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Table 5 Summary statistics to assess binary FGF-21 in predicting incident type 2 diabetes risk among female participants, the Singapore Chinese Health Studya

From: Sex-specific association between fibroblast growth factor 21 and type 2 diabetes: a nested case-control study in Singapore Chinese men and women

Variable

Multivariable modelsb

Discrimination (AUC [95% CI])

Calibration (AIC)

NRI

IDI

Base model 1c

0.622 (0.555–0.689)

156

  

Base model 1c + FGF-21

0.640 (0.574–0.706)f

149

0.358 (0.118–0.598)

0.028 (0.007–0.048)

Base model 2d

0.764 (0.707–0.820)

130

  

Base model 2d + FGF-21

0.768 (0.712–0.824)f

128

0.358 (0.118–0.598)

0.013 (0.001–0.025)

Base model 3e

0.792 (0.739–0.845)

135

  

Base model 3e + FGF-21

0.798 (0.746–0.850)f

133

0.388 (0.149–0.628)

0.015 (0.001–0.029)

  1. aBinary FGF-21 was created using a cutoff point of 123, with a sensitivity of 75.7%, and specificity of 41.4%
  2. bMultivariable model adjusted for all the variables included in the base model plus binary FGF-21 (<123 vs. ≥ 123 pg/mL)
  3. cBase model 1 included age (continuous) and BMI (continuous)
  4. dBase model 2 included variables in base model 1 plus smoking status (never, ever smoker), history of hypertension (yes, no), and levels of TG (mmol/L), HDL-C (mmol/L), and random glucose (mmol/L) (all in quartiles)
  5. eBase model 3 included variables in base model 2 plus adiponectin (μg/mL) and hs-CRP (mg/L) (both in quartiles)
  6. fCompared to the base model, the P-values for the differences of AUC after including FGF-21 to the base model were 0.11 for base model 1, 0.56 for base model 2 and 0.41 for model 3