MRI findings and clinical characteristics
Abstract Objective To identify magnetic resonance imaging (MRI) and clinical characteristics that are closely associated with the progression of haemophilic arthropathy (HA) after different therapies and to establish a prediction model for HA progression using Cox proportional hazards regression, th...
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BMC
2025-04-01
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| Series: | Orphanet Journal of Rare Diseases |
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| Online Access: | https://doi.org/10.1186/s13023-025-03716-1 |
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| author | Lu Zhang Jinxia Guo Shufang Wei Jiajia Li Yincong Dou Tianming Cheng Yinghui Ge Tuo Zhang |
| author_facet | Lu Zhang Jinxia Guo Shufang Wei Jiajia Li Yincong Dou Tianming Cheng Yinghui Ge Tuo Zhang |
| author_sort | Lu Zhang |
| collection | DOAJ |
| description | Abstract Objective To identify magnetic resonance imaging (MRI) and clinical characteristics that are closely associated with the progression of haemophilic arthropathy (HA) after different therapies and to establish a prediction model for HA progression using Cox proportional hazards regression, thus facilitating the development of personalized clinical replacement therapy plans. Materials and methods Retrospective clinical and imaging data were collected from HA patients registered at the Henan Provincial Registration Management Center of Haemophilia from December 2010 to May 2023. The inclusion criteria were joints with a history of haemorrhage and initial/posttreatment reevaluation with X-ray and MRI. Joints with severe damage (i.e., a Pettersson score > 6) were excluded. Joint disease progression was defined as a > 1-point increase in the Pettersson score. Progression-free survival (PFS) was the primary outcome. MRI observations revealed joint effusion, synovial hypertrophy, haemosiderin deposition, bone destruction or cystic degeneration at the joint margins, and cartilage destruction. Age, body mass index (BMI), factor VIII (FVIII) activity, activated partial thromboplastin time (APTT), prothrombin time (PT), therapy type, annual joint bleeding rate (AJBR), and the Haemophilia Joint Health Score (HJHS) were also assessed. Subsequently, univariate and multivariate Cox proportional hazards regression models were employed to analyse the clinical and imaging characteristics influencing HA progression. Factors with a P < 0.15 in univariate analysis were subsequently included in the multivariate analysis. The impact of various imaging and clinical characteristics on PFS was assessed via Kaplan‒Meier (K-M) survival curves. Results This study included 98 joints across 65 patients. During the follow-up period, 63 joints exhibited progression. Both univariate and multivariate Cox analyses revealed that MRI-detected synovial hypertrophy (MRI-SP) was an independent risk factor for HA progression. Incorporating BMI into the model improved its predictive performance (Model 1: c-index = 0.671, P < 0.01). Spearman’s correlation analysis revealed strong correlations between baseline MRI-SP and detected haemosiderin deposition (r = 0.73) as well as AJBRs (r = 0.66). K-M survival curves indicated that patients receiving prophylactic treatment and those with less severe MRI-SP had better progression-free survival. Conclusion MRI-detected synovial hypertrophy is an independent risk factor for HA progression. The predictive model, which includes BMI as a covariate for assessing the risk of HA progression, can serve as an auxiliary tool for developing personalized treatment plans for HA patients. |
| format | Article |
| id | doaj-art-064ab27c3beb4e3c8a936a09e4f4ac6a |
| institution | OA Journals |
| issn | 1750-1172 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | BMC |
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| series | Orphanet Journal of Rare Diseases |
