title: On the Use of Fractional Polynomial Models to Assess Preventive Aspect of Variables: An Example in Prevention of Mortality Following HIV Infection.
abstract: BACKGROUND
  Identification of disease risk factors can help in the prevention of diseases. In assessing the predictive value of continuous variables, a routine procedure is to categorize the factors. This yield to inability to detect non-linear relationship, if exist. Multivariate fractional polynomial (MFP) modeling is a flexible method to reveal non-linear associations. We aim to demonstrate the impact of choice of risk function on the significance of variables.
  
  
  METHODS
  We selected 6508 HIV-infected persons registered in the Australia National HIV Registry between 1980 and 2003 to assess the predictors associated with the risk of death after HIV infection prior to AIDS. First, CD4 count as a categorical factor with three other categorical variables (age, sex, and HIV exposure category) was entered into the Cox regression model. Second, CD4 counts as a continuous variable along with other categorical variables were entered into the fractional polynomial (FP) model.
  
  
  RESULTS
  Both the Cox and FP models showed age ≥ 40 years and hemophiliac patients were significantly associated with increased risk of death. In the categorized model, the CD4 variable did not reach the significance level. However, this variable was highly significant in the MFP model. The FP model showed slightly better performance in terms of discrimination ability and goodness of fit.
  
  
  CONCLUSIONS
  The FP model is a flexible method in detecting the predictive effect of continuous variables. This method enhances the ability to assess the predictive ability of variables and improves model performance.
authors.affiliation: Research Center for Modeling in Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran ; Department of Biostatistics and Epidemiology, Kerman University of Medical Sciences, Kerman, Iran.
authors.forename: Mohammad Reza
authors.initials: MR
authors.lastname: Baneshi
authors.forename: Fatemeh
authors.initials: F
authors.lastname: Nakhaee
authors.forename: Matthew
authors.initials: M
authors.lastname: Law
keywords: Continuous variables; HIV/AIDS; fractional polynomial; modeling