Development and validation of a nomogram for predicting the probability of arthroplasty in patients with osteonecrosis of the femoral head after fibular strut grafting
Year: 2026
Type: article
Study design: Observational Study
Abstract: BACKGROUND: While fibular strut grafting (FSG) is effective for osteonecrosis of the femoral head (ONFH), some patients still progress to total hip arthroplasty (THA). This study aimed to identify risk factors for FSG failure and develop a validated nomogram to predict the mid-long term survival rate after FSG. METHODS: Data on patients with ONFH who underwent FSG were collected in our institution from February 2009 to December 2018. Independent predictors were identified using univariable and multivariable Cox regression analyses. Kaplan-Meier analysis was used to estimate survival after FSG. A nomogram predicting failure, defined as conversion to THA, was developed from the selected predictors and internally validated using the concordance index (C index), the Receiver Operating characteristic (ROC) curves, and calibration curves. RESULTS: Among 416 eligible patients, 55 converted to THA. The 5-, 8-, and 10-year survival rates after FSG were 89.7%, 83.6%, and 82%, respectively. Age, smoking, Fibrinogen (FIB), hypertension, diabetes, and ARCO stage were independent predictors of failure. Subsequently, a nomogram model was developed incorporating 7 predictors (including JIC classification). Its C-index was 0.734 (95%CI 0.66-0.80). The area under the curves (AUCs) of the nomogram predicted for 5-, 8-, and 10-year were 0.727, 0.735, and 0.735, respectively. Predicted and observed survival rates agreed closely. CONCLUSION: The internal validation shows that the nomogram model has acceptable discriminative ability and good accuracy. It may support clinical application, effectively optimize perioperative management, and help doctors and patients to avoid FSG failure.
Source: Annals of Medicine
Language: English
Topic: Bone and Joint Diseases
Subfield: Orthopedics and Sports Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,557
Awards: G3226519281, G6758420856, G6867880645
OpenAlex ID: W7221193582
