ABT-199 induces apoptosis within 8 hours and the most significant dose-limiting toxicity is tumor lysis syndrome.
The model with medium AUC performance was selected as the optimum model with the most significant dose-volume predictive factor.
The most significant dose-volume predictive factor for the logistic regression NTCP model can be determined by using statistical analysis.
The most significant dose-responsive transcripts for each of the enriched GO categories are illustrated in the heatmaps to the right of Figure 5, panels A-D.
In this study, we confirmed that and determined the most significant dose-volume predictive factor by using the LASSO with bootstrapping technique.
The most significant dose-volume predictive factor for the logistic regression model was determined by using the LASSO with bootstrapping technique [ 8, 10].
The most significant dose-volume predictive factor for the logistic regression NTCP model was determined by using the LASSO with bootstrapping technique (the LASSO shrinking path diagrams are shown in Figure 2).
The most significant dose-volume predictive factor for the logistic regression NTCP model was determined by the LASSO with V16 Gy as the cutoff dose for group 0 and V40 Gy for group 1, respectively.
The most significant dose-limiting toxicity (DLT) was rash, which was maculopapular in nature with a truncal distribution, and was distinct from the acneiform rash seen with epidermal growth factor receptor inhibitors.
The type of biologic therapy was by far the most significant predictor of dose escalation, as patients starting infliximab were over 6 times more likely to increase dose than patients starting on etanercept (Transformed Odds Ratio [OR] = 6.38; p < 0.0001).
This synergism is observed over a range of concentrations 5-1000 nM), but is most significant at low doses, where inhibition of cell growth by Ara-C occurs but cell killing is minimal.
