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Table 4 Logistic regression: effect of tobacco and XPC, ERCC2 and ERCC5 polymorphisms on tumors stages

From: The effect of tobacco, XPC, ERCC2 and ERCC5 genetic variants in bladder cancer development

         95% Confidence Interval for Exp(B)
stade a B Std. Error Wald Df Sig. Exp(B) Lower Bound Upper Bound
Pt1 Intercept -,55 1,80 ,09 1 ,75    
  Sex ,97 ,78 1,54 1 ,21 2,64 ,57 12,20
  Age -1,16 ,47 6,06 1 ,01 ,31 ,12 ,78
  [XPC (A/C) = AA] -,11 ,53 ,04 1 ,82 ,89 ,31 2,53
  [XPC (A/C) = AC] ,49 ,54 ,83 1 ,36 1,64 ,56 4,74
  [XPC (A/C) = CC] 0b . . 0 . . . .
  [ERCC2 (A/C) = AA] ,66 ,64 1,07 1 ,30 1,94 ,55 6,84
  [ERCC2 (A/C) = AC] ,24 ,65 ,13 1 ,71 1,27 ,35 4,56
  [ERCC2 (A/C) = CC] 0b . . 0 . . . .
  [ERCC5 (G/C) = CC] ,64 ,65 ,99 1 ,31 1,91 ,53 6,82
  [ERCC5(G/C) = GC] ,25 ,41 ,36 1 ,54 1,28 ,57 2,87
  [ERCC5(G/C) = GG] 0b . . 0 . . . .
  [PY = 0] ,20 ,56 ,13 1 ,71 1,22 ,40 3,72
  [PY = 1-19] -1,87 ,89 4,41 1 ,03 ,15 ,02 ,88
  [PY ≥ 20] 0b . . 0 . . . .
≥pT2 Intercept -,62 3,04 ,04 1 ,83    
  Sex 1,27 1,41 ,81 1 ,36 3,58 ,22 57,00
  Age -1,71 ,63 7,22 1 ,00 ,18 ,05 ,63
  [XPC(A/C) = AA] -,42 ,59 ,51 1 ,47 ,65 ,20 2,10
  [XPC(A/C) = AC] -,19 ,62 ,09 1 ,75 ,82 ,24 2,77
  [XPC(A/C) = CC] 0b . . 0 . . . .
  [ERCC2(A/C) = AA] ,65 ,80 ,67 1 ,41 1,93 ,40 9,29
  [ERCC2(A/C) = AC] ,34 ,80 ,18 1 ,67 1,40 ,29 6,81
  [ERCC2(A/C) = CC] 0b . . 0 . . . .
  [ERCC5(G/C) = CC] 1,02 ,71 2,07 1 ,14 2,79 ,69 11,33
  [ERCC5(G/C) = GC] -,16 ,50 ,10 1 ,74 ,84 ,31 2,29
  [ERCC5(G/C) = GG] 0b . . 0 . . . .
  [PY = 0] -1,21 ,88 1,87 1 ,17 ,29 ,05 1,69
  [PY = 1-19] -2,24 1,16 3,72 1 ,05 ,10 ,01 1,03
  [PY ≥ 20] 0b . . 0 . . . .
  1. This model was obtained after adjustment to sex and age; a: The reference category is Pta tumor group; b: this parameter is set to zero because it is redundant; PY: pack years. Logistic regression: Number of observation = 193, Chi-square: 32.851, p = 0.035, Pseudo R-square = 0.087, Log likelihood = 187,948