Table 4.

Cox regression analysis, including mutational status grouped as DTA mutation and “other mutation,” sex, age, and tobacco consumption

VariableHR95% CIP
A.    
 Only DTA mutation 1.21 1.01-1.45 .035 
 Other mutation 1.01 0.65-1.55 .981 
 Age, y 1.11 1.08-1.13 <.001 
 Sex (male) 1.15 0.91-1.46 .233 
 Smoking (1st tertile) 1.03 0.82-1.30 .772 
 Smoking (2nd tertile) 1.22 0.96-1.55 .108 
 Smoking (3rd tertile) 1.72 1.26-2.36 .001 
B.    
 Only DTA mutation 1.18 0.98-1.41 .077 
 Other mutation 0.97 0.63-1.50 .899 
 Sex (male) 1.15 0.91-1.44 .247 
 Smoking (1st tertile) 1.04 0.83-1.31 .715 
 Smoking (2nd tertile) 1.25 0.99-1.58 .060 
 Smoking (3rd tertile) 1.75 1.28-2.38 <.001 
VariableHR95% CIP
A.    
 Only DTA mutation 1.21 1.01-1.45 .035 
 Other mutation 1.01 0.65-1.55 .981 
 Age, y 1.11 1.08-1.13 <.001 
 Sex (male) 1.15 0.91-1.46 .233 
 Smoking (1st tertile) 1.03 0.82-1.30 .772 
 Smoking (2nd tertile) 1.22 0.96-1.55 .108 
 Smoking (3rd tertile) 1.72 1.26-2.36 .001 
B.    
 Only DTA mutation 1.18 0.98-1.41 .077 
 Other mutation 0.97 0.63-1.50 .899 
 Sex (male) 1.15 0.91-1.44 .247 
 Smoking (1st tertile) 1.04 0.83-1.31 .715 
 Smoking (2nd tertile) 1.25 0.99-1.58 .060 
 Smoking (3rd tertile) 1.75 1.28-2.38 <.001 

In part A, time since blood sample is used as the underlying time scale, whereas age is used as the underlying the time scale in part B. When we divided the mutations into DTA and “other mutations,” defined as non-DTA mutations, but with or without cooccurring DTA mutations, we found a significant association of DTA mutations after adjusting for age, sex, and tobacco consumption. This association was retained as a borderline significant association when we used age as the underlying time scale in the Cox regression.

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