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. Published on behalf of the European Society of Cardiology. All rights reserved.
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. Published on behalf of the European Society of Cardiology. All rights reserved.
Authors: Mario Gaudino; Irbaz Hameed; Mohamed Rahouma; Faiza M Khan; Derrick Y Tam; Giuseppe Biondi-Zoccai; Michelle Demetres; Mary E Charlson; Marc Ruel; Filippo Crea; Volkmar Falk; Leonard N Girardi; Stephen Fremes; Joanna Chikwe Journal: JAMA Intern Med Date: 2020-07-01 Impact factor: 21.873
Authors: Muhammad Shahzeb Khan; Rohan Kumar Ochani; Asim Shaikh; Muhammad Shariq Usman; Naser Yamani; Safi U Khan; M Hassan Murad; John Mandrola; Rami Doukky; Richard A Krasuski Journal: Circ Cardiovasc Qual Outcomes Date: 2019-12-11