title: A novel approach for prediction of vitamin d status using support vector regression.
abstract: BACKGROUND
  Epidemiological evidence suggests that vitamin D deficiency is linked to various chronic diseases. However direct measurement of serum 25-hydroxyvitamin D (25(OH)D) concentration, the accepted biomarker of vitamin D status, may not be feasible in large epidemiological studies. An alternative approach is to estimate vitamin D status using a predictive model based on parameters derived from questionnaire data. In previous studies, models developed using Multiple Linear Regression (MLR) have explained a limited proportion of the variance and predicted values have correlated only modestly with measured values. Here, a new modelling approach, nonlinear radial basis function support vector regression (RBF SVR), was used in prediction of serum 25(OH)D concentration. Predicted scores were compared with those from a MLR model.
  
  
  METHODS
  Determinants of serum 25(OH)D in Caucasian adults (n = 494) that had been previously identified were modelled using MLR and RBF SVR to develop a 25(OH)D prediction score and then validated in an independent dataset. The correlation between actual and predicted serum 25(OH)D concentrations was analysed with a Pearson correlation coefficient.
  
  
  RESULTS
  Better correlation was observed between predicted scores and measured 25(OH)D concentrations using the RBF SVR model in comparison with MLR (Pearson correlation coefficient: 0.74 for RBF SVR; 0.51 for MLR). The RBF SVR model was more accurately able to identify individuals with lower 25(OH)D levels (<75 nmol/L).
  
  
  CONCLUSIONS
  Using identical determinants, the RBF SVR model provided improved prediction of serum 25(OH)D concentrations and vitamin D deficiency compared with a MLR model, in this dataset.
authors.affiliation: National Centre for Epidemiology and Population Health, The Australian National University, Canberra, Australia.
authors.forename: Shuyu
authors.initials: S
authors.lastname: Guo
authors.forename: Robyn M
authors.initials: RM
authors.lastname: Lucas
authors.forename: Anne-Louise
authors.initials: AL
authors.lastname: Ponsonby
mesh_terms: D000465:Algorithms; D006801:Humans; D016014:Linear Models; D012372:ROC Curve; D060388:Support Vector Machine; D014807:Vitamin D / Q000031:analogs & derivatives / Q000097:blood*; D014808:Vitamin D Deficiency / Q000097:blood / Q000453:epidemiology
chemical_list: D014807:Vitamin D; C104450:25-hydroxyvitamin D