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. 2020 Mar 20;4(6):1082–1092. doi: 10.1182/bloodadvances.2019001201

Table 2.

Results of the ROC analysis used to identify optimal cutoff points for PFS and OS in the testing (N = 141) and validation (N = 113) cohorts

Functional PET parameters ROC analysis for PFS ROC analysis for OS
Cutoff point Sensitivity, % Specificity, % AUC P Cutoff point Sensitivity, % Specificity, % AUC P
Testing set SUVmax 20 60 55 0.556 .342 24.2 74 40 0.550 .433
MTV, mL 931 57 75 0.629 .029 1149 52 81 0.670 .011
TLG 3960 63 62 0.620 .034 6991 57 73 0.661 .012
MH (AUC-CSH) 0.43 53 66 0.545 .474 0.43 52 69 0.555 .431
Validation set SUVmax 31 27 86 0.507 .917 31 32 86 0.582 .267
MTV, mL 336 73 54 0.629 .029 336 79 54 0.637 .070
TLG 3186 55 66 0.574 .318 3574 63 70 0.634 .079
MH (AUC-CSH) 0.47 53 66 0.527 .730 0.46 42 85 0.648 .046

Bold P values indicate statistically significant results (P < .05).