title: Prediction of vitamin D deficiency by simple patient characteristics.
abstract: BACKGROUND
  Vitamin D status is currently diagnosed by measuring serum 25-hydroxyvitamin D [25(OH)D].
  
  
  OBJECTIVE
  This study aimed to develop a risk profile that can be used to easily identify older individuals at high risk of vitamin D deficiency.
  
  
  METHODS
  This study was performed within the Longitudinal Aging Study Amsterdam, an ongoing cohort study in a representative sample of the Dutch older population (n = 1509 for the development sample and n = 1100 for the validation sample). Prediction models for serum 25(OH)D concentrations <50 and <30 nmol/L were developed by using backward logistic regression. Risk scores were calculated by dividing the individual regression coefficients by the regression coefficient with the lowest β to create simple scores.
  
  
  RESULTS
  Serum 25(OH)D concentrations <50 and <30 nmol/L were present in 46.2% and 17.5% of participants, respectively. The model for the prediction of concentrations <50 nmol/L consisted of 13 easily assessable predictors, whereas the model for concentrations <30 nmol/L contained 10 predictors. The resulting areas under the curve (AUCs) were 0.78 and 0.80, respectively. The AUC in the external validation data set was 0.71 for the <50-nmol/L model. At a cutoff of 58 in total risk score (range: 8-97), the model predicted concentrations <50 nmol/L with a sensitivity of 61% and a specificity of 82%, whereas these values were 61% and 84%, respectively, at a cutoff of 110 in the total risk score (range: 6-204) in the model for concentrations <30 nmol/L.
  
  
  CONCLUSIONS
  Two total risk scores, including 13 or 10 predictors that can easily be assessed, were developed and are able to predict serum 25(OH)D concentrations <50 and <30 nmol/L accurately. These risk scores may be useful in clinical practice to identify persons at risk of vitamin D deficiency.
authors.affiliation: Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research (ES, MWH, MV, and NMvS), and the Departments of Internal Medicine and Endocrinology (RTdJ, MdH, and PL) and General Practice (TM), VU University Medical Center, Amsterdam, Netherlands; and the Department of Health Sciences, EMGO Institute for Health and Care Research, Faculty of Earth and Life Sciences, VU University Amsterdam, Amsterdam, Netherlands (MWH and MV).
authors.forename: Evelien
authors.initials: E
authors.lastname: Sohl
authors.forename: Martijn W
authors.initials: MW
authors.lastname: Heymans
authors.forename: Renate T
authors.initials: RT
authors.lastname: de Jongh
authors.forename: Martin
authors.initials: M
authors.lastname: den Heijer
authors.forename: Marjolein
authors.initials: M
authors.lastname: Visser
authors.forename: Thomas
authors.initials: T
authors.lastname: Merlijn
authors.forename: Paul
authors.initials: P
authors.lastname: Lips
authors.forename: Natasja M
authors.initials: NM
authors.lastname: van Schoor
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001499:Bayes Theorem; D005260:Female; D006801:Humans; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D009426:Netherlands; D015995:Prevalence; D012307:Risk Factors; D014807:Vitamin D / Q000097:blood*; D014808:Vitamin D Deficiency / Q000097:blood / Q000175:diagnosis* / Q000453:epidemiology*
chemical_list: D014807:Vitamin D