Prediction of Pathologic Findings with MRI-Based Clinical Staging Using the Bayesian Network Modeling in Prostate Cancer: A Radiation Oncologist Perspective.

Cancer Res Treat · 2022 · PMC8756129 · PMID 34015891

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closest p · 1.2× alpha

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boldest claim

The sentences

marginal significancep=0.060so close (0.05 < p ≤ 0.1)

the Roach formula In terms of ECE prediction, BN model showed improved performance with marginal significance compared to the Roach formula (AUC, 0.76 vs. 0.74; DeLong’s method p=0.060) ( Fig. 5A ).

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marginally significantno p-value reported

Furthermore, in the internal comparison between the BN model and Roach formula [ 3 ], our BN model showed improved AUC values compared to the Roach model for ECE (p=0.060) and SVI (p < 0.001) prediction, although the difference for ECE was marginally significant and the absolute difference were modest.

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