Table 3. Binary logistic regression model identifies tumour depth as an independent predictor of lower cSCC R-Smad activity.
| Variable | DF | Χ2 (Wald) | P (<0.05) | R.R | 95% CI |
|---|---|---|---|---|---|
| Depth | 1 | 7.447 | 0.006 | 1.127 | 1.034-1.227 |
| Poorly diff | 1 | 3.125 | 0.077 | ||
| Site = Lower limb | 1 | 1.168 | 0.280 | ||
| Diameter | - | 1.107 | 0.293 | ||
| Invasion beyond fat | 1 | 0.739 | 0.390 | ||
| Site = Torso | 1 | 0.629 | 0.428 | ||
| Clark level ≥IV | 1 | 0.140 | 0.708 | ||
| Site = Upper limb | 1 | 0.114 | 0.736 | ||
| Site = High-risk H&N | 1 | 0.82 | 0.774 | ||
| PNI | 1 | 0.48 | 0.827 | ||
| Site = Low-risk H&N | 1 | 0.019 | 0.889 |
Binary outcome = TGF-β Signalling “off” * (0=No, 1=Yes).
*≤25th Percentile of the mean (PO4-SMAD2 = ≤ 76, PO4-SMAD3 = ≤ 41). B = Co-efficients, S.E = Standard error of co-efficients, Wald = Wald chi-squared value. df = degree of freedom, Sig. = 2-tailed p-value for testing null hypothesis. Exp(B) = Exponentiation of co-efficients (Odds ratios), C.I = Confidence intervals. H&N = Sun-exposed head and neck, Clark Level IV = Invasion into the reticular dermis, PNI = Perineural invasion.