Table 3.
Results of logistic regression for the model
| Parameter | Df | Estimate (β) | Pr > chisq | Odds ratio | CI 95% |
|---|---|---|---|---|---|
| Intercept |
1 |
0.953 |
0.467 |
|
|
| Marital status |
1 |
0.013 |
0.647 |
1.295 |
0.429- 3.912 |
| Gender |
1 |
−1.012 |
0.010 |
0.132 |
0.028 - 0.617 |
| Age |
1 |
−0.038 |
0.102 |
0.963 |
0.920 - 1.008 |
| Education 0 |
1 |
0.544 |
0.256 |
0.982 |
0.189 – 5.104 |
| 1 |
1 |
−0.761 |
0.116 |
0.266 |
0.46 – 1.532 |
| 2 |
1 |
−0.345 |
0.549 |
0.404 |
0.059 – 2.768 |
| Tumour site 0 |
1 |
−0.297 |
0.562 |
0.151 |
0.026 – 0.869 |
| 1 |
1 |
−1.476 |
0.028 |
0.046 |
0.005 – 0.421 |
| 2 |
1 |
0.177 |
0.811 |
0.242 |
0.026 - 2.263 |
| Treatment Intent 0 |
1 |
0.199 |
0.686 |
0.730 |
0.102 – 5.208 |
| 1 | 1 | −0.712 | 0.282 | 0.293 | 0.025 – 3.85 |
Marital status (married = 1, single=0) Gender(male=1, female=0); Age was used as a continuous variable Educ. (Basic = 0, Sec. = 1, Tert. = 2, uneduc. = 3) Tumour site (Abd/pel = 0, H/Neck = 1, Thorax = 2, other =3) Treatment Int. (curative = 0, Palliative = 1, unspecified =2).