| spelling | doaj-art-064ab27c3beb4e3c8a936a09e4f4ac6a2025-08-20T02:17:58ZengBMCOrphanet Journal of Rare Diseases1750-11722025-04-012011910.1186/s13023-025-03716-1The prediction of haemophilic arthropathy progression based on MRI findings and clinical characteristicsLu Zhang0Jinxia Guo1Shufang Wei2Jiajia Li3Yincong Dou4Tianming Cheng5Yinghui Ge6Tuo Zhang7Department of Medical Imaging, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou UniversityGE Healthcare MR ResearchDepartment of Radiology, Fuwai Central China Cardiovascular HospitalDepartment of Radiology, Fuwai Central China Cardiovascular HospitalDepartment of Medical Imaging, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou UniversityDepartment of Medical Imaging, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou UniversityDepartment of Radiology, Fuwai Central China Cardiovascular HospitalDepartment of Radiology, Fuwai Central China Cardiovascular HospitalAbstract Objective To identify magnetic resonance imaging (MRI) and clinical characteristics that are closely associated with the progression of haemophilic arthropathy (HA) after different therapies and to establish a prediction model for HA progression using Cox proportional hazards regression, thus facilitating the development of personalized clinical replacement therapy plans. Materials and methods Retrospective clinical and imaging data were collected from HA patients registered at the Henan Provincial Registration Management Center of Haemophilia from December 2010 to May 2023. The inclusion criteria were joints with a history of haemorrhage and initial/posttreatment reevaluation with X-ray and MRI. Joints with severe damage (i.e., a Pettersson score > 6) were excluded. Joint disease progression was defined as a > 1-point increase in the Pettersson score. Progression-free survival (PFS) was the primary outcome. MRI observations revealed joint effusion, synovial hypertrophy, haemosiderin deposition, bone destruction or cystic degeneration at the joint margins, and cartilage destruction. Age, body mass index (BMI), factor VIII (FVIII) activity, activated partial thromboplastin time (APTT), prothrombin time (PT), therapy type, annual joint bleeding rate (AJBR), and the Haemophilia Joint Health Score (HJHS) were also assessed. Subsequently, univariate and multivariate Cox proportional hazards regression models were employed to analyse the clinical and imaging characteristics influencing HA progression. Factors with a P < 0.15 in univariate analysis were subsequently included in the multivariate analysis. The impact of various imaging and clinical characteristics on PFS was assessed via Kaplan‒Meier (K-M) survival curves. Results This study included 98 joints across 65 patients. During the follow-up period, 63 joints exhibited progression. Both univariate and multivariate Cox analyses revealed that MRI-detected synovial hypertrophy (MRI-SP) was an independent risk factor for HA progression. Incorporating BMI into the model improved its predictive performance (Model 1: c-index = 0.671, P < 0.01). Spearman’s correlation analysis revealed strong correlations between baseline MRI-SP and detected haemosiderin deposition (r = 0.73) as well as AJBRs (r = 0.66). K-M survival curves indicated that patients receiving prophylactic treatment and those with less severe MRI-SP had better progression-free survival. Conclusion MRI-detected synovial hypertrophy is an independent risk factor for HA progression. The predictive model, which includes BMI as a covariate for assessing the risk of HA progression, can serve as an auxiliary tool for developing personalized treatment plans for HA patients.https://doi.org/10.1186/s13023-025-03716-1Haemophilic arthropathyMagnetic resonance imagingProgressionPredictionSynovial hypertrophy |
| spellingShingle | Lu Zhang Jinxia Guo Shufang Wei Jiajia Li Yincong Dou Tianming Cheng Yinghui Ge Tuo Zhang The prediction of haemophilic arthropathy progression based on MRI findings and clinical characteristics Orphanet Journal of Rare Diseases Haemophilic arthropathy Magnetic resonance imaging Progression Prediction Synovial hypertrophy |
| title | The prediction of haemophilic arthropathy progression based on MRI findings and clinical characteristics |
| title_full | The prediction of haemophilic arthropathy progression based on MRI findings and clinical characteristics |
| title_fullStr | The prediction of haemophilic arthropathy progression based on MRI findings and clinical characteristics |
| title_full_unstemmed | The prediction of haemophilic arthropathy progression based on MRI findings and clinical characteristics |
| title_short | The prediction of haemophilic arthropathy progression based on MRI findings and clinical characteristics |
| title_sort | prediction of haemophilic arthropathy progression based on mri findings and clinical characteristics |
| topic | Haemophilic arthropathy Magnetic resonance imaging Progression Prediction Synovial hypertrophy |
| url | https://doi.org/10.1186/s13023-025-03716-1 |
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