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. 2023 May 19;26(6):106932. doi: 10.1016/j.isci.2023.106932

Table 4.

Performance of models in predicting DMFS

Models Training cohort
Validation cohort
C-index 95% CI p value C-index 95% CI p value
Radiomics combined model 0.66 0.59–0.73 Ref 0.71 0.62–0.80 Ref
Clinical model 0.77 0.71–0.83 0.005 0.73 0.64–0.82 0.97
DL combined model 0.85 0.78–0.92 <0.001 0.84 0.78–0.90 0.02
RC model 0.78 0.71–0.84 <0.001 0.78 0.70–0.86 0.43
DC model 0.89 0.84–0.94 <0.001 0.87 0.80–0.93 0.009
DC model vs. DL combined model 0.02 0.76
RC model vs. Clinical model 0.65 0.28
AUC 95% CI p value AUC 95% CI p value
Radiomics combined model 0.67 0.59–0.74 Ref 0.70 0.60–0.80 Ref
Clinical model 0.78 0.73–0.85 0.01 0.72 0.62–0.81 0.78
DL combined model 0.85 0.78–0.93 <0.001 0.84 0.77–0.91 0.02
RC model 0.80 0.73–0.87 <0.001 0.74 0.65–0.84 0.36
DC model 0.90 0.85–0.96 <0.001 0.85 0.78–0.93 0.01
DC model vs. DL combined model 0.007 0.75
RC model vs. Clinical model 0.53 0.65

Note that, DL combined model and Radiomics combined model were conducted based on the three MR sequences (T1W, T2W, and CET1W). DC model, a model combining deep learning and clinical variables. RC model, a model combining radiomics and clinical variables.

Abbreviations: NPC, nasopharyngeal carcinoma; C-index, Harrell’s concordance index; CI: confidence interval; DL, deep learning; Ref, reference; AUC, area under curve.