Early prediction of neoadjuvant chemotherapy response for advanced breast cancer using PET/MRI image deep learning.

Sci Rep · 2020 · PMC7712787 · PMID 33273490

Europe PMC DOI

hedged sentence

0.0910

closest p · 1.8× alpha

0.0910

boldest claim

The sentences

approached the borderline of significancep = 0.091so close (0.05 < p ≤ 0.1)

Both ΔMTV and ΔTLG had the highest AUC at 0.833 (95% CI 0.429–0.991); approached the borderline of significance (p = 0.091).The optimal cutoff values responders for ΔMTV and ΔTLG were − 71.9% and − 79.9%, respectively, with 100%/67% sensitivity/specificity for both parameters.

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