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Transforming the interpretation of significance in heart failure trials

Heart failure (HF) therapeutics are held to a high scientific and regulatory standard. Conclusions and interpretation of randomized clinical trials (RCTs) have been viewed narrowly on whether primary endpoints meet thresholds of significance based on achieving a pre-specified ‘P-value’. Reductionist interpretations of P-values at traditional cut-offs have been recently questioned. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) Working Group (www.gradeworkinggroup.org) suggested that clinical decision-making should not depend on binary P-value thresholds. The American Statistical Association has promoted the continuous interpretation of P-values and abandonment of language surrounding ‘statistical significance’.1,2 The Heart Failure Collaboratory, a multidisciplinary working group hosted a meeting at the US Food and Drug Administration on 25 July 2019 reappraising statistical approaches and reporting in emerging HF clinical trials. Citing concerns surrounding the reproducibility of RCT findings, researchers have even gone to another extreme by proposing a reduction of the generally accepted threshold of statistical significance from a P-value of 0.05 to 0.005 and to reclassify values falling between 0.05 and 0.005 as merely ‘suggestive’.3 In light of this shifting landscape, we examined the distribution of observed P-values across recently conducted HF RCTs and critically discuss issues related to interpreting and communicating uncertainty within trial results in an effort to guide better clinical usefulness and interpretation.