Skip to main content

Table 3 Remoteness and patients’ socio-economic characteristics: univariate and multilevel logistic regression analysis as predictive factors of being operated on by a high-volume breast cancer surgeon

From: For patients with breast cancer, geographic and social disparities are independent determinants of access to specialized surgeons. A eleven-year population-based multilevel analysis

 

Univariate logistic regression analysis

Multilevel logistic regression analysis

 

Odds ratio (95 % CI*)

p-value

Odds ratio (95 % CI*)

p-value

Individual data

    

Age

    

< 50 years old

0.90 (0.76; 1.07)

<0.001

 

0.179

50 to 74 years old

1

 

> 74 years old

0.68 (0.55; 0.83)

 

T Stage - size

    

T1

1

<0.001

 

0.189

T2

0.79 (0.66-0.95)

 

T3 and T4

0.58 (0.41-0.81)

 

Circumstances of diagnosis

    

Screening

1

<0.001

1

0.005

Not screening

0.72 (0.62; 0.83)

0.78 (0.66-0.93)

Time to go to the nearest reference cancer care centre

    

< 10 minutes

1

<0.001

1

<0.001

10 to 20 minutes

0.98 (0.80; 1.21)

0.86 (0.68-1.07)

20 to 35 minutes

0.70 (0.56; 0.88)

0.56 (0.43-0.73)

> 35 minutes

0.50 (0.42; 0.61)

0.38 (0.29-0.50)

Aggregate data

    

Place of residence

    

Rural

0.72 (0.62; 0.84)

<0.001

0.68 (0.53-0.87)

0.002

Urban

1

1

Townsend index

    

Quintile 1 (most affluent)

1

<0.001

1

0.013

Quintile 2

0.84 (0.60; 1.18)

0.84 (0.58-1.21)

Quintile 3

0.73 (0.52; 1.03)

0.74 (0.52-1.08)

Quintile 4

0.67 (0.49; 0.93)

0.69 (0.48-0.97)

Quintile 5 (most deprived)

0.65 (0.49; 0.88)

0.61 (0.44-0.85)

  1. * CI: Confidence Interval.