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. Author manuscript; available in PMC: 2021 Oct 15.
Published in final edited form as: Cell. 2020 Oct 1;183(2):363–376.e13. doi: 10.1016/j.cell.2020.09.001

Figure 5: DIREct-On enables fully noninvasive outcome classification.

Figure 5:

A) Proportion of patients expected to achieve DCB (blue) or NDB (orange) by the DIREct-Pre model stratified by clinical outcome determined by RECIST in the DIREct Discovery Cohort (n = 34).

B) Probability of PFS for high DIREct-Pre score (median = 8.2 mo.) and low DIREct-Pre score (median = 2.0 mo.) patients in the DIREct Discovery Cohort, using the optimal cut-point identified by LOOCV analysis (n = 34).

C) Probability of PFS for high DIREct-Pre score (median = 8.4 mo.) and low DIREct-Pre score (median = 2.6 mo.) patients in the DIREct Validation Cohort using the cut-point defined in the DIREct Discovery Cohort (n = 38).

D) Hazard ratio (top) or accuracy (bottom) for low scores (below LOOCV-generated cut-point) of each model with the indicated parameters only considering patients with all parameters available in the DIREct Discovery Cohort (n = 26). Error bars represent the 95% CIs generated by bootstrapping. NS = not significant, ** = P < 0.01.

E) Proportion of patients expected to achieve DCB (blue) or NDB (orange) by DIREct-On stratified by clinical outcome determined by RECIST in the DIREct Discovery Cohort (n = 34).

F) Probability of PFS for high DIREct-On score (median = 16.5 mo.) and low DIREct-On score (median = 1.9 mo.) patients in the DIREct Discovery Cohort, using the optimal cut-point identified by LOOCV analysis (n = 34).

G) Probability of PFS for high DIREct-On score (median = 8.5 mo.) and low DIREct-On score (median = 2.1 mo.) patients in the DIREct Validation Cohort using the cut-point defined in the DIREct Discovery Cohort (n = 38).

H) Accuracy for each individual parameter and DIREct-On in the combined DIREct Discovery and Validation Cohorts for those cases with all data types available, using the cut-points identified the DIREct Discovery Cohort (n = 58). Error bars represent 95% CIs generated by bootstrapping. ** = P < 0.01, *** = P < 0.001.

I) Net reclassification improvement of DIREct-On compared to each individual feature (top) and DIREct-On compared to Bayesian models with each feature that comprises DIREct-On removed (bottom). Errors bars represent 95% CIs generated by bootstrapping. * = P < 0.01, ** = P < 0.01. See also Figure S5.