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AimsThe effect of statins on risk of heart failure (HF) hospitalization and HF death remains uncertain. We aimed to establish whether statins reduce major HF events.Methods and resultsWe searched Medline, EMBASE, and the Cochrane Central Register of Controlled Trials for randomized controlled endpoint statin trials from 1994 to 2014. Collaborating trialists provided unpublished data from adverse event reports. We included primary- and secondary-prevention statin trials with >1000 participants followed for >1 year. Outcomes consisted of first non-fatal HF hospitalization, HF death and a composite of first non-fatal HF hospitalization or HF death. HF events occurring

Aims Guidelines for the management of chronic heart failure (CHF) cite the results of randomized controlled trials (RCTs) to support treatment recommendations. The significance of an observed treatment-effect relies on the use of a boundary P-value, most commonly P<0.05. There is concern about relying on arbitrary threshold P-values to report results as ‘statistically significant’. The ‘fragility index’ (FI) has been proposed as an additional measure of the robustness of trial findings. FI is the minimum number of events needing to change from a non-event to an event in order to render a significant result non-significant. We calculated the FI to examine the robustness of statistically significant RCTs in CHF. Methods and results Two reviewers extracted data from RCTs supporting treatment recommendations in CHF guidelines. Twenty-five eligible trials were identified with a median sample size of 2331 patients (range 129–8399) and a median number of primary endpoints of 688.5 (range 88–2031). For the primary endpoint (analysed for 20 trials), the median FI was 26 (range 0–118). The FI was≤10 in 7 (35%) of these 20 trials, and in 4 (20%) trials the number of patients lost to follow-up in the treatment group exceeded the FI. Conclusion The results of some large RCTs in CHF hinge on a small number of events. The FI offers an additional, easy to understand metric, which augments the standard reporting of boundary P-values for statistical significance. The FI helps in the interpretation of the robustness of the results of RCTs. [ABSTRACT FROM AUTHOR]