Development and validation of GMI signature based random survival forest prognosis model to predict clinical outcome in acute myeloid leukemia.

BMC Med Genomics · 2019 · PMC6595612 · PMID 31242922

Europe PMC DOI

hedged sentence

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closest p · 0.0× alpha

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boldest claim

The sentences

highly significantp = 1.263e-11actually significant

4 b, the Kaplan-Meier analyses exhibited highly significant differences in time to overall survival between two different risk groups (hazard ratio [HR], 16.4; 95% confidence interval [CI], 5.68–47.3; p = 1.263e-11).

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