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Osteonecrosis in individuals with systemic lupus erythematosus: A predictive model
Jennifer Mendoza-Alonzo1, José Zayas-Castro1, Karina Soto-Sandoval2
1Department of Industrial and Management Systems Engineering, University of South Florida, 4202 E. Fowler Avenue, Tampa, FL 33620, USA.
Objective:
This work attempts to provide a model to predict the development of osteonecrosis (ON) in individuals with systemic lupus erythematosus (SLE) using pharmacological, demographic, and psychoactive factors.
Method:
A review of the literature was conducted to construct a survey administered across Chile to individuals with SLE during a period of three weeks. This work used a sample size of 46 de-identified data records. Two Bayesian logistic regression models were created, with non-informative prior and informative prior distributions, and a random forest model was done for comparison. All models were cross-validated.
Results:
The significant variables used were mean corticosteroids per day (mg) and tobacco use. The random forest model provided good accuracy and sensitivity, but low specificity. Bayesian logistic regression with prior information increased the specificity.
Conclusions:
This work determined that the use of corticosteroids and tobacco are significant variables to predict ON. Using prior information provides good accuracy, specificity, and sensitivity to the prediction. Further studies need to be conducted to validate the model using a testing set.
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