Calculation of the fragility index of randomized controlled trials in epilepsy published in twelve major journals

Das, Saibal; Xaviar, Suja

doi:10.1016/j.eplepsyres.2019.106258

Cited by 6 publications

(6 citation statements)

References 19 publications

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“…Conversely, the findings of the FI analysis are consistent with other studies examining the FI of MD trials [21], peri-operative medicine [64], critical care [65], epilepsy [66], orthopedics [67], and other medical areas, reporting similarly low FIs. Moreover, the use of the RFI in a broader context can reduce the risk of overlooking advantageous interventions [18].…”

Section: Discussionsupporting

confidence: 86%

Fragility of cardiovascular outcome trials (CVOTs) examining nutrition interventions among patients with diabetes mellitus: a systematic review of randomized controlled trials

et al. 2022

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Purpose There is controversy regarding the optimal statistical method to interpret how robust is a statistically significant result. The fragility index (FI) and the reverse fragility index (RFI) are quantitative measures that can facilitate the appraisal of a clinical trial’s robustness. This study was performed to evaluate the FI and RFI of randomized controlled trials (RCTs) examining nutritional interventions in patients with diabetes mellitus, focusing on cardiovascular outcomes. Methods A systematic search was conducted and relevant RCTs were identified in three databases. RCTs examining nutritional interventions (supplements or dietary patterns) in patients with DM with dichotomous primary endpoints involving cardiovascular outcomes were eligible. Data were extracted to compose 2 × 2 event tables and the FI and RFI were calculated for each comparison, using Fisher’s exact test. Risk of bias (RoB) of the included RCTs was assessed with the Cochrane RoB 2.0 tool. Results A total of 14,315 records were screened and 10 RCTs were included in the analyses. The median FI of the paired comparisons was 3 (IQR: 2–4) and the median RFI was 8 (IQR: 4.5–17). RoB and heterogeneity were low. Conclusions RCTs examining nutritional interventions and cardiovascular outcomes among patients with diabetes mellitus appear to be statistically fragile. Τhe FI and the RFI can be reported and interpreted as an additional perspective of a trial’s robustness. Highlights • In the evidence-healthcare era, assessing how robust statistically significant results are remains a matter of controversy. • Recently, the fragility index (FI) and reverse fragility index (RFI) were proposed to assess the robustness of randomized controlled trials (RCTs) with 2 × 2 comparisons. • When applying the FI and RFI, RCTs examining nutritional interventions and cardiovascular outcomes among patients with diabetes mellitus (DM) appear to be statistically fragile. • Τhe FI and the RFI can be reported and interpreted as an additional perspective of a trial’s robustness. • RCTs implementing nutrition interventions among patients with DM can improve their methodology.

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Section: Discussionsupporting

confidence: 86%

Fragility of cardiovascular outcome trials (CVOTs) examining nutrition interventions among patients with diabetes mellitus: a systematic review of randomized controlled trials

et al. 2022

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“…29 It is intuitive that for any hypothetical study, exaggerating the outcome difference to yield lower P values would lead to correspondingly higher FIs, and vice versa. An analysis of 17 RCTs in the New England Journal of Medicine 30 and of the traumatic brain injury literature 31 came to the same conclusion (although an analysis of 10 RCTs in the epilepsy literature found no correlation 32 ). Carter et al argue that the FI is just the P value in disguise, 29 and adds little to traditional statistics.…”

Section: Fi Is Influenced By the P Value Sample Size And Event Ratesmentioning

confidence: 83%

The Fragility Index for Assessing the Robustness of the Statistically Significant Results of Experimental Clinical Studies

2021

J GEN INTERN MED

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I n a randomized controlled trial (RCT) comparing treatments A and B, a null hypothesis (H 0 ) of no difference in a primary outcome of interest is defined. Whether any observed difference is statistically significant has traditionally been based on the P value and the confidence interval (CI). For a century, an arbitrary threshold of 0.05 (1/20) has been used to define statistical significance. 1 Because this probability is quite low, we conclude that P ≤ 0.05 suggests that the observed difference between A and B is incompatible with H 0 , and, with a ≥ 95% degree of certainty, that A and B are different. The 95% CI is a lower-upper limit in which the true effect estimate lies within a 95% certainty. A 95% CI that does not include the null effect size indicates the observed difference has reached statistical significance, and H 0 is rejected. The 95% CI provides information about the precision of the estimate and complements the P value. Reporting both is recommended.Use of a P value of 0.05 to dichotomize whether treatments A and B are "truly" different is appealing because of its simplicity. Indeed, for all its many limitations, 2 its use actually increased from 1990 to 2015 in MEDLINE and PubMed Central abstracts and articles. 3 Statistical significance carries considerable weight. Researchers, editors and reviewers, readers, and the press tend to become more excited about positive results. 4 However, a shocking number of scientific studies and meta-analyses are not reproducible or replicable. [5][6][7] A reasonable question to ask is: if a positive study was to be repeated, how "easy" might it be for the results to change from being statistically significant to non-significant (and thus, rightly or wrongly, lose some of their appeal)? What if there was, by sheer chance, one or several more (or less) outcome event(s) in one of the comparative groups? Would the coveted statistical significance be lost? In recent years, there has been much interest in a metric-the fragility index (FI), [8][9][10][11] first proposed 3 decades ago 12 -to test the robustness/fragility of statistically significant results. The various applications and implications of the FI are discussed herein.

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“…The original fragility index has been applied to RCTs in oncology and other areas of medicine. 17 , 19 , 71 , 72 , 73 , 74 However, the original fragility index is based on binary outcomes and the Fisher exact test, which could be misleading for time-to-event data, in which the primary interest is the timing of events. 19 Although descriptions of time-to-event fragility exist, 18 , 19 to our knowledge, no previous peer-reviewed original investigations have estimated time-aware fragility index for clinical trials, including oncology trials.…”

Section: Discussionmentioning

confidence: 99%

Survival-Inferred Fragility Index of Phase 3 Clinical Trials Evaluating Immune Checkpoint Inhibitors

et al. 2020

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Key Points Question How stable are the conclusions of phase 3 randomized clinical trials of immune checkpoint inhibitors in oncology? Findings This cross-sectional study of 45 randomized clinical trials calculated the survival-inferred fragility index and found that many oncologic trials assessing immune checkpoint inhibitors have a low survival-inferred fragility index, often less than a small fraction of the sample size and less than the number of patients censored soon after randomization. Meaning These results challenge the robustness of many phase 3 randomized clinical trials of immune checkpoint inhibitors in oncology and address the uncertainty regarding their potential clinical benefit.

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Calculation of the fragility index of randomized controlled trials in epilepsy published in twelve major journals

Cited by 6 publications

References 19 publications

Fragility of cardiovascular outcome trials (CVOTs) examining nutrition interventions among patients with diabetes mellitus: a systematic review of randomized controlled trials

Fragility of cardiovascular outcome trials (CVOTs) examining nutrition interventions among patients with diabetes mellitus: a systematic review of randomized controlled trials

The Fragility Index for Assessing the Robustness of the Statistically Significant Results of Experimental Clinical Studies

Survival-Inferred Fragility Index of Phase 3 Clinical Trials Evaluating Immune Checkpoint Inhibitors

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