Development and validation of a prediction model for glucocorticoid-associated osteonecrosis of the femoral head by targeted sequencing

Author:

Jiang Chang1ORCID,Wang Xinyuan1,Huang Kai2,Chen Limeng2,Ji Zongfei3,Hua Bingxuan1,Qi Guobin1,Yuan Hengfeng1,Cao Yuanwu1,Jiang Lindi3ORCID,Peng David Haixiang2,Yan Zuoqin1

Affiliation:

1. Department of Orthopaedics, Zhongshan Hospital, Fudan University

2. Dunwill Medical Technology

3. Department of Rheumatology, Zhongshan Hospital, Fudan University, Shanghai, China

Abstract

Abstract Objective To develop and validate a prediction model based on targeted sequencing for glucocorticoid (GC)-associated osteonecrosis of the femoral head (GA-ONFH) in GC-treated adults. Methods This two-centre retrospective study was conducted between July 2015 and April 2019 at Zhongshan Hospital (training set) and the Sixth People’s Hospital (test set) in Shanghai, China. All patients had a history of GC therapy, with a dose exceeding 2000 mg equivalent prednisone within 6 weeks. Patients were divided into two groups according to whether they were diagnosed with GA-ONFH within 2 years after GC initiation. Blood or saliva samples were collected for targeted sequencing of 358 single nucleotide polymorphisms and genetic risk score (GRS) calculating for developing GA-ONFH prediction model. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were performed to evaluate and validate the model. Results . The training set comprised 117 patients, while the test set comprised 30 patients for external validation. Logistic regression analysis showed that GRS was significantly associated with GA-ONFH (OR 1.87, 95% CI: 1.48, 2.37). The ROC and DCA curves showed that the multivariate model considering GRS, age at GC initial, sex and underlying diseases had a discrimination with area under the ROC curve (AUC) of 0.98 (95% CI: 0.96, 1.00). This model was further externally validated using the test set with an AUC of 0.91 (95% CI: 0.81, 1.00). Conclusion Our prediction model comprising GRS, age, sex and underlying diseases yields valid predictions of GA-ONFH incidence. It may facilitate effective screening and prevention strategies of GA-ONFH.

Funder

National Natural Science Foundation of China

Shanghai Hospital Development Center Emerging Advanced Technology Joint Research Project

Clinical Research Plan of SHDC

Publisher

Oxford University Press (OUP)

Subject

Pharmacology (medical),Rheumatology

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