Table 2. Logistic regression model to predict use of tumor genome sequencing (n = 215).
| Variables | Univariate analysis OR (95% CI) | P Value | Multivariate analysis* Adjusted OR (95% CI) | P Value | |||
|---|---|---|---|---|---|---|---|
| Academic institution (vs Non-Academic) | 2.33 | (1.21–4.60) | 0.006 | ||||
| Time allocated to research (>25% vs ≤25%) | 2.85 | (1.56–5.28) | 0.0002 | 3.37 | 1.84–6.15 | <0.0001 | |
| Field (Other vs Medical Oncologist) | 1.02 | (0.39–2.53) | 0.97 | ||||
| Number of new breast cancer patient/months (>10 vs ≤10) | 1.43 | (0.77–2.67) | 0.23 | ||||
| Years of clinical practice (>10 vs ≤10) | 1.11 | (0.61–2.05) | 0.71 | ||||
| Continent of clinical practice (vs Europe) | Asia | 3.56 | (0.90–16.93) | 0.07 | 5.76 | 1.57–21.15 | 0.01 |
| Other continents | 1.27 | (0.63–2.55) | 0.50 | 1.39 | (0.68–2.82) | 0.37 | |
| Guidelines in institute (Yes vs No/I do not know) | 2.06 | (0.97–4.39) | 0.06 | 2.09 | 0.99–4.42 | 0.05 | |
*Results showed only for variables associated with use of tumor genome sequencing with p value equal or less to 0.05